OmniOpt2

Setting	Value
Max. nr. evaluations	1000
Number random steps	20
Nr. of workers (parameter)	20
Main process memory (GB)	8
Worker memory (GB)	1
Nr. imported jobs	500
Name	Type	Lower bound	Upper bound	Type	Log Scale?
recent_samples_size	int	1	5000	int	No
significance	float	0.001	0.999	float	No
gamma	float	0.001	0.999	float	No
max_node_size	int	1	5000	int	No
max_tree_depth	int	1	5000	int	No
max_time_stationary	int	1	5000	int	No
Failed	Succeeded	Running	Total
2	658	1	661
name	min/max
ACCURACY	max
RUNTIME	min
Key	Value
config_yaml	None
config_toml	None
config_json	None
num_random_steps	20
max_eval	None
run_program	None
experiment_name	None
mem_gb	1
parameter	None
continue_previous_job	/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_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	30
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
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<html lang='en'>
	<head>
		<meta charset='UTF-8'>
		<meta name='viewport' content='width=device-width, initial-scale=1.0'>
		<title>Exported &raquo;s4122485/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0&laquo; from OmniOpt2-Share</title>
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				padding: 0px !important;
				width: revert !important;
				min-width: revert !important;
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			._share_link {
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				background-color: #f8f9fa;
				padding: 0px;
				text-align: center;
				border-top: 1px solid #dee2e6;
				width: 100%;
				box-sizing: border-box;
				position: fixed;
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				z-index: 2;
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				height: 26px;
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				width: 0;
				height: 0;
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				cursor: pointer;
				top: 0;
				left: 0;
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				background-color: #ccc;
				transition: .4s;
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				content: "";
				height: 20px;
				width: 20px;
				left: 3px;
				bottom: 3px;
				background-color: white;
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			input:checked + .slider {
				background-color: #444;
			}
			
			input:checked + .slider:before {
				transform: translateX(24px);
			}
			
			.mode-text {
				position: absolute;
				top: 5px;
				left: 65px;
				font-size: 14px;
				color: black;
				transition: .4s;
				width: 65px;
				display: block;
				font-size: 0.7rem;
				text-align: center;
			}
			
			input:checked + .slider .mode-text {
				content: "Dark Mode";
				color: white;
			}
			
			#mainContent {
				height: fit-content;
				min-height: 100%;
			}
			
			li {
				text-align: left;
			}
			
			#share_path {
				margin-bottom: 20px;
				margin-top: 20px;
			}
			
			#sortForm {
				margin-bottom: 20px;
			}
			
			.share_folder_buttons {
				margin-top: 10px;
				margin-bottom: 10px;
			}
			
			.nav_tab_button {
				margin: 10px;
			}
			
			.header_table {
				margin: 10px;
			}
			
			.no_border {
				border: unset !important;
			}
			
			.gui_table {
				padding: 5px !important;
			}
			
			.gui_parameter_row {
			}
			
			.gui_parameter_row_cell {
				border: unset !important;
			}
			
			.gui_param_table {
				width: 95%;
				margin: unset !important;
			}
			
			table td, table tr,
			.parameterRow table {
				padding: 2px !important;
			}
			
			.parameterRow table {
				margin: 0px;
				border: unset;
			}
			
			.parameterRow > td {
				border: 0px !important;
			}
			
			.parameter_config_table td, .parameter_config_table tr, #config_table th, #config_table td, #hidden_config_table th, #hidden_config_table td {
				border: 0px !important;
			}
			
			.green_text {
				color: green;
			}
			
			.remove_parameter {
				white-space: pre;
			}
			
			select {
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				background-color: #fff;
				color: #222;
				padding: 5px 30px 5px 5px;
				border: 1px solid #555;
				border-radius: 5px;
				cursor: pointer;
				outline: none;
				transition: all 0.3s ease;
				background:
					url("data:image/svg+xml;charset=UTF-8,%3Csvg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 10 6'%3E%3Cpath fill='%23888' d='M0 0l5 6 5-6z'/%3E%3C/svg%3E")
					no-repeat right 10px center,
				linear-gradient(180deg, #fff, #ecebe5 86%, #d8d0c4);
				background-size: 12px, auto;
			}
			
			select:hover {
				border-color: #888;
			}
			
			select:focus {
				border-color: #4caf50;
				box-shadow: 0 0 5px rgba(76, 175, 80, 0.5);
			}
			
			select::-ms-expand {
				display: none;
			}
			
			input, textarea {
				border-radius: 5px;
			}
			
			#search {
				width: 200px;
				max-width: 70%;
				background-image: url(images/search.svg);
				background-repeat: no-repeat;
				background-size: auto 40px;
				height: 40px;
				line-height: 40px;
				padding-left: 40px;
				box-sizing: border-box;
			}
			
			input[type="checkbox"] {
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				width: 25px;
				height: 25px;
				border: 2px solid #3498db;
				border-radius: 5px;
				background-color: #fff;
				position: relative;
				cursor: pointer;
				transition: all 0.3s ease;
				width: 25px !important;
			}
			
			input[type="checkbox"]:checked {
				background-color: #3498db;
				border-color: #2980b9;
			}
			
			input[type="checkbox"]:checked::before {
				content: '✔';
				position: absolute;
				left: 4px;
				top: 2px;
				color: #fff;
			}
			
			input[type="checkbox"]:hover {
				border-color: #2980b9;
				background-color: #3caffc;
			}
			
			.toc {
				margin-bottom: 20px;
			}
			
			.toc li {
				margin-bottom: 5px;
			}
			
			.toc a {
				text-decoration: none;
				color: #007bff;
			}
			
			.toc a:hover {
				text-decoration: underline;
			}
			
			.table-container {
				width: 100%;
				overflow-x: auto;
			}
			
			.section-header {
				background-color: #1d6f9a !important;
				color: white;
			}
			
			.warning {
				color: red;
			}
			
			.li_list a {
				text-decoration: none;
			}
			
			.gridjs-td {
				white-space: nowrap;
			}
			
			th, td {
				border: 1px solid gray !important;
			}
			
			.no_border {
				border: 0px !important;
			}
			
			.no_break {
			
			}
			
			img {
				user-select: none;
				pointer-events: none;
			}
			
			#config_table, #hidden_config_table {
				user-select: none;
			}
			
			.copy_clipboard_button {
				margin-bottom: 10px;
			}
			
			.badge_table {
				background-color: unset !important;
			}
			
			.make_markable {
				user-select: text;
			}
			
			.header-container {
				display: flex;
				flex-wrap: wrap;
				align-items: center;
				justify-content: space-between;
				gap: 1rem;
				padding: 10px;
				background: var(--header-bg, #fff);
				border-bottom: 1px solid #ccc;
			}
			
			.header-logo-group {
				display: flex;
				gap: 1rem;
				align-items: center;
				flex: 1 1 auto;
				min-width: 200px;
			}
			
			.logo-img {
				max-height: 45px;
				height: auto;
				width: auto;
				object-fit: contain;
				pointer-events: unset;
			}
			
			.header-badges {
				flex-direction: column;
				gap: 5px;
				align-items: flex-start;
				flex: 0 1 auto;
				margin-top: auto;
				margin-bottom: auto;
			}
			
			.badge-img {
				height: auto;
				max-width: 130px;
				margin-top: 3px;
			}
			
			.header-tabs {
				margin-top: 10px;
				display: flex;
				flex-wrap: wrap;
				gap: 10px;
				flex: 2 1 100%;
				justify-content: center;
			}
			
			.nav-tab {
				display: inline-block;
				text-decoration: none;
				padding: 8px 16px;
				border-radius: 20px;
				background: linear-gradient(to right, #4a90e2, #357ABD);
				color: white;
				font-weight: bold;
				white-space: nowrap;
				transition: background 0.2s ease-in-out, transform 0.2s;
				box-shadow: 0 2px 4px rgba(0,0,0,0.2);
			}
			
			.nav-tab:hover {
				background: linear-gradient(to right, #5aa0f2, #4a90e2);
				transform: translateY(-2px);
			}
			
			.current-tag {
				padding-left: 10px;
				font-size: 0.9rem;
				color: #666;
			}
			
			.header-theme-toggle {
				flex: 1 1 auto;
				align-items: center;
				margin-top: 20px;
				min-width: 120px;
			}
			
			.switch {
				position: relative;
				display: inline-block;
				width: 60px;
				height: 30px;
			}
			
			.switch input {
				display: none;
			}
			
			.slider {
				position: absolute;
				top: 0; left: 0; right: 0; bottom: 0;
				background-color: #ccc;
				border-radius: 34px;
				cursor: pointer;
			}
			
			.slider::before {
				content: "";
				position: absolute;
				height: 24px;
				width: 24px;
				left: 3px;
				bottom: 3px;
				background-color: white;
				transition: .4s;
				border-radius: 50%;
			}
			
			input:checked + .slider {
				background-color: #2196F3;
			}
			
			input:checked + .slider::before {
				transform: translateX(30px);
			}
			
			@media (max-width: 768px) {
				.header-logo-group,
				.header-badges,
				.header-theme-toggle {
					justify-content: center;
					flex: 1 1 100%;
					text-align: center;
					width: inherit;
				}
			
				.logo-img {
					max-height: 50px;
					pointer-events: unset;
				}
			
				.badge-img {
					max-width: 100px;
				}
			
				.hide_on_mobile {
					display: none;
				}
			
				.nav-tab {
					font-size: 0.9rem;
					padding: 6px 12px;
				}
			
				.header_button {
					white-space: pre;
					font-size: 2em;
				}
			}
			
			.header_button {
				white-space: pre;
				margin-top: 20px;
				margin: 5px;
			}
			
			.line_break_anywhere {
				line-break: anywhere;
			}
			
			.responsive-container {
				display: flex;
				flex-wrap: wrap;
				justify-content: space-between;
				gap: 20px;
			}
			
			.responsive-container .half {
				flex: 1 1 48%;
				box-sizing: border-box;
				min-width: 500px;
			}
			
			.config-section table {
				width: 100%;
				border-collapse: collapse;
			}
			
			@media (max-width: 768px) {
				.responsive-container .half {
					flex: 1 1 100%;
				}
			}
			
			@keyframes spin {
				0% {
					transform: rotate(0deg);
				}
			
				100% {
					transform: rotate(360deg);
				}
			}
			
			.rotate {
				animation: spin 2s linear infinite;
				display: inline-block;
			}
			
			input::placeholder {
				font-family: 'IBM Plex Sans', 'Source Sans Pro', sans-serif;
			}
			
			.gridjs-th-content {
				overflow: visible !important;
			}
			
			.error_text {
				color: red;
			}
			
			h1, h2, h3, h4, h5, h6 {
				margin-top: 1em;
				font-weight: bold;
				color: #333;
				border-left: 5px solid #ccc;
				padding-left: 0.5em;
			}
			
			.no_cursive {
				font-style: normal;	
			}
			
			.caveat {
				background-color: #fff8b3;
				border: 1px solid #f2d600;
				padding: 1em 1em 1em 70px;
				position: relative;
				font-family: sans-serif;
				color: #665500;
				margin: 1em 0;
				border-radius: 4px;
			}
			
			.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
				margin-top: 0;
				margin-bottom: 0.5em;
				font-weight: bold;
			}
			
			.caveat::before {
				content: "⚠️";
				font-size: 50px;
				line-height: 1;
				position: absolute;
				left: 10px;
				top: 50%;
				transform: translateY(-50%);
				pointer-events: none;
				user-select: none;
			}
			
			.caveat.warning::before { content: "⚠️"; }
			.caveat.stop::before { content: "🛑"; }
			.caveat.exclamation::before { content: "❗"; }
			.caveat.alarm::before { content: "🚨"; }
			.caveat.tip::before { content: "💡"; }
			
			.tutorial_icon {
				display: inline-block;
				font-size: 1.3em;
				line-height: 1;
				vertical-align: middle;
				transform: translateY(-10%);
				padding: 0.2em 0;
			}
			
			.highlight {
				background-color: yellow;
				font-weight: bold;
			}
			
			#searchResults li {
				opacity: 0;
				transform: translateY(8px);
				animation: fadeInUp 0.3s ease-out forwards;
				animation-delay: 0.05s;
				list-style: none;
				margin-bottom: 5px;
			}
			
			@keyframes fadeInUp {
				to {
					opacity: 1;
					transform: translateY(0);
				}
			}
			
			.search_headline {
				font-weight: bold;
				margin-top: 1em;
				margin-bottom: 0.3em;
				color: #444;
			}
			
			.search_share_path {
				color: black;
				display: block ruby;
				margin-top: 20px;
			}
			
			@media print {
				#scads_bar {
					display: none !important;
				}
			}
			

			/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
			body{
				color: #222
			}
			
			.surface{
				background: #ece9d8
			}
			
			u{
				text-decoration: none;
				border-bottom: .5px solid #222
			}
			
			a{
				color: #00f
			}
			
			a: focus{
				outline: 1px dotted #00f
			}
			
			code,code *{
				font-family: monospace
			}
			
			pre{
				display: block;
				padding: 12px 8px;
				background-color: #000;
				color: silver;
				font-size: 1rem;
				margin: 0;
				overflow: scroll;
			}
			
			summary: focus{
				outline: 1px dotted #000
			}
			
			: :-webkit-scrollbar{
				width: 16px
			}
			
			: :-webkit-scrollbar: horizontal{
				height: 17px
			}
			
			: :-webkit-scrollbar-track{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb{
				background-color: #dfdfdf;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
			}
			
			: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
				display: block
			}
			
			: :-webkit-scrollbar-button: vertical: start{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: vertical: end{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 16px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 16px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			button{
				border: none;
				background: #ece9d8;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
				border-radius: 0;
				min-width: 75px;
				min-height: 23px;
				padding: 0 12px
			}
			
			button: not(: disabled).active,button: not(: disabled): active{
				box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
			}
			
			button.focused,button: focus{
				outline: 1px dotted #000;
				outline-offset: -4px
			}
			
			label{
				display: inline-flex;
				align-items: center
			}
			
			textarea{
				padding: 3px 4px;
				border: none;
				background-color: #fff;
				box-sizing: border-box;
				-webkit-appearance: none;
				-moz-appearance: none;
				appearance: none;
				border-radius: 0
			}
			
			textarea: focus{
				outline: none
			}
			
			select: focus option{
				color: #000;
				background-color: #fff
			}
			
			.vertical-bar{
				width: 4px;
				height: 20px;
				background: silver;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
			}
			
			&: disabled,&: disabled+label{
				color: grey;
				text-shadow: 1px 1px 0 #fff
			}
			
			input[type=radio]+label{
				line-height: 13px;
				position: relative;
				margin-left: 19px
			}
			
			input[type=radio]+label: before{
				content: "";
				position: absolute;
				top: 0;
				left: -19px;
				display: inline-block;
				width: 13px;
				height: 13px;
				margin-right: 6px;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: active+label: before{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: checked+label: after{
				content: "";
				display: block;
				width: 5px;
				height: 5px;
				top: 5px;
				left: -14px;
				position: absolute;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=radio][disabled]+label: before{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
			}
			
			input[type=radio][disabled]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
			}
			
			input[type=email],input[type=password]{
				padding: 3px 4px;
				border: 1px solid #7f9db9;
				background-color: #fff;
				box-sizing: border-box;
				-webkit-appearance: none;
				-moz-appearance: none;
				appearance: none;
				border-radius: 0;
				height: 21px;
				line-height: 2
			}
			
			input[type=email]: focus,input[type=password]: focus{
				outline: none
			}
			
			input[type=range]{
				-webkit-appearance: none;
				width: 100%;
				background: transparent
			}
			
			input[type=range]: focus{
				outline: none
			}
			
			input[type=range]: :-webkit-slider-thumb{
				-webkit-appearance: none;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range]: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range]: :-webkit-slider-runnable-track{
				background: #000;
				border-right: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
			}
			
			input[type=range]: :-moz-range-track{
				background: #000;
				border-right: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
			}
			
			input[type=range].has-box-indicator: :-webkit-slider-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			input[type=range].has-box-indicator: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
			}
			
			.is-vertical{
				display: inline-block;
				width: 4px;
				height: 150px;
				transform: translateY(50%)
			}
			
			.is-vertical>input[type=range]{
				width: 150px;
				height: 4px;
				margin: 0 16px 0 10px;
				transform-origin: left;
				transform: rotate(270deg) translateX(calc(-50% + 8px))
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
				border-left: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
			}
			
			.is-vertical>input[type=range]: :-moz-range-track{
				border-left: 1px solid grey;
				border-bottom: 1px solid grey;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-thumb{
				transform: translateY(-8px) scaleX(-1)
			}
			
			.is-vertical>input[type=range]: :-moz-range-thumb{
				transform: translateY(2px) scaleX(-1)
			}
			
			.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
				transform: translateY(-10px) scaleX(-1)
			}
			
			.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
				transform: translateY(0) scaleX(-1)
			}
			
			.window{
				font-size: 11px;
				box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
				background: #ece9d8;
				padding: 3px
			}
			
			.window fieldset{
				margin-bottom: 9px
			}
			
			.title-bar{
				background: #000;
				padding: 3px 2px 3px 3px;
				display: flex;
				justify-content: space-between;
				align-items: center
			}
			
			.title-bar-text{
				font-weight: 700;
				color: #fff;
				letter-spacing: 0;
				margin-right: 24px
			}
			
			.title-bar-controls button{
				padding: 0;
				display: block;
				min-width: 16px;
				min-height: 14px
			}
			
			.title-bar-controls button: focus{
				outline: none
			}
			
			.window-body{
				margin: 8px
			}
			
			.window-body pre{
				margin: -8px
			}
			
			.status-bar{
				margin: 0 1px;
				display: flex;
				gap: 1px
			}
			
			.status-bar-field{
				box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
				flex-grow: 1;
				padding: 2px 3px;
				margin: 0
			}
			
			ul.tree-view{
				display: block;
				background: #fff;
				padding: 6px;
				margin: 0
			}
			
			ul.tree-view li{
				list-style-type: none;
				margin-top: 3px
			}
			
			ul.tree-view a{
				text-decoration: none;
				color: #000
			}
			
			ul.tree-view a: focus{
				background-color: #2267cb;
				color: #fff
			}
			
			ul.tree-view ul{
				margin-top: 3px;
				margin-left: 16px;
				padding-left: 16px;
				border-left: 1px dotted grey
			}
			
			ul.tree-view ul>li{
				position: relative
			}
			
			ul.tree-view ul>li: before{
				content: "";
				display: block;
				position: absolute;
				left: -16px;
				top: 6px;
				width: 12px;
				border-bottom: 1px dotted grey
			}
			
			ul.tree-view ul>li: last-child: after{
				content: "";
				display: block;
				position: absolute;
				left: -20px;
				top: 7px;
				bottom: 0;
				width: 8px;
				background: #fff
			}
			
			ul.tree-view ul details>summary: before{
				margin-left: -22px;
				position: relative;
				z-index: 1
			}
			
			ul.tree-view details{
				margin-top: 0
			}
			
			ul.tree-view details>summary: before{
				text-align: center;
				display: block;
				float: left;
				content: "+";
				border: 1px solid grey;
				width: 8px;
				height: 9px;
				line-height: 9px;
				margin-right: 5px;
				padding-left: 1px;
				background-color: #fff
			}
			
			ul.tree-view details[open] summary{
				margin-bottom: 0
			}
			
			ul.tree-view details[open]>summary: before{
				content: "-"
			}
			
			fieldset{
				border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
				padding: 10px;
				padding-block-start: 8px;
				margin: 0
			}
			
			legend{
				background: #ece9d8
			}
			
			menu[role=tablist]{
				position: relative;
				margin: 0 0 -2px;
				text-indent: 0;
				list-style-type: none;
				display: flex;
				padding-left: 3px
			}
			
			menu[role=tablist] button{
				z-index: 1;
				display: block;
				color: #222;
				text-decoration: none;
				min-width: unset
			}
			
			menu[role=tablist] button[aria-selected=true]{
				padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
			}
			
			menu[role=tablist] button: focus{
				outline: 1px dotted #222;outline-offset: -4px
			}
			
			menu[role=tablist].justified button{
				flex-grow: 1;text-align: center
			}
			
			[role=tabpanel]{
				padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
			}
			
			: :-webkit-scrollbar{
				width: 17px
			}
			
			: :-webkit-scrollbar-corner{
				background: #dfdfdf
			}
			
			: :-webkit-scrollbar-track: vertical{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-track: horizontal{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb{
				background-position: 50%;
				background-repeat: no-repeat;
				background-color: #c8d6fb;
				background-size: 7px;
				border: 1px solid #fff;
				border-radius: 2px;
				box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
			}
			
			: :-webkit-scrollbar-thumb: vertical{
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-thumb: horizontal{
				background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
			}
			
			: :-webkit-scrollbar-button: vertical: start{
				height: 17px;
				background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 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			}
			
			: :-webkit-scrollbar-button: vertical: end{
				height: 17px;
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			}
			
			: :-webkit-scrollbar-button: horizontal: start{
				width: 17px;
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			}
			
			: :-webkit-scrollbar-button: horizontal: end{
				width: 17px;
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			}
			
			.window{
				box-shadow: inset -1px -1px #00138c,inset 1px 1px #0831d9,inset -2px -2px #001ea0,inset 2px 2px #166aee,inset -3px -3px #003bda,inset 3px 3px #0855dd;
				border-top-left-radius: 8px;
				border-top-right-radius: 8px;
				padding: 0 0 3px;
				-webkit-font-smoothing: antialiased
			}
			
			.title-bar{
				background: linear-gradient(180deg,#0997ff,#0053ee 8%,#0050ee 40%,#06f 88%,#06f 93%,#005bff 95%,#003dd7 96%,#003dd7);
				padding: 3px 5px 3px 3px;
				border-top: 1px solid #0831d9;
				border-left: 1px solid #0831d9;
				border-right: 1px solid #001ea0;
				border-top-left-radius: 8px;
				border-top-right-radius: 7px;
				font-size: 13px;
				text-shadow: 1px 1px #0f1089;
				height: 21px
			}
			
			.title-bar-text{
				padding-left: 3px
			}
			
			.title-bar-controls{
				display: flex
			}
			
			.title-bar-controls button{
				min-width: 21px;
				min-height: 21px;
				margin-left: 2px;
				background-repeat: no-repeat;
				background-position: 50%;
				box-shadow: none;
				background-color: #0050ee;
				transition: background .1s;
				border: none
			}
			
			.title-bar-controls button: active,.title-bar-controls button: focus,.title-bar-controls button: hover{
				box-shadow: none!important
			}
			
			.title-bar-controls button[aria-label=Minimize]{
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stroke='%239e3217' d='M2 10h1'/%3E%3Cpath stroke='%23b4381a' d='M3 10h1'/%3E%3Cpath stroke='%23df9a87' d='M10 10h1m-2 1h1m-2 2h1'/%3E%3Cpath stroke='%23c6441f' d='M13 10h1m3 0h1m-8 3h1m-1 3h1'/%3E%3Cpath stroke='%23c74520' d='M14 10h2m-6 4h1m-1 1h1m7 2h1m-7 1h1m4 0h1'/%3E%3Cpath stroke='%23c7451f' d='M16 10h1m1 2h1'/%3E%3Cpath stroke='%237b2711' d='M1 11h1'/%3E%3Cpath stroke='%23a13217' d='M2 11h1'/%3E%3Cpath stroke='%23b7391a' d='M3 11h1'/%3E%3Cpath stroke='%23e09b88' d='M11 11h1'/%3E%3Cpath stroke='%23e29d89' d='M12 11h1'/%3E%3Cpath stroke='%23c94621' d='M13 11h1m-3 2h1'/%3E%3Cpath stroke='%23ca4721' d='M14 11h1m2 1h1m-7 2h1m-1 1h1m0 2h1m2 1h1'/%3E%3Cpath stroke='%23ca4821' d='M15 11h1m1 6h1'/%3E%3Cpath stroke='%23c94620' d='M16 11h1m1 3h1m-8 2h1m6 0h1'/%3E%3Cpath stroke='%23c84620' d='M17 11h1m0 2h1'/%3E%3Cpath stroke='%23a53418' d='M2 12h1'/%3E%3Cpath stroke='%23b83a1b' d='M3 12h1'/%3E%3Cpath stroke='%23e19d89' d='M11 12h1'/%3E%3Cpath stroke='%23e39e89' d='M12 12h1'/%3E%3Cpath stroke='%23e0947c' d='M13 12h1'/%3E%3Cpath stroke='%23cc4a22' d='M14 12h1m-3 2h1m4 0h1m-6 1h1'/%3E%3Cpath stroke='%23cd4a22' d='M15 12h1m0 1h1m0 2h1m-5 1h1m1 1h1'/%3E%3Cpath stroke='%23cb4922' d='M16 12h1m0 1h1m-5 4h1'/%3E%3Cpath stroke='%23c3411e' d='M19 12h1m-1 1h1m-1 4h1m-8 2h2m3 0h1'/%3E%3Cpath stroke='%23a93618' d='M2 13h1'/%3E%3Cpath stroke='%23dd9987' d='M7 13h1m-2 2h1'/%3E%3Cpath stroke='%23e39f8a' d='M12 13h1'/%3E%3Cpath stroke='%23e59f8b' d='M13 13h1'/%3E%3Cpath stroke='%23e5a08b' d='M14 13h1m-2 1h1'/%3E%3Cpath stroke='%23ce4c23' d='M15 13h1m0 3h1'/%3E%3Cpath stroke='%23882b13' d='M1 14h1'/%3E%3Cpath stroke='%23e6a08b' d='M14 14h1'/%3E%3Cpath stroke='%23e6a18b' d='M15 14h1m-2 1h1'/%3E%3Cpath stroke='%23ce4b23' d='M16 14h1m-4 1h1'/%3E%3Cpath stroke='%238b2c14' d='M1 15h1m-1 1h1'/%3E%3Cpath stroke='%23ac3619' d='M2 15h1'/%3E%3Cpath stroke='%23d76b48' d='M15 15h1'/%3E%3Cpath stroke='%23cf4c23' d='M16 15h1m-2 1h1'/%3E%3Cpath stroke='%23c94721' d='M18 15h1m-3 3h1'/%3E%3Cpath stroke='%23bb3c1b' d='M3 16h1'/%3E%3Cpath stroke='%23bf3e1d' d='M6 16h1'/%3E%3Cpath stroke='%23cb4821' d='M12 16h1'/%3E%3Cpath stroke='%23cd4b23' d='M14 16h1'/%3E%3Cpath stroke='%23cc4922' d='M17 16h1m-4 1h1m1 0h1'/%3E%3Cpath stroke='%238d2d14' d='M1 17h1'/%3E%3Cpath stroke='%23bc3c1b' d='M3 17h1m-1 1h1'/%3E%3Cpath stroke='%23c84520' d='M11 17h1m1 1h1'/%3E%3Cpath stroke='%23ae3719' d='M2 18h1'/%3E%3Cpath stroke='%23c94720' d='M14 18h1'/%3E%3Cpath stroke='%23c95839' d='M19 18h1'/%3E%3Cpath stroke='%23a7bdf0' d='M0 19h1m0 1h1'/%3E%3Cpath stroke='%23ead7d3' d='M1 19h1'/%3E%3Cpath stroke='%23b34e35' d='M2 19h1'/%3E%3Cpath stroke='%23c03e1c' d='M8 19h1'/%3E%3Cpath stroke='%23c9583a' d='M18 19h1'/%3E%3Cpath stroke='%23f3dbd4' d='M19 19h1'/%3E%3Cpath stroke='%23a7bcef' d='M20 19h1m-2 1h1'/%3E%3C/svg%3E")
			}
			
			.status-bar{
				margin: 0 3px;
				box-shadow: inset 0 1px 2px grey;
				padding: 2px 1px;
				gap: 0
			}
			
			.status-bar-field{
				-webkit-font-smoothing: antialiased;
				box-shadow: none;
				padding: 1px 2px;
				border-right: 1px solid rgba(208,206,191,.75);
				border-left: 1px solid hsla(0,0%,100%,.75)
			}
			
			.status-bar-field: first-of-type{
				border-left: none
			}
			
			.status-bar-field: last-of-type{
				border-right: none
			}
			
			button{
				-webkit-font-smoothing: antialiased;
				box-sizing: border-box;
				border: 1px solid #003c74;
				background: linear-gradient(180deg,#fff,#ecebe5 86%,#d8d0c4);
				box-shadow: none;
				border-radius: 3px
			}
			
			button: not(: disabled).active,button: not(: disabled): active{
				box-shadow: none;
				background: linear-gradient(180deg,#cdcac3,#e3e3db 8%,#e5e5de 94%,#f2f2f1)
			}
			
			button: not(: disabled): hover{
				box-shadow: inset -1px 1px #fff0cf,inset 1px 2px #fdd889,inset -2px 2px #fbc761,inset 2px -2px #e5a01a
			}
			
			button.focused,button: focus{
				box-shadow: inset -1px 1px #cee7ff,inset 1px 2px #98b8ea,inset -2px 2px #bcd4f6,inset 1px -1px #89ade4,inset 2px -2px #89ade4
			}
			
			button: :-moz-focus-inner{
				border: 0
			}
			
			input,label,option,select,textarea{
				-webkit-font-smoothing: antialiased
			}
			
			input[type=radio]{
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				margin: 0;
				background: 0;
				position: fixed;
				opacity: 0;
				border: none
			}
			
			input[type=radio]+label{
				line-height: 16px
			}
			
			input[type=radio]+label: before{
				background: linear-gradient(135deg,#dcdcd7,#fff);
				border-radius: 50%;
				border: 1px solid #1d5281
			}
			
			input[type=radio]: not([disabled]): not(: active)+label: hover: before{
				box-shadow: inset -2px -2px #f8b636,inset 2px 2px #fedf9c
			}
			
			input[type=radio]: active+label: before{
				background: linear-gradient(135deg,#b0b0a7,#e3e1d2)
			}
			
			input[type=radio]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23a9dca6' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%234dbf4a' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23a0d29e' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%2355d551' d='M1 1h1'/%3E%3Cpath stroke='%2343c33f' d='M2 1h1'/%3E%3Cpath stroke='%2329a826' d='M3 1h1'/%3E%3Cpath stroke='%239acc98' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%2342c33f' d='M1 2h1'/%3E%3Cpath stroke='%2338b935' d='M2 2h1'/%3E%3Cpath stroke='%2321a121' d='M3 2h1'/%3E%3Cpath stroke='%23269623' d='M4 2h1'/%3E%3Cpath stroke='%232aa827' d='M1 3h1'/%3E%3Cpath stroke='%2322a220' d='M2 3h1'/%3E%3Cpath stroke='%23139210' d='M3 3h1'/%3E%3Cpath stroke='%2398c897' d='M4 3h1'/%3E%3Cpath stroke='%23249624' d='M2 4h1'/%3E%3Cpath stroke='%2398c997' d='M3 4h1'/%3E%3C/svg%3E")
			}
			
			input[type=radio]: focus+label{
				outline: 1px dotted #000
			}
			
			input[type=radio][disabled]+label: before{
				border: 1px solid #cac8bb;
				background: #fff
			}
			
			input[type=radio][disabled]: checked+label: after{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 5 5' shape-rendering='crispEdges'%3E%3Cpath stroke='%23e8e6da' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23d2ceb5' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23e5e3d4' d='M3 0h1M0 3h1'/%3E%3Cpath stroke='%23d7d3bd' d='M1 1h1'/%3E%3Cpath stroke='%23d0ccb2' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%23c7c2a2' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%23e2dfd0' d='M4 1h1M1 4h1'/%3E%3Cpath stroke='%23cdc8ac' d='M2 2h1'/%3E%3Cpath stroke='%23c5bf9f' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%23c3bd9c' d='M4 2h1'/%3E%3Cpath stroke='%23bfb995' d='M3 3h1'/%3E%3Cpath stroke='%23e2dfcf' d='M4 3h1M3 4h1'/%3E%3Cpath stroke='%23c4be9d' d='M2 4h1'/%3E%3C/svg%3E")
			}
			
			input[type=email],input[type=password],textarea: :selection{
				background: #2267cb;
				color: #fff
			}
			
			input[type=range]: :-webkit-slider-thumb{
				height: 21px;
				width: 11px;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
				transform: translateY(-8px)
			}
			
			input[type=range]: :-moz-range-thumb{
				height: 21px;
				width: 11px;
				border: 0;
				border-radius: 0;
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 21' shape-rendering='crispEdges'%3E%3Cpath stroke='%23becbd3' d='M1 0h1M0 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M2 0h1M0 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M3 0h5M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M8 0h1M0 14h1'/%3E%3Cpath stroke='%239fb2be' d='M9 0h1M0 15h1'/%3E%3Cpath stroke='%23a6d1b1' d='M1 1h1'/%3E%3Cpath stroke='%236fd16e' d='M2 1h1M1 2h1'/%3E%3Cpath stroke='%2367ce65' d='M3 1h1M1 3h1'/%3E%3Cpath stroke='%2366ce64' d='M4 1h3'/%3E%3Cpath stroke='%2362cd61' d='M7 1h1'/%3E%3Cpath stroke='%2345c343' d='M8 1h1M7 2h1'/%3E%3Cpath stroke='%2363ac76' d='M9 1h1M2 16h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%23879aa6' d='M10 1h1'/%3E%3Cpath stroke='%2363cd62' d='M2 2h1'/%3E%3Cpath stroke='%2349c547' d='M3 2h1M2 3h1'/%3E%3Cpath stroke='%2347c446' d='M4 2h3'/%3E%3Cpath stroke='%2321b71f' d='M8 2h1'/%3E%3Cpath stroke='%231da41c' d='M9 2h1'/%3E%3Cpath stroke='%237d8e99' d='M10 2h1'/%3E%3Cpath stroke='%2325b923' d='M3 3h1'/%3E%3Cpath stroke='%2321b81f' d='M4 3h4M2 15h1'/%3E%3Cpath stroke='%231ea71c' d='M8 3h1'/%3E%3Cpath stroke='%231b9619' d='M9 3h1'/%3E%3Cpath stroke='%23778892' d='M10 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f7f7f4' d='M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h4m-4 1h3m-2 1h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 4h1M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 4h1M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f1f1ed' d='M7 13h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 13h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 13h1'/%3E%3Cpath stroke='%234bc549' d='M1 14h1'/%3E%3Cpath stroke='%23f4f4f1' d='M2 14h1'/%3E%3Cpath stroke='%23e6e6e2' d='M7 14h1m-2 1h1'/%3E%3Cpath stroke='%23cececa' d='M8 14h1'/%3E%3Cpath stroke='%231a9319' d='M9 14h1'/%3E%3Cpath stroke='%23788993' d='M10 14h1'/%3E%3Cpath stroke='%2369b17b' d='M1 15h1'/%3E%3Cpath stroke='%23f2f2ee' d='M3 15h1m0 1h1'/%3E%3Cpath stroke='%23d0d0cc' d='M7 15h1m-2 1h1'/%3E%3Cpath stroke='%231a9118' d='M8 15h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%234c845a' d='M9 15h1'/%3E%3Cpath stroke='%2372838d' d='M10 15h1'/%3E%3Cpath stroke='%2391a6b2' d='M1 16h1m0 1h1m0 1h1m0 1h1'/%3E%3Cpath stroke='%2321b61f' d='M3 16h1m0 1h1'/%3E%3Cpath stroke='%23e7e7e3' d='M5 16h1'/%3E%3Cpath stroke='%234b8259' d='M8 16h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%236e7e88' d='M9 16h1m-2 1h1m-2 1h1m-2 1h1'/%3E%3Cpath stroke='%23d7d7d4' d='M5 17h1'/%3E%3Cpath stroke='%231da21b' d='M5 18h1'/%3E%3Cpath stroke='%23589868' d='M5 19h1'/%3E%3Cpath stroke='%2380929e' d='M5 20h1'/%3E%3C/svg%3E");
				transform: translateY(2px)
			}
			
			input[type=range]: :-webkit-slider-runnable-track{
				width: 100%;
				height: 2px;
				box-sizing: border-box;
				background: #ecebe4;
				border-right: 1px solid #f3f2ea;
				border-bottom: 1px solid #f3f2ea;
				border-radius: 2px;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
			}
			
			input[type=range]: :-moz-range-track{
				width: 100%;
				height: 2px;
				box-sizing: border-box;
				background: #ecebe4;
				border-right: 1px solid #f3f2ea;
				border-bottom: 1px solid #f3f2ea;
				border-radius: 2px;
				box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #9d9c99,-1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,-1px 1px 0 #fff,1px -1px #9d9c99
			}
			
			input[type=range].has-box-indicator: :-webkit-slider-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(-10px)
			}
			
			input[type=range].has-box-indicator: :-moz-range-thumb{
				background: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 11 22' shape-rendering='crispEdges'%3E%3Cpath stroke='%23f2f1e7' d='M0 0h1m9 0h1M0 21h1m9 0h1'/%3E%3Cpath stroke='%23879aa6' d='M1 0h1m8 20h1'/%3E%3Cpath stroke='%237d8e99' d='M2 0h1m7 19h1'/%3E%3Cpath stroke='%23778892' d='M3 0h5m2 3h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23788993' d='M8 0h1m1 2h1'/%3E%3Cpath stroke='%2372838d' d='M9 0h1m0 1h1'/%3E%3Cpath stroke='%239fb2be' d='M0 1h1m8 20h1'/%3E%3Cpath stroke='%2363af76' d='M1 1h1m7 19h1'/%3E%3Cpath stroke='%231eab1c' d='M2 1h1m6 18h1'/%3E%3Cpath stroke='%231c9d1a' d='M3 1h1'/%3E%3Cpath stroke='%231b9a1a' d='M4 1h3m1 0h1m0 1h1'/%3E%3Cpath stroke='%231b9b1a' d='M7 1h1'/%3E%3Cpath stroke='%234d875b' d='M9 1h1'/%3E%3Cpath stroke='%23afbfc8' d='M0 2h1m7 19h1'/%3E%3Cpath stroke='%2346ca44' d='M1 2h1m5 17h1m0 1h1'/%3E%3Cpath stroke='%2322be20' d='M2 2h1m5 17h1'/%3E%3Cpath stroke='%231faf1d' d='M3 2h1'/%3E%3Cpath stroke='%231fae1d' d='M4 2h3'/%3E%3Cpath stroke='%231fad1d' d='M7 2h1'/%3E%3Cpath stroke='%231da11b' d='M8 2h1'/%3E%3Cpath stroke='%23b5c4cd' d='M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m2 3h5'/%3E%3Cpath stroke='%23f7f7f4' d='M1 3h1M1 4h1M1 5h1M1 6h1M1 7h1M1 8h1M1 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f5f5f2' d='M2 3h1M2 4h1M2 5h1M2 6h1M2 7h1M2 8h1M2 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23f3f3ef' d='M3 3h4M3 4h5M3 5h5M3 6h5M3 7h5M3 8h5M3 9h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5m-5 1h5'/%3E%3Cpath stroke='%23f1f1ed' d='M7 3h1'/%3E%3Cpath stroke='%23dbdbd8' d='M8 3h1'/%3E%3Cpath stroke='%23c4c4c1' d='M9 3h1'/%3E%3Cpath stroke='%23ddddd9' d='M8 4h1M8 18h1'/%3E%3Cpath stroke='%23c6c6c3' d='M9 4h1M9 18h1'/%3E%3Cpath stroke='%23dcdcd9' d='M8 5h1M8 6h1M8 7h1M8 8h1M8 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23c3c3c0' d='M9 5h1M9 6h1M9 7h1M9 8h1M9 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1'/%3E%3Cpath stroke='%23b6c5cd' d='M0 19h1m1 2h1'/%3E%3Cpath stroke='%2370d66f' d='M1 19h1m0 1h1'/%3E%3Cpath stroke='%2364d362' d='M2 19h1'/%3E%3Cpath stroke='%234acb48' d='M3 19h1'/%3E%3Cpath stroke='%2348cb46' d='M4 19h3'/%3E%3Cpath stroke='%23becbd3' d='M0 20h1m0 1h1'/%3E%3Cpath stroke='%23a6d2b1' d='M1 20h1'/%3E%3Cpath stroke='%2367d466' d='M3 20h1'/%3E%3Cpath stroke='%2366d465' d='M4 20h3'/%3E%3Cpath stroke='%2363d362' d='M7 20h1'/%3E%3C/svg%3E");transform: translateY(0)
			}
			
			.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
				border-left: 1px solid #f3f2ea;
				border-right: 0;
				border-bottom: 1px solid #f3f2ea;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
			}
			
			.is-vertical>input[type=range]: :-moz-range-track{
				border-left: 1px solid #f3f2ea;
				border-right: 0;
				border-bottom: 1px solid #f3f2ea;
				box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #9d9c99,1px -1px 0 #9d9c99,0 -1px 0 #9d9c99,1px 1px 0 #fff,-1px -1px #9d9c99
			}
			
			fieldset{
				box-shadow: none;
				background: #fff;
				border: 1px solid #d0d0bf;
				border-radius: 4px;
				padding-top: 10px
			}
			
			legend{
				background: transparent;
				color: #0046d5
			}
			
			.field-row{
				display: flex;
				align-items: center
			}
			
			.field-row>*+*{
				margin-left: 6px
			}
			
			[class^=field-row]+[class^=field-row]{
				margin-top: 6px
			}
			
			.field-row-stacked{
				display: flex;
				flex-direction: column
			}
			
			.field-row-stacked *+*{
				margin-top: 6px
			}
			
			menu[role=tablist] button{
				background: linear-gradient(180deg,#fff,#fafaf9 26%,#f0f0ea 95%,#ecebe5);
				margin-left: -1px;
				margin-right: 2px;
				border-radius: 0;
				border-color: #91a7b4;
				border-top-right-radius: 3px;
				border-top-left-radius: 3px;
				padding: 0 12px 3px
			}
			
			menu[role=tablist] button: hover{
				box-shadow: unset;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]{
				border-color: #919b9c;
				margin-right: -1px;
				border-bottom: 1px solid transparent;
				border-top: 1px solid #e68b2c;
				box-shadow: inset 0 2px #ffc73c
			}
			
			menu[role=tablist] button[aria-selected=true]: first-of-type: before{
				content: "";
				display: block;
				position: absolute;
				z-index: -1;
				top: 100%;
				left: -1px;
				height: 2px;
				width: 0;
				border-left: 1px solid #919b9c
			}
			
			[role=tabpanel]{
				box-shadow: inset 1px 1px #fcfcfe,inset -1px -1px #fcfcfe,1px 2px 2px 0 rgba(208,206,191,.75)
			}
			
			ul.tree-view{
				-webkit-font-smoothing: auto;
				border: 1px solid #7f9db9;
				padding: 2px 5px
			}
			
			@keyframes sliding{
				0%{
					transform: translateX(-30px)
				}
			
				to{
					transform: translateX(100%)
				}
			}
			
			progress{
				box-sizing: border-box;
				appearance: none;
				-webkit-appearance: none;
				-moz-appearance: none;
				height: 14px;
				border: 1px solid #686868;
				border-radius: 4px;
				padding: 1px 2px 1px 0;
				overflow: hidden;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress,progress: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				height: 14px
			}
			
			progress[value]: :-webkit-progress-bar{
				background-color: transparent
			}
			
			progress[value]: :-webkit-progress-value{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress[value]: :-moz-progress-bar{
				border-radius: 2px;
				background: repeating-linear-gradient(90deg,#fff 0,#fff 2px,transparent 0,transparent 10px),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]): :-webkit-progress-bar{
				width: 100%;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff);
				animation: sliding 2s linear 0s infinite
			}
			
			progress: not([value]): :-webkit-progress-bar: not([value]){
				animation: sliding 2s linear 0s infinite;
				background: repeating-linear-gradient(90deg,transparent 0,transparent 8px,#fff 0,#fff 10px,transparent 0,transparent 18px,#fff 0,#fff 20px,transparent 0,transparent 28px,#fff 0,#fff),linear-gradient(180deg,#acedad 0,#7be47d 14%,#4cda50 28%,#2ed330 42%,#42d845 57%,#76e275 71%,#8fe791 85%,#fff)
			}
			
			progress: not([value]){
				position: relative
			}
			
			progress: not([value]): before{
				box-sizing: border-box;
				content: "";
				position: absolute;
				top: 0;
				left: 0;
				width: 100%;
				height: 100%;
				background-color: #fff;
				-webkit-box-shadow: inset 0 0 1px 0 #686868;
				-moz-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before,progress: not([value]): before: not([value]){
				box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): before: not([value]){
				-moz-box-shadow: inset 0 0 1px 0 #686868;
				-webkit-box-shadow: inset 0 0 1px 0 #686868
			}
			
			progress: not([value]): after{
				box-sizing: border-box;
				content: "";
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4406 significance 0.5907575293518603 gamma 0.008680147845298053 max_node_size 2974 max_tree_depth 4393 max_time_stationary 3450",
			        4406,
			        0.5907575293518603,
			        0.008680147845298053,
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			    [
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			        230,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 986 significance 0.31041173600032923 gamma 0.5093849985674024 max_node_size 1461 max_tree_depth 4224 max_time_stationary 3620",
			        986,
			        0.31041173600032923,
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			    [
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			        314,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3256 significance 0.8816417094748468 gamma 0.22139193329773843 max_node_size 3489 max_tree_depth 731 max_time_stationary 1370",
			        3256,
			        0.8816417094748468,
			        0.22139193329773843,
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			    [
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			        365,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4534 significance 0.19990248140506447 gamma 0.9013140374626964 max_node_size 30 max_tree_depth 1343 max_time_stationary 694",
			        4534,
			        0.19990248140506447,
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			    [
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			        177,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 485 significance 0.8731756000891328 gamma 0.8327616627383977 max_node_size 2428 max_tree_depth 4787 max_time_stationary 4933",
			        485,
			        0.8731756000891328,
			        0.8327616627383977,
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			    [
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			        111,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 204 significance 0.13920288311876355 gamma 0.45237312735617163 max_node_size 652 max_tree_depth 1118 max_time_stationary 4024",
			        204,
			        0.13920288311876355,
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			    [
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			        239,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2736 significance 0.4415563245806843 gamma 0.43657942264154553 max_node_size 2581 max_tree_depth 161 max_time_stationary 74",
			        2736,
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			        0.43657942264154553,
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			    [
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			        187,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 641 significance 0.701076369209215 gamma 0.14517577851749958 max_node_size 466 max_tree_depth 398 max_time_stationary 2732",
			        641,
			        0.701076369209215,
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			    [
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			        267,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3100 significance 0.5537282305583358 gamma 0.7852063008826226 max_node_size 4240 max_tree_depth 3830 max_time_stationary 963",
			        3100,
			        0.5537282305583358,
			        0.7852063008826226,
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			    [
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			        354,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1689 significance 0.053041900254786015 gamma 0.044402859272435306 max_node_size 4056 max_tree_depth 2905 max_time_stationary 2990",
			        1689,
			        0.053041900254786015,
			        0.044402859272435306,
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			    [
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			        409,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3803 significance 0.6398893621359021 gamma 0.6939912160672247 max_node_size 1094 max_tree_depth 2063 max_time_stationary 1999",
			        3803,
			        0.6398893621359021,
			        0.6939912160672247,
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			    [
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			        336,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3518 significance 0.11477782777324319 gamma 0.6173704246245325 max_node_size 4679 max_tree_depth 4557 max_time_stationary 2277",
			        3518,
			        0.11477782777324319,
			        0.6173704246245325,
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			    [
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			        398,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4064 significance 0.37196361186355353 gamma 0.09189808507077396 max_node_size 2089 max_tree_depth 3237 max_time_stationary 1657",
			        4064,
			        0.37196361186355353,
			        0.09189808507077396,
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			        "None",
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			    [
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			        432,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4896 significance 0.811136255953461 gamma 0.2520049238912761 max_node_size 1806 max_tree_depth 2674 max_time_stationary 333",
			        4896,
			        0.811136255953461,
			        0.2520049238912761,
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			    [
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			        1744911936,
			        13,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2037 significance 0.999 gamma 0.001 max_node_size 1 max_tree_depth 4328 max_time_stationary 2124",
			        2037,
			        0.999,
			        0.001,
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			    [
			        1744914183,
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			        65,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 29 significance 0.999 gamma 0.001 max_node_size 4048 max_tree_depth 4655 max_time_stationary 1570",
			        29,
			        0.999,
			        0.001,
			        4048,
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			        50,
			        633.64453125,
			        632.96875,
			        -1,
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			    [
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			        84,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2120 significance 0.001 gamma 0.771300723490473 max_node_size 2181 max_tree_depth 2103 max_time_stationary 3588",
			        2120,
			        0.001,
			        0.771300723490473,
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			    [
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			        58,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 27 significance 0.999 gamma 0.001 max_node_size 2927 max_tree_depth 2871 max_time_stationary 2099",
			        27,
			        0.999,
			        0.001,
			        2927,
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			    [
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			        13,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4563 significance 0.001 gamma 0.4569398697769124 max_node_size 1 max_tree_depth 3426 max_time_stationary 5000",
			        4563,
			        0.001,
			        0.4569398697769124,
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			    [
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			        88,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 59 significance 0.999 gamma 0.38292064438628126 max_node_size 5000 max_tree_depth 5000 max_time_stationary 2763",
			        59,
			        0.999,
			        0.38292064438628126,
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			    [
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			        65,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.999 gamma 0.2985864275500203 max_node_size 3812 max_tree_depth 1 max_time_stationary 2756",
			        1,
			        0.999,
			        0.2985864275500203,
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			    [
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			        79,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 56 significance 0.001 gamma 0.001 max_node_size 2674 max_tree_depth 1 max_time_stationary 2153",
			        56,
			        0.001,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2964 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 2748 max_time_stationary 3063",
			        2964,
			        0.001,
			        0.999,
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			    [
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			        93,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 70 significance 0.001 gamma 0.001 max_node_size 4059 max_tree_depth 5000 max_time_stationary 1",
			        70,
			        0.001,
			        0.001,
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			    [
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			        13,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3637 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 3812 max_time_stationary 1",
			        3637,
			        0.001,
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			    [
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			        26,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1877 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 3745 max_time_stationary 3445",
			        1877,
			        0.001,
			        0.001,
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			    [
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			        571,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1995 significance 0.001 gamma 0.9156452681601369 max_node_size 2424 max_tree_depth 5000 max_time_stationary 3911",
			        1995,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2050 significance 0.001 gamma 0.8012294899270462 max_node_size 2158 max_tree_depth 2779 max_time_stationary 3393",
			        2050,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2006 significance 0.999 gamma 0.7600472533959074 max_node_size 2306 max_tree_depth 1 max_time_stationary 3636",
			        2006,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2034 significance 0.999 gamma 0.8034864277805018 max_node_size 2212 max_tree_depth 921 max_time_stationary 3553",
			        2034,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 74 significance 0.999 gamma 0.5992927917452732 max_node_size 4830 max_tree_depth 3005 max_time_stationary 3244",
			        74,
			        0.999,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2046 significance 0.999 gamma 0.7771316266113567 max_node_size 2202 max_tree_depth 1 max_time_stationary 3492",
			        2046,
			        0.999,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1994 significance 0.001 gamma 0.6939257145613666 max_node_size 2365 max_tree_depth 1616 max_time_stationary 3247",
			        1994,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1989 significance 0.999 gamma 0.7539296709760747 max_node_size 2604 max_tree_depth 1 max_time_stationary 3541",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2019 significance 0.999 gamma 0.999 max_node_size 2176 max_tree_depth 1 max_time_stationary 3908",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 21 significance 0.001 gamma 0.6149316360858328 max_node_size 1026 max_tree_depth 1 max_time_stationary 5000",
			        21,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 60 significance 0.001 gamma 0.001 max_node_size 2909 max_tree_depth 5000 max_time_stationary 3249",
			        60,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4576 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 4454 max_time_stationary 5000",
			        4576,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2038 significance 0.999 gamma 0.999 max_node_size 2097 max_tree_depth 4002 max_time_stationary 4119",
			        2038,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2442 significance 0.001 gamma 0.001 max_node_size 4664 max_tree_depth 5000 max_time_stationary 4014",
			        2442,
			        0.001,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1993 significance 0.999 gamma 0.999 max_node_size 2178 max_tree_depth 102 max_time_stationary 3721",
			        1993,
			        0.999,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2057 significance 0.999 gamma 0.999 max_node_size 2071 max_tree_depth 1769 max_time_stationary 3664",
			        2057,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 76 significance 0.999 gamma 0.001 max_node_size 4705 max_tree_depth 1 max_time_stationary 1",
			        76,
			        0.999,
			        0.001,
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			    [
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			        431,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1978 significance 0.999 gamma 0.001 max_node_size 4135 max_tree_depth 3754 max_time_stationary 5000",
			        1978,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4992 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 5000 max_time_stationary 3929",
			        4992,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2007 significance 0.999 gamma 0.6435293819644944 max_node_size 2124 max_tree_depth 5000 max_time_stationary 3581",
			        2007,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2148 significance 0.001 gamma 0.999 max_node_size 2113 max_tree_depth 4394 max_time_stationary 4142",
			        2148,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2025 significance 0.999 gamma 0.999 max_node_size 2127 max_tree_depth 4597 max_time_stationary 2930",
			        2025,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 75 significance 0.999 gamma 0.001 max_node_size 4499 max_tree_depth 5000 max_time_stationary 2171",
			        75,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 64 significance 0.999 gamma 0.7436817892313229 max_node_size 4403 max_tree_depth 5000 max_time_stationary 5000",
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1981 significance 0.999 gamma 0.999 max_node_size 2178 max_tree_depth 5000 max_time_stationary 4684",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4056 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.001 max_node_size 2014 max_tree_depth 2352 max_time_stationary 5000",
			        1,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1973 significance 0.999 gamma 0.999 max_node_size 1820 max_tree_depth 1 max_time_stationary 3690",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 47 significance 0.999 gamma 0.999 max_node_size 1673 max_tree_depth 1 max_time_stationary 3697",
			        47,
			        0.999,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 59 significance 0.999 gamma 0.001 max_node_size 2328 max_tree_depth 881 max_time_stationary 2004",
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			        0.999,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 69 significance 0.999 gamma 0.001 max_node_size 5000 max_tree_depth 5000 max_time_stationary 1",
			        69,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 67 significance 0.999 gamma 0.001 max_node_size 4168 max_tree_depth 1 max_time_stationary 1",
			        67,
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			        0.001,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 110 significance 0.999 gamma 0.001 max_node_size 1914 max_tree_depth 4317 max_time_stationary 3896",
			        110,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2032 significance 0.999 gamma 0.4895613386657353 max_node_size 2197 max_tree_depth 4317 max_time_stationary 3364",
			        2032,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.001 max_node_size 961 max_tree_depth 746 max_time_stationary 1",
			        1,
			        0.001,
			        0.001,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1988 significance 0.999 gamma 0.4020274863716802 max_node_size 2294 max_tree_depth 5000 max_time_stationary 3284",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2002 significance 0.001 gamma 0.999 max_node_size 2092 max_tree_depth 2733 max_time_stationary 1",
			        2002,
			        0.001,
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			        489,
			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1976 significance 0.001 gamma 0.999 max_node_size 1857 max_tree_depth 5000 max_time_stationary 4125",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1971 significance 0.999 gamma 0.999 max_node_size 4312 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1978 significance 0.999 gamma 0.001 max_node_size 2222 max_tree_depth 1954 max_time_stationary 2540",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 69 significance 0.999 gamma 0.001 max_node_size 4379 max_tree_depth 2116 max_time_stationary 3610",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4199 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 1438 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 54 significance 0.999 gamma 0.4469387568863352 max_node_size 1924 max_tree_depth 4883 max_time_stationary 3154",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 56 significance 0.001 gamma 0.5781428312752409 max_node_size 1832 max_tree_depth 460 max_time_stationary 3164",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 49 significance 0.001 gamma 0.6306296480339937 max_node_size 1860 max_tree_depth 5000 max_time_stationary 3718",
			        49,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 380 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 2062 max_time_stationary 1787",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2120 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 1 max_time_stationary 2454",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 43 significance 0.999 gamma 0.5344961474893015 max_node_size 802 max_tree_depth 4522 max_time_stationary 2714",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3939 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 1 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2061 significance 0.001 gamma 0.999 max_node_size 2284 max_tree_depth 4746 max_time_stationary 3812",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 440 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 1842 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 57 significance 0.999 gamma 0.28441200972061875 max_node_size 4548 max_tree_depth 1 max_time_stationary 4979",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1059 significance 0.999 gamma 0.001 max_node_size 1 max_tree_depth 4049 max_time_stationary 2151",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1977 significance 0.001 gamma 0.999 max_node_size 2013 max_tree_depth 1 max_time_stationary 3738",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3683 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 1857 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1892 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 834 max_time_stationary 3580",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 355 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 1969 max_time_stationary 1964",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 44 significance 0.001 gamma 0.999 max_node_size 1713 max_tree_depth 5000 max_time_stationary 3943",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2141 significance 0.999 gamma 0.999 max_node_size 2597 max_tree_depth 2242 max_time_stationary 4950",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2134 significance 0.999 gamma 0.999 max_node_size 2469 max_tree_depth 4827 max_time_stationary 3701",
			        2134,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 46 significance 0.999 gamma 0.001 max_node_size 4763 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2115 significance 0.001 gamma 0.999 max_node_size 5000 max_tree_depth 885 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.999 gamma 0.001 max_node_size 987 max_tree_depth 1 max_time_stationary 2380",
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1498 significance 0.999 gamma 0.999 max_node_size 5000 max_tree_depth 1340 max_time_stationary 5000",
			        1498,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 293 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 1741 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 187 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 77 max_time_stationary 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1998 significance 0.001 gamma 0.999 max_node_size 2111 max_tree_depth 5000 max_time_stationary 1667",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 965 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 3720 max_time_stationary 3499",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3242 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 4601 max_time_stationary 341",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 63 significance 0.999 gamma 0.001 max_node_size 4133 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2141 significance 0.001 gamma 0.001 max_node_size 5000 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2355 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 3359 max_time_stationary 4259",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 105 significance 0.001 gamma 0.001 max_node_size 1689 max_tree_depth 289 max_time_stationary 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.999 gamma 0.42528055528693287 max_node_size 1 max_tree_depth 4761 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1417 significance 0.001 gamma 0.001 max_node_size 5000 max_tree_depth 4961 max_time_stationary 177",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 59 significance 0.001 gamma 0.001 max_node_size 1785 max_tree_depth 1 max_time_stationary 1108",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.001 max_node_size 1115 max_tree_depth 1 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 55 significance 0.001 gamma 0.001 max_node_size 1987 max_tree_depth 311 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1086 significance 0.999 gamma 0.001 max_node_size 3772 max_tree_depth 1833 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1058 significance 0.999 gamma 0.001 max_node_size 4605 max_tree_depth 4333 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.001 max_node_size 2995 max_tree_depth 5000 max_time_stationary 2212",
			        1,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2050 significance 0.001 gamma 0.999 max_node_size 2437 max_tree_depth 1 max_time_stationary 4307",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4870 significance 0.001 gamma 0.001 max_node_size 1 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2096 significance 0.999 gamma 0.001 max_node_size 1299 max_tree_depth 1478 max_time_stationary 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.999 max_node_size 5000 max_tree_depth 1022 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 142 significance 0.999 gamma 0.999 max_node_size 5000 max_tree_depth 2074 max_time_stationary 5000",
			        142,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2039 significance 0.999 gamma 0.999 max_node_size 2666 max_tree_depth 3576 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2030 significance 0.001 gamma 0.999 max_node_size 2623 max_tree_depth 5000 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2056 significance 0.001 gamma 0.999 max_node_size 2584 max_tree_depth 4575 max_time_stationary 5000",
			        2056,
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			        0.999,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2834 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 47 max_time_stationary 2085",
			        2834,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2055 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 5000 max_time_stationary 2659",
			        2055,
			        0.999,
			        0.999,
			        1,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 144 significance 0.999 gamma 0.001 max_node_size 3781 max_tree_depth 1 max_time_stationary 1",
			        144,
			        0.999,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3180 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 5000 max_time_stationary 5000",
			        3180,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2067 significance 0.001 gamma 0.999 max_node_size 2517 max_tree_depth 5000 max_time_stationary 5000",
			        2067,
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			        0.999,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3581 significance 0.001 gamma 0.999 max_node_size 1 max_tree_depth 1 max_time_stationary 2871",
			        3581,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2138 significance 0.001 gamma 0.001 max_node_size 2486 max_tree_depth 3226 max_time_stationary 408",
			        2138,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3008 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 284 max_time_stationary 1",
			        3008,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 120 significance 0.999 gamma 0.999 max_node_size 2457 max_tree_depth 1593 max_time_stationary 5000",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2083 significance 0.001 gamma 0.999 max_node_size 2490 max_tree_depth 4918 max_time_stationary 4960",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.001 max_node_size 4012 max_tree_depth 176 max_time_stationary 2326",
			        1,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.999 gamma 0.001 max_node_size 3222 max_tree_depth 385 max_time_stationary 5000",
			        1,
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 159 significance 0.999 gamma 0.001 max_node_size 5000 max_tree_depth 4897 max_time_stationary 4642",
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 3533 significance 0.999 gamma 0.001 max_node_size 1 max_tree_depth 962 max_time_stationary 1",
			        3533,
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 2120 significance 0.001 gamma 0.001 max_node_size 1364 max_tree_depth 4664 max_time_stationary 1",
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 4405 significance 0.999 gamma 0.999 max_node_size 1 max_tree_depth 1 max_time_stationary 5000",
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			    [
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			        "module load GCCcore\/10.3.0 Python && source \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/venv\/bin\/activate && python \/data\/horse\/ws\/s4122485-compPerfDD\/benchmark\/dfki\/benchmarkdd\/main.py 1 1 0 OutdoorObjects 2000 HoeffdingTreeClassifier CDLEEDS recent_samples_size 1 significance 0.001 gamma 0.41903605040363523 max_node_size 594 max_tree_depth 3469 max_time_stationary 5000",
			        1,
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			    [
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			    [
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			        20,
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			    [
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			        20,
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			    ],
			    [
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			        20,
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			    [
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			    [
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			        20,
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			    [
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			        20,
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			    ],
			    [
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			        20,
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			    ],
			    [
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			        20,
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			    ],
			    [
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			        20,
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			    ],
			    [
			        1745351152.1725647,
			        20,
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			    ],
			    [
			        1745351152.370006,
			        20,
			        1,
			        5
			    ]
			];
			var tab_main_worker_cpu_ram_csv_json = [
			    [
			        1744908680,
			        642.28515625,
			        17.1
			    ],
			    [
			        1744908680,
			        642.2890625,
			        13.7
			    ],
			    [
			        1744908680,
			        642.2890625,
			        14.5
			    ],
			    [
			        1744908680,
			        642.2890625,
			        15.3
			    ],
			    [
			        1744908680,
			        642.2890625,
			        14.3
			    ],
			    [
			        1744908680,
			        642.2890625,
			        15.1
			    ],
			    [
			        1744908680,
			        642.2890625,
			        13.3
			    ],
			    [
			        1744909399,
			        705.0234375,
			        23.2
			    ],
			    [
			        1744909399,
			        705.0234375,
			        19.2
			    ],
			    [
			        1744909399,
			        705.0234375,
			        19.2
			    ],
			    [
			        1744909399,
			        705.0234375,
			        18.4
			    ],
			    [
			        1744929987,
			        934.73828125,
			        35.9
			    ],
			    [
			        1744929987,
			        934.73828125,
			        42.9
			    ],
			    [
			        1744929987,
			        934.73828125,
			        43.1
			    ],
			    [
			        1744929987,
			        934.73828125,
			        32.4
			    ],
			    [
			        1744980842,
			        978.1875,
			        37.9
			    ],
			    [
			        1744980842,
			        978.1875,
			        32.4
			    ],
			    [
			        1744980842,
			        978.1875,
			        31.4
			    ],
			    [
			        1744980842,
			        978.1875,
			        25.8
			    ],
			    [
			        1745049502,
			        1042.08203125,
			        48
			    ],
			    [
			        1745049502,
			        1042.08203125,
			        47
			    ],
			    [
			        1745049503,
			        1042.08203125,
			        45.3
			    ],
			    [
			        1745049503,
			        1042.08203125,
			        44
			    ],
			    [
			        1745119715,
			        979.515625,
			        32.3
			    ],
			    [
			        1745119715,
			        979.515625,
			        14.3
			    ],
			    [
			        1745119715,
			        979.515625,
			        14.3
			    ],
			    [
			        1745119715,
			        979.515625,
			        13.6
			    ],
			    [
			        1745190703,
			        1026.01953125,
			        20.5
			    ],
			    [
			        1745190703,
			        1026.01953125,
			        23.3
			    ],
			    [
			        1745190703,
			        1026.01953125,
			        24.2
			    ],
			    [
			        1745190703,
			        1026.01953125,
			        25
			    ],
			    [
			        1745271700,
			        1070.85546875,
			        28.5
			    ],
			    [
			        1745271700,
			        1070.85546875,
			        4.2
			    ],
			    [
			        1745271700,
			        1070.85546875,
			        4.6
			    ],
			    [
			        1745271700,
			        1070.85546875,
			        5.1
			    ],
			    [
			        1745351159,
			        1109.765625,
			        17.9
			    ],
			    [
			        1745351159,
			        1109.765625,
			        24.7
			    ],
			    [
			        1745351159,
			        1109.765625,
			        24.9
			    ],
			    [
			        1745351159,
			        1109.765625,
			        12.5
			    ]
			];
			var tab_main_worker_cpu_ram_headers_json = [
			    "timestamp",
			    "ram_usage_mb",
			    "cpu_usage_percent"
			];
			
			"use strict";
			
			function add_default_layout_data (layout, no_height = 0) {
				layout["width"] = get_graph_width();
				if (!no_height) {
					layout["height"] = get_graph_height();
				}
				layout["paper_bgcolor"] = 'rgba(0,0,0,0)';
				layout["plot_bgcolor"] = 'rgba(0,0,0,0)';
			
				return layout;
			}
			
			function get_marker_size() {
				return 12;
			}
			
			function get_text_color() {
				return theme == "dark" ? "white" : "black";
			}
			
			function get_font_size() {
				return 14;
			}
			
			function get_graph_height() {
				return 800;
			}
			
			function get_font_data() {
				return {
					size: get_font_size(),
					color: get_text_color()
				}
			}
			
			function get_axis_title_data(name, axis_type = "") {
				if(axis_type) {
					return {
						text: name,
						type: axis_type,
						font: get_font_data()
					};
				}
			
				return {
					text: name,
					font: get_font_data()
				};
			}
			
			function get_graph_width() {
				var width = document.body.clientWidth || window.innerWidth || document.documentElement.clientWidth;
				return Math.max(800, Math.floor(width * 0.9));
			}
			
			function createTable(data, headers, table_name) {
				if (!$("#" + table_name).length) {
					console.error("#" + table_name + " not found");
					return;
				}
			
				new gridjs.Grid({
					columns: headers,
					data: data,
					search: true,
					sort: true,
					ellipsis: false
				}).render(document.getElementById(table_name));
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			
				colorize_table_entries();
			
				add_colorize_to_gridjs_table();
			}
			
			function download_as_file(id, filename) {
				var text = $("#" + id).text();
				var blob = new Blob([text], {
					type: "text/plain"
				});
				var link = document.createElement("a");
				link.href = URL.createObjectURL(blob);
				link.download = filename;
				document.body.appendChild(link);
				link.click();
				document.body.removeChild(link);
			}
			
			function copy_to_clipboard_from_id (id) {
				var text = $("#" + id).text();
			
				copy_to_clipboard(text);
			}
			
			function copy_to_clipboard(text) {
				if (!navigator.clipboard) {
					let textarea = document.createElement("textarea");
					textarea.value = text;
					document.body.appendChild(textarea);
					textarea.select();
					try {
						document.execCommand("copy");
					} catch (err) {
						console.error("Copy failed:", err);
					}
					document.body.removeChild(textarea);
					return;
				}
			
				navigator.clipboard.writeText(text).then(() => {
					console.log("Text copied to clipboard");
				}).catch(err => {
					console.error("Failed to copy text:", err);
				});
			}
			
			function filterNonEmptyRows(data) {
				var new_data = [];
				for (var row_idx = 0; row_idx <  data.length; row_idx++) {
					var line = data[row_idx];
			
					var line_has_empty_data = false;
			
					for (var col_idx = 0; col_idx < line.length; col_idx++) {
						var col_header_name = tab_results_headers_json[col_idx];
						var single_data_point = line[col_idx];
			
						if(single_data_point === "" && !special_col_names.includes(col_header_name)) {
							line_has_empty_data = true;
							continue;
						}
					}
			
					if(!line_has_empty_data) {
						new_data.push(line);
					}
				}
			
				return new_data;
			}
			
			function make_text_in_parallel_plot_nicer() {
				$(".parcoords g > g > text").each(function() {
					if (theme == "dark") {
						$(this)
							.css("text-shadow", "unset")
							.css("font-size", "0.9em")
							.css("fill", "white")
							.css("stroke", "black")
							.css("stroke-width", "2px")
							.css("paint-order", "stroke fill");
					} else {
						$(this)
							.css("text-shadow", "unset")
							.css("font-size", "0.9em")
							.css("fill", "black")
							.css("stroke", "unset")
							.css("stroke-width", "unset")
							.css("paint-order", "stroke fill");
					}
				});
			}
			
			function createParallelPlot(dataArray, headers, resultNames, ignoreColumns = []) {
				if ($("#parallel-plot").data("loaded") == "true") {
					return;
				}
			
				dataArray = filterNonEmptyRows(dataArray);
				const ignoreSet = new Set(ignoreColumns);
				const numericalCols = [];
				const categoricalCols = [];
				const categoryMappings = {};
			
				headers.forEach((header, colIndex) => {
					if (ignoreSet.has(header)) return;
			
					const values = dataArray.map(row => row[colIndex]);
					if (values.every(val => !isNaN(parseFloat(val)))) {
						numericalCols.push({ name: header, index: colIndex });
					} else {
						categoricalCols.push({ name: header, index: colIndex });
						const uniqueValues = [...new Set(values)];
						categoryMappings[header] = Object.fromEntries(uniqueValues.map((val, i) => [val, i]));
					}
				});
			
				const dimensions = [];
			
				numericalCols.forEach(col => {
					dimensions.push({
						label: col.name,
						values: dataArray.map(row => parseFloat(row[col.index])),
						range: [
							Math.min(...dataArray.map(row => parseFloat(row[col.index]))),
							Math.max(...dataArray.map(row => parseFloat(row[col.index])))
						]
					});
				});
			
				categoricalCols.forEach(col => {
					dimensions.push({
						label: col.name,
						values: dataArray.map(row => categoryMappings[col.name][row[col.index]]),
						tickvals: Object.values(categoryMappings[col.name]),
						ticktext: Object.keys(categoryMappings[col.name])
					});
				});
			
				let colorScale = null;
				let colorValues = null;
			
				if (resultNames.length > 1) {
					let selectBox = '<select id="result-select" style="margin-bottom: 10px;">';
					selectBox += '<option value="none">No color</option>';
					var k = 0;
					resultNames.forEach(resultName => {
						var minMax = result_min_max[k];
						if(minMax === undefined) {
							minMax = "min [automatically chosen]"
						}
						selectBox += `<option value="${resultName}">${resultName} (${minMax})</option>`;
						k = k + 1;
					});
					selectBox += '</select>';
					$("#parallel-plot").before(selectBox);
			
					$("#result-select").change(function() {
						const selectedResult = $(this).val();
						if (selectedResult === "none") {
							colorValues = null;
							colorScale = null;
						} else {
							const resultCol = numericalCols.find(col => col.name.toLowerCase() === selectedResult.toLowerCase());
							colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
			
							let minResult = Math.min(...colorValues);
							let maxResult = Math.max(...colorValues);
			
							var _result_min_max_idx = result_names.indexOf(selectedResult);
			
							let invertColor = false;
							if (result_min_max.length > _result_min_max_idx) {
								invertColor = result_min_max[_result_min_max_idx] === "max";
							}
			
							colorScale = invertColor
								? [[0, 'red'], [1, 'green']]
								: [[0, 'green'], [1, 'red']];
						}
						updatePlot();
					});
				} else {
					let invertColor = false;
					if (Object.keys(result_min_max).length == 1) {
						invertColor = result_min_max[0] === "max";
					}
			
					colorScale = invertColor
						? [[0, 'red'], [1, 'green']]
						: [[0, 'green'], [1, 'red']];
			
					const resultCol = numericalCols.find(col => col.name.toLowerCase() === resultNames[0].toLowerCase());
					colorValues = dataArray.map(row => parseFloat(row[resultCol.index]));
				}
			
				function updatePlot() {
					const trace = {
						type: 'parcoords',
						dimensions: dimensions,
						line: colorValues ? { color: colorValues, colorscale: colorScale } : {},
						unselected: {
							line: {
								color: get_text_color(),
								opacity: 0
							}
						},
					};
			
					dimensions.forEach(dim => {
						if (!dim.line) {
							dim.line = {};
						}
						if (!dim.line.color) {
							dim.line.color = 'rgba(169,169,169, 0.01)';
						}
					});
			
					Plotly.newPlot('parallel-plot', [trace], add_default_layout_data({}));
			
					make_text_in_parallel_plot_nicer();
				}
			
				updatePlot();
			
				$("#parallel-plot").data("loaded", "true");
			
				make_text_in_parallel_plot_nicer();
			}
			
			function plotWorkerUsage() {
				if($("#workerUsagePlot").data("loaded") == "true") {
					return;
				}
				var data = tab_worker_usage_csv_json;
				if (!Array.isArray(data) || data.length === 0) {
					console.error("Invalid or empty data provided.");
					return;
				}
			
				let timestamps = [];
				let desiredWorkers = [];
				let realWorkers = [];
			
				for (let i = 0; i < data.length; i++) {
					let entry = data[i];
			
					if (!Array.isArray(entry) || entry.length < 3) {
						console.warn("Skipping invalid entry:", entry);
						continue;
					}
			
					let unixTime = parseFloat(entry[0]);
					let desired = parseInt(entry[1], 10);
					let real = parseInt(entry[2], 10);
			
					if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
						console.warn("Skipping invalid numerical values:", entry);
						continue;
					}
			
					timestamps.push(new Date(unixTime * 1000).toISOString());
					desiredWorkers.push(desired);
					realWorkers.push(real);
				}
			
				let trace1 = {
					x: timestamps,
					y: desiredWorkers,
					mode: 'lines+markers',
					name: 'Desired Workers',
					line: {
						color: 'blue'
					}
				};
			
				let trace2 = {
					x: timestamps,
					y: realWorkers,
					mode: 'lines+markers',
					name: 'Real Workers',
					line: {
						color: 'red'
					}
				};
			
				let layout = {
					title: "Worker Usage Over Time",
					xaxis: {
						title: get_axis_title_data("Time", "date")
					},
					yaxis: {
						title: get_axis_title_data("Number of Workers")
					},
					legend: {
						x: 0,
						y: 1
					}
				};
			
				Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
				$("#workerUsagePlot").data("loaded", "true");
			}
			
			function plotCPUAndRAMUsage() {
				if($("#mainWorkerCPURAM").data("loaded") == "true") {
					return;
				}
				var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
				var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
				var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);
			
				var trace1 = {
					x: timestamps,
					y: cpuUsage,
					mode: 'lines+markers',
					marker: {
						size: get_marker_size(),
					},
					name: 'CPU Usage (%)',
					type: 'scatter',
					yaxis: 'y1'
				};
			
				var trace2 = {
					x: timestamps,
					y: ramUsage,
					mode: 'lines+markers',
					marker: {
						size: get_marker_size(),
					},
					name: 'RAM Usage (MB)',
					type: 'scatter',
					yaxis: 'y2'
				};
			
				var layout = {
					title: 'CPU and RAM Usage Over Time',
					xaxis: {
						title: get_axis_title_data("Timestamp", "date"),
						tickmode: 'array',
						tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
						ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
						tickangle: -45
					},
					yaxis: {
						title: get_axis_title_data("CPU Usage (%)"),
						rangemode: 'tozero'
					},
					yaxis2: {
						title: get_axis_title_data("RAM Usage (MB)"),
						overlaying: 'y',
						side: 'right',
						rangemode: 'tozero'
					},
					legend: {
						x: 0.1,
						y: 0.9
					}
				};
			
				var data = [trace1, trace2];
				Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
				$("#mainWorkerCPURAM").data("loaded", "true");
			}
			
			function plotScatter2d() {
				if ($("#plotScatter2d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter2d");
			
				var minInput = document.getElementById("minValue");
				var maxInput = document.getElementById("maxValue");
			
				if (!minInput || !maxInput) {
					minInput = document.createElement("input");
					minInput.id = "minValue";
					minInput.type = "number";
					minInput.placeholder = "Min Value";
					minInput.step = "any";
			
					maxInput = document.createElement("input");
					maxInput.id = "maxValue";
					maxInput.type = "number";
					maxInput.placeholder = "Max Value";
					maxInput.step = "any";
			
					var inputContainer = document.createElement("div");
					inputContainer.style.marginBottom = "10px";
					inputContainer.appendChild(minInput);
					inputContainer.appendChild(maxInput);
					plotDiv.appendChild(inputContainer);
				}
			
				var resultSelect = document.getElementById("resultSelect");
				if (result_names.length > 1 && !resultSelect) {
					resultSelect = document.createElement("select");
					resultSelect.id = "resultSelect";
					resultSelect.style.marginBottom = "10px";
			
					var sortedResults = [...result_names].sort();
					sortedResults.forEach(result => {
						var option = document.createElement("option");
						option.value = result;
						option.textContent = result;
						resultSelect.appendChild(option);
					});
			
					var selectContainer = document.createElement("div");
					selectContainer.style.marginBottom = "10px";
					selectContainer.appendChild(resultSelect);
					plotDiv.appendChild(selectContainer);
				}
			
				minInput.addEventListener("input", updatePlots);
				maxInput.addEventListener("input", updatePlots);
				if (resultSelect) {
					resultSelect.addEventListener("change", updatePlots);
				}
			
				updatePlots();
			
				async function updatePlots() {
					var minValue = parseFloat(minInput.value);
					var maxValue = parseFloat(maxInput.value);
					if (isNaN(minValue)) minValue = -Infinity;
					if (isNaN(maxValue)) maxValue = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var selectedResult = resultSelect ? resultSelect.value : result_names[0];
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
					if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 2) {
						console.error("Not enough columns for Scatter-Plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							let xCol = numericColumns[i];
							let yCol = numericColumns[j];
			
							let xIndex = tab_results_headers_json.indexOf(xCol);
							let yIndex = tab_results_headers_json.indexOf(yCol);
			
							let data = tab_results_csv_json.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
							}));
			
							data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
							let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
							let layout = {
								title: layoutTitle,
								xaxis: {
									title: get_axis_title_data(xCol)
								},
								yaxis: {
									title: get_axis_title_data(yCol)
								},
								showlegend: false
							};
							let subDiv = document.createElement("div");
			
							let spinnerContainer = document.createElement("div");
							spinnerContainer.style.display = "flex";
							spinnerContainer.style.alignItems = "center";
							spinnerContainer.style.justifyContent = "center";
							spinnerContainer.style.width = layout.width + "px";
							spinnerContainer.style.height = layout.height + "px";
							spinnerContainer.style.position = "relative";
			
							let spinner = document.createElement("div");
							spinner.className = "spinner";
							spinner.style.width = "40px";
							spinner.style.height = "40px";
			
							let loadingText = document.createElement("span");
							loadingText.innerText = `Loading ${layoutTitle}`;
							loadingText.style.marginLeft = "10px";
			
							spinnerContainer.appendChild(spinner);
							spinnerContainer.appendChild(loadingText);
			
							plotDiv.appendChild(spinnerContainer);
			
							await new Promise(resolve => setTimeout(resolve, 50));
			
							let colors = data.map(d => {
								if (d.result === null) {
									return 'rgb(0, 0, 0)';
								} else {
									let norm = (d.result - minResult) / (maxResult - minResult);
									if (invertColor) {
										norm = 1 - norm;
									}
									return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
								}
							});
			
							let trace = {
								x: data.map(d => d.x),
								y: data.map(d => d.y),
								mode: 'markers',
								marker: {
									size: get_marker_size(),
									color: data.map(d => d.result !== null ? d.result : null),
									colorscale: invertColor ? [
										[0, 'red'],
										[1, 'green']
									] : [
										[0, 'green'],
										[1, 'red']
									],
									colorbar: {
										title: 'Result',
										tickvals: [minResult, maxResult],
										ticktext: [`${minResult}`, `${maxResult}`]
									},
									symbol: data.map(d => d.result === null ? 'x' : 'circle'),
								},
								text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
								type: 'scatter',
								showlegend: false
							};
			
							try {
								plotDiv.replaceChild(subDiv, spinnerContainer);
							} catch (err) {
								//
							}
							Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
						}
					}
				}
			
				$("#plotScatter2d").data("loaded", "true");
			}
			
			function plotScatter3d() {
				if ($("#plotScatter3d").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotScatter3d");
				if (!plotDiv) {
					console.error("Div element with id 'plotScatter3d' not found");
					return;
				}
				plotDiv.innerHTML = "";
			
				var minInput3d = document.getElementById("minValue3d");
				var maxInput3d = document.getElementById("maxValue3d");
			
				if (!minInput3d || !maxInput3d) {
					minInput3d = document.createElement("input");
					minInput3d.id = "minValue3d";
					minInput3d.type = "number";
					minInput3d.placeholder = "Min Value";
					minInput3d.step = "any";
			
					maxInput3d = document.createElement("input");
					maxInput3d.id = "maxValue3d";
					maxInput3d.type = "number";
					maxInput3d.placeholder = "Max Value";
					maxInput3d.step = "any";
			
					var inputContainer3d = document.createElement("div");
					inputContainer3d.style.marginBottom = "10px";
					inputContainer3d.appendChild(minInput3d);
					inputContainer3d.appendChild(maxInput3d);
					plotDiv.appendChild(inputContainer3d);
				}
			
				var select3d = document.getElementById("select3dScatter");
				if (result_names.length > 1 && !select3d) {
					if (!select3d) {
						select3d = document.createElement("select");
						select3d.id = "select3dScatter";
						select3d.style.marginBottom = "10px";
						select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");
			
						select3d.addEventListener("change", updatePlots3d);
			
						plotDiv.appendChild(select3d);
					}
				}
			
				minInput3d.addEventListener("input", updatePlots3d);
				maxInput3d.addEventListener("input", updatePlots3d);
			
				updatePlots3d();
			
				async function updatePlots3d() {
					var selectedResult = select3d ? select3d.value : result_names[0];
					var minValue3d = parseFloat(minInput3d.value);
					var maxValue3d = parseFloat(maxInput3d.value);
			
					if (isNaN(minValue3d)) minValue3d = -Infinity;
					if (isNaN(maxValue3d)) maxValue3d = Infinity;
			
					while (plotDiv.children.length > 2) {
						plotDiv.removeChild(plotDiv.lastChild);
					}
			
					var resultIndex = tab_results_headers_json.findIndex(header =>
						header.toLowerCase() === selectedResult.toLowerCase()
					);
					var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
			
					var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
					var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
					if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
					if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);
			
					var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";
			
					var numericColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !result_names.includes(col) &&
						tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
					);
			
					if (numericColumns.length < 3) {
						console.error("Not enough columns for 3D scatter plots");
						return;
					}
			
					for (let i = 0; i < numericColumns.length; i++) {
						for (let j = i + 1; j < numericColumns.length; j++) {
							for (let k = j + 1; k < numericColumns.length; k++) {
								let xCol = numericColumns[i];
								let yCol = numericColumns[j];
								let zCol = numericColumns[k];
			
								let xIndex = tab_results_headers_json.indexOf(xCol);
								let yIndex = tab_results_headers_json.indexOf(yCol);
								let zIndex = tab_results_headers_json.indexOf(zCol);
			
								let data = tab_results_csv_json.map(row => ({
									x: parseFloat(row[xIndex]),
									y: parseFloat(row[yIndex]),
									z: parseFloat(row[zIndex]),
									result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
								}));
			
								data = data.filter(d => d.result >= minResult && d.result <= maxResult);
			
								let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
								let layout = {
									title: layoutTitle,
									scene: {
										xaxis: {
											title: get_axis_title_data(xCol)
										},
										yaxis: {
											title: get_axis_title_data(yCol)
										},
										zaxis: {
											title: get_axis_title_data(zCol)
										}
									},
									showlegend: false
								};
			
								let spinnerContainer = document.createElement("div");
								spinnerContainer.style.display = "flex";
								spinnerContainer.style.alignItems = "center";
								spinnerContainer.style.justifyContent = "center";
								spinnerContainer.style.width = layout.width + "px";
								spinnerContainer.style.height = layout.height + "px";
								spinnerContainer.style.position = "relative";
			
								let spinner = document.createElement("div");
								spinner.className = "spinner";
								spinner.style.width = "40px";
								spinner.style.height = "40px";
			
								let loadingText = document.createElement("span");
								loadingText.innerText = `Loading ${layoutTitle}`;
								loadingText.style.marginLeft = "10px";
			
								spinnerContainer.appendChild(spinner);
								spinnerContainer.appendChild(loadingText);
			
								plotDiv.appendChild(spinnerContainer);
			
								await new Promise(resolve => setTimeout(resolve, 50));
			
								let colors = data.map(d => {
									if (d.result === null) {
										return 'rgb(0, 0, 0)';
									} else {
										let norm = (d.result - minResult) / (maxResult - minResult);
										if (invertColor) {
											norm = 1 - norm;
										}
										return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
									}
								});
			
								let trace = {
									x: data.map(d => d.x),
									y: data.map(d => d.y),
									z: data.map(d => d.z),
									mode: 'markers',
									marker: {
										size: get_marker_size(),
										color: data.map(d => d.result !== null ? d.result : null),
										colorscale: invertColor ? [
											[0, 'red'],
											[1, 'green']
										] : [
											[0, 'green'],
											[1, 'red']
										],
										colorbar: {
											title: 'Result',
											tickvals: [minResult, maxResult],
											ticktext: [`${minResult}`, `${maxResult}`]
										},
									},
									text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
									type: 'scatter3d',
									showlegend: false
								};
			
								let subDiv = document.createElement("div");
								try {
									plotDiv.replaceChild(subDiv, spinnerContainer);
								} catch (err) {
									//
								}
								Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
							}
						}
					}
				}
			
				$("#plotScatter3d").data("loaded", "true");
			}
			
			async function plot_worker_cpu_ram() {
				if($("#worker_cpu_ram_pre").data("loaded") == "true") {
					return;
				}
			
				const logData = $("#worker_cpu_ram_pre").text();
				const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;
			
				const hostData = {};
			
				logData.split("\n").forEach(line => {
					line = line.trim();
					const match = line.match(regex);
					if (match) {
						const timestamp = new Date(parseInt(match[1]) * 1000);
						const hostname = match[2];
						const cpu = parseFloat(match[3]);
						const ram = parseFloat(match[4]);
			
						if (!hostData[hostname]) {
							hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
						}
			
						hostData[hostname].timestamps.push(timestamp);
						hostData[hostname].cpuUsage.push(cpu);
						hostData[hostname].ramUsage.push(ram);
					}
				});
			
				if (!Object.keys(hostData).length) {
					console.log("No valid data found");
					return;
				}
			
				const container = document.getElementById("cpuRamWorkerChartContainer");
				container.innerHTML = "";
			
				var i = 1;
			
				Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
					const chartId = `workerChart_${index}`;
					const chartDiv = document.createElement("div");
					chartDiv.id = chartId;
					chartDiv.style.marginBottom = "40px";
					container.appendChild(chartDiv);
			
					const cpuTrace = {
						x: timestamps,
						y: cpuUsage,
						mode: "lines+markers",
						name: "CPU Usage (%)",
						yaxis: "y1",
						line: {
							color: "red"
						}
					};
			
					const ramTrace = {
						x: timestamps,
						y: ramUsage,
						mode: "lines+markers",
						name: "RAM Usage (MB)",
						yaxis: "y2",
						line: {
							color: "blue"
						}
					};
			
					const layout = {
						title: `Worker CPU and RAM Usage - ${hostname}`,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date")
						},
						yaxis: {
							title: get_axis_title_data("CPU Usage (%)"),
							side: "left",
							color: "red"
						},
						yaxis2: {
							title: get_axis_title_data("RAM Usage (MB)"),
							side: "right",
							overlaying: "y",
							color: "blue"
						},
						showlegend: true
					};
			
					Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
					i++;
				});
			
				$("#plot_worker_cpu_ram_button").remove();
				$("#worker_cpu_ram_pre").data("loaded", "true");
			}
			
			function load_log_file(log_nr, filename) {
				var pre_id = `single_run_${log_nr}_pre`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							if (data.data) {
								$("#" + pre_id).html(data.data);
								$("#" + pre_id).data("loaded", true);
							} else {
								log(`No 'data' key found in response.`);
							}
			
							$("#spinner_log_" + log_nr).remove();
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#spinner_log_" + log_nr).remove();
						});
				}
			}
			
			function load_debug_log () {
				var pre_id = `here_debuglogs_go`;
			
				if (!$("#" + pre_id).data("loaded")) {
					const params = new URLSearchParams(window.location.search);
			
					const user_id = params.get('user_id');
					const experiment_name = params.get('experiment_name');
					const run_nr = params.get('run_nr');
			
					var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;
			
					fetch(url)
						.then(response => response.json())
						.then(data => {
							$("#debug_log_spinner").remove();
			
							if (data.data) {
								try {
									$("#" + pre_id).html(data.data);
								} catch (err) {
									$("#" + pre_id).text(`Error loading data: ${err}`);
								}
			
								$("#" + pre_id).data("loaded", true);
			
								if (typeof apply_theme_based_on_system_preferences === 'function') {
									apply_theme_based_on_system_preferences();
								}
							} else {
								log(`No 'data' key found in response.`);
							}
						})
						.catch(error => {
							log(`Error loading log: ${error}`);
							$("#debug_log_spinner").remove();
						});
				}
			}
			
			function plotBoxplot() {
				if ($("#plotBoxplot").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough numeric columns for Boxplot");
					return;
				}
			
				var resultIndex = tab_results_headers_json.findIndex(function(header) {
					return result_names.includes(header.toLowerCase());
				});
				var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
				var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
				var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));
			
				var plotDiv = document.getElementById("plotBoxplot");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'box',
						name: col,
						boxmean: 'sd',
						marker: {
							color: 'rgb(0, 255, 0)'
						},
					};
				});
			
				let layout = {
					title: 'Boxplot of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Value")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotBoxplot").data("loaded", "true");
			}
			
			function plotHeatmap() {
				if ($("#plotHeatmap").data("loaded") === "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col => {
					if (special_col_names.includes(col) || result_names.includes(col)) {
						return false;
					}
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.every(row => {
						let value = parseFloat(row[index]);
						return !isNaN(value) && isFinite(value);
					});
				});
			
				if (numericColumns.length < 2) {
					console.error("Not enough valid numeric columns for Heatmap");
					return;
				}
			
				var columnData = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					return tab_results_csv_json.map(row => parseFloat(row[index]));
				});
			
				var dataMatrix = numericColumns.map((_, i) =>
					numericColumns.map((_, j) => {
						let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
						return values.reduce((a, b) => a + b, 0) / values.length;
					})
				);
			
				var trace = {
					z: dataMatrix,
					x: numericColumns,
					y: numericColumns,
					colorscale: 'Viridis',
					type: 'heatmap'
				};
			
				var layout = {
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					yaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				var plotDiv = document.getElementById("plotHeatmap");
				plotDiv.innerHTML = "";
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotHeatmap").data("loaded", "true");
			}
			
			function plotHistogram() {
				if ($("#plotHistogram").data("loaded") == "true") {
					return;
				}
			
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Histogram");
					return;
				}
			
				var plotDiv = document.getElementById("plotHistogram");
				plotDiv.innerHTML = "";
			
				const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];
			
				let traces = numericColumns.map((col, index) => {
					let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));
			
					return {
						x: data,
						type: 'histogram',
						name: col,
						opacity: 0.7,
						marker: {
							color: colorPalette[index % colorPalette.length]
						},
						autobinx: true
					};
				});
			
				let layout = {
					title: 'Histogram of Numerical Columns',
					xaxis: {
						title: get_axis_title_data("Value")
					},
					yaxis: {
						title: get_axis_title_data("Frequency")
					},
					showlegend: true,
					barmode: 'overlay'
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotHistogram").data("loaded", "true");
			}
			
			function plotViolin() {
				if ($("#plotViolin").data("loaded") == "true") {
					return;
				}
				var numericColumns = tab_results_headers_json.filter(col =>
					!special_col_names.includes(col) && !result_names.includes(col) &&
					tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
				);
			
				if (numericColumns.length < 1) {
					console.error("Not enough columns for Violin Plot");
					return;
				}
			
				var plotDiv = document.getElementById("plotViolin");
				plotDiv.innerHTML = "";
			
				let traces = numericColumns.map(col => {
					let index = tab_results_headers_json.indexOf(col);
					let data = tab_results_csv_json.map(row => parseFloat(row[index]));
			
					return {
						y: data,
						type: 'violin',
						name: col,
						box: {
							visible: true
						},
						line: {
							color: 'rgb(0, 255, 0)'
						},
						marker: {
							color: 'rgb(0, 255, 0)'
						},
						meanline: {
							visible: true
						},
					};
				});
			
				let layout = {
					title: 'Violin Plot of Numerical Columns',
					yaxis: {
						title: get_axis_title_data("Value")
					},
					xaxis: {
						title: get_axis_title_data("Columns")
					},
					showlegend: false
				};
			
				Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
				$("#plotViolin").data("loaded", "true");
			}
			
			function plotExitCodesPieChart() {
				if ($("#plotExitCodesPieChart").data("loaded") == "true") {
					return;
				}
			
				var exitCodes = tab_job_infos_csv_json.map(row => row[tab_job_infos_headers_json.indexOf("exit_code")]);
			
				var exitCodeCounts = exitCodes.reduce(function(counts, exitCode) {
					counts[exitCode] = (counts[exitCode] || 0) + 1;
					return counts;
				}, {});
			
				var labels = Object.keys(exitCodeCounts);
				var values = Object.values(exitCodeCounts);
			
				var plotDiv = document.getElementById("plotExitCodesPieChart");
				plotDiv.innerHTML = "";
			
				var trace = {
					labels: labels,
					values: values,
					type: 'pie',
					hoverinfo: 'label+percent',
					textinfo: 'label+value',
					marker: {
						colors: ['#ff9999','#66b3ff','#99ff99','#ffcc99','#c2c2f0']
					}
				};
			
				var layout = {
					title: 'Exit Code Distribution',
					showlegend: true
				};
			
				Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
				$("#plotExitCodesPieChart").data("loaded", "true");
			}
			
			function plotResultEvolution() {
				if ($("#plotResultEvolution").data("loaded") == "true") {
					return;
				}
			
				result_names.forEach(resultName => {
					var relevantColumns = tab_results_headers_json.filter(col =>
						!special_col_names.includes(col) && !col.startsWith("OO_Info") && col.toLowerCase() !== resultName.toLowerCase()
					);
			
					var xColumnIndex = tab_results_headers_json.indexOf("trial_index");
					var resultIndex = tab_results_headers_json.indexOf(resultName);
			
					let data = tab_results_csv_json.map(row => ({
						x: row[xColumnIndex],
						y: parseFloat(row[resultIndex])
					}));
			
					data.sort((a, b) => a.x - b.x);
			
					let xData = data.map(item => item.x);
					let yData = data.map(item => item.y);
			
					let trace = {
						x: xData,
						y: yData,
						mode: 'lines+markers',
						name: resultName,
						line: {
							shape: 'linear'
						},
						marker: {
							size: get_marker_size()
						}
					};
			
					let layout = {
						title: `Evolution of ${resultName} over time`,
						xaxis: {
							title: get_axis_title_data("Trial-Index")
						},
						yaxis: {
							title: get_axis_title_data(resultName)
						},
						showlegend: true
					};
			
					let subDiv = document.createElement("div");
					document.getElementById("plotResultEvolution").appendChild(subDiv);
			
					Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
				});
			
				$("#plotResultEvolution").data("loaded", "true");
			}
			
			function plotResultPairs() {
				if ($("#plotResultPairs").data("loaded") == "true") {
					return;
				}
			
				var plotDiv = document.getElementById("plotResultPairs");
				plotDiv.innerHTML = "";
			
				for (let i = 0; i < result_names.length; i++) {
					for (let j = i + 1; j < result_names.length; j++) {
						let xName = result_names[i];
						let yName = result_names[j];
			
						let xIndex = tab_results_headers_json.indexOf(xName);
						let yIndex = tab_results_headers_json.indexOf(yName);
			
						let data = tab_results_csv_json
							.filter(row => row[xIndex] !== "" && row[yIndex] !== "")
							.map(row => ({
								x: parseFloat(row[xIndex]),
								y: parseFloat(row[yIndex]),
								status: row[tab_results_headers_json.indexOf("trial_status")]
							}));
			
						let colors = data.map(d => d.status === "COMPLETED" ? 'green' : (d.status === "FAILED" ? 'red' : 'gray'));
			
						let trace = {
							x: data.map(d => d.x),
							y: data.map(d => d.y),
							mode: 'markers',
							marker: {
								size: get_marker_size(),
								color: colors
							},
							text: data.map(d => `Status: ${d.status}`),
							type: 'scatter',
							showlegend: false
						};
			
						let layout = {
							xaxis: {
								title: get_axis_title_data(xName)
							},
							yaxis: {
								title: get_axis_title_data(yName)
							},
							showlegend: false
						};
			
						let subDiv = document.createElement("div");
						plotDiv.appendChild(subDiv);
			
						Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
					}
				}
			
				$("#plotResultPairs").data("loaded", "true");
			}
			
			function add_up_down_arrows_for_scrolling () {
				const upArrow = document.createElement('div');
				const downArrow = document.createElement('div');
			
				const style = document.createElement('style');
				style.innerHTML = `
					.scroll-arrow {
						position: fixed;
						right: 10px;
						z-index: 100;
						cursor: pointer;
						font-size: 25px;
						display: none;
						background-color: green;
						color: white;
						padding: 5px;
						outline: 2px solid white;
						box-shadow: 0 0 10px rgba(0, 0, 0, 0.5);
						transition: background-color 0.3s, transform 0.3s;
					}
					.scroll-arrow:hover {
						background-color: darkgreen;
						transform: scale(1.1);
					}
					#up-arrow {
						top: 10px;
					}
					#down-arrow {
						bottom: 10px;
					}
				`;
				document.head.appendChild(style);
			
				upArrow.id = "up-arrow";
				upArrow.classList.add("scroll-arrow");
				upArrow.classList.add("invert_in_dark_mode");
				upArrow.innerHTML = "&#8593;";
			
				downArrow.id = "down-arrow";
				downArrow.classList.add("scroll-arrow");
				downArrow.classList.add("invert_in_dark_mode");
				downArrow.innerHTML = "&#8595;";
			
				document.body.appendChild(upArrow);
				document.body.appendChild(downArrow);
			
				function checkScrollPosition() {
					const scrollPosition = window.scrollY;
					const pageHeight = document.documentElement.scrollHeight;
					const windowHeight = window.innerHeight;
			
					if (scrollPosition > 0) {
						upArrow.style.display = "block";
					} else {
						upArrow.style.display = "none";
					}
			
					if (scrollPosition + windowHeight < pageHeight) {
						downArrow.style.display = "block";
					} else {
						downArrow.style.display = "none";
					}
				}
			
				window.addEventListener("scroll", checkScrollPosition);
			
				upArrow.addEventListener("click", function () {
					window.scrollTo({ top: 0, behavior: 'smooth' });
				});
			
				downArrow.addEventListener("click", function () {
					window.scrollTo({ top: document.documentElement.scrollHeight, behavior: 'smooth' });
				});
			
				checkScrollPosition();
			
				if (typeof apply_theme_based_on_system_preferences === 'function') {
					apply_theme_based_on_system_preferences();
				}
			}
			
			function plotGPUUsage() {
				if ($("#tab_gpu_usage").data("loaded") === "true") {
					return;
				}
			
				Object.keys(gpu_usage).forEach(node => {
					const nodeData = gpu_usage[node];
			
					var timestamps = [];
					var gpuUtilizations = [];
					var temperatures = [];
			
					nodeData.forEach(entry => {
						try {
							var timestamp = new Date(entry[0]* 1000);
							var utilization = parseFloat(entry[1]);
							var temperature = parseFloat(entry[2]);
			
							if (!isNaN(timestamp) && !isNaN(utilization) && !isNaN(temperature)) {
								timestamps.push(timestamp);
								gpuUtilizations.push(utilization);
								temperatures.push(temperature);
							} else {
								console.warn("Invalid data point:", entry);
							}
						} catch (error) {
							console.error("Error processing GPU data entry:", error, entry);
						}
					});
			
					var trace1 = {
						x: timestamps,
						y: gpuUtilizations,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Utilization (%)',
						type: 'scatter',
						yaxis: 'y1'
					};
			
					var trace2 = {
						x: timestamps,
						y: temperatures,
						mode: 'lines+markers',
						marker: {
							size: get_marker_size(),
						},
						name: 'GPU Temperature (°C)',
						type: 'scatter',
						yaxis: 'y2'
					};
			
					var layout = {
						title: 'GPU Usage Over Time - ' + node,
						xaxis: {
							title: get_axis_title_data("Timestamp", "date"),
							tickmode: 'array',
							tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
							ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
							tickangle: -45
						},
						yaxis: {
							title: get_axis_title_data("GPU Utilization (%)"),
							overlaying: 'y',
							rangemode: 'tozero'
						},
						yaxis2: {
							title: get_axis_title_data("GPU Temperature (°C)"),
							overlaying: 'y',
							side: 'right',
							position: 0.85,
							rangemode: 'tozero'
						},
						legend: {
							x: 0.1,
							y: 0.9
						}
					};
			
					var divId = 'gpu_usage_plot_' + node;
			
					if (!document.getElementById(divId)) {
						var div = document.createElement('div');
						div.id = divId;
						div.className = 'gpu-usage-plot';
						document.getElementById('tab_gpu_usage').appendChild(div);
					}
			
					var plotData = [trace1, trace2];
			
					Plotly.newPlot(divId, plotData, add_default_layout_data(layout));
				});
			
				$("#tab_gpu_usage").data("loaded", "true");
			}
			
			function plotResultsDistributionByGenerationMethod() {
				if ("true" === $("#plotResultsDistributionByGenerationMethod").data("loaded")) {
					return;
				}
			
				var res_col = result_names[0];
				var gen_method_col = "generation_node";
			
				var data = {};
			
				tab_results_csv_json.forEach(row => {
					var gen_method = row[tab_results_headers_json.indexOf(gen_method_col)];
					var result = row[tab_results_headers_json.indexOf(res_col)];
			
					if (!data[gen_method]) {
						data[gen_method] = [];
					}
					data[gen_method].push(result);
				});
			
				var traces = Object.keys(data).map(method => {
					return {
						y: data[method],
						type: 'box',
						name: method,
						boxpoints: 'outliers',
						jitter: 0.5,
						pointpos: 0
					};
				});
			
				var layout = {
					title: 'Distribution of Results by Generation Method',
					yaxis: {
						title: get_axis_title_data(res_col)
					},
					xaxis: {
						title: get_axis_title_data("Generation Method")
					},
					boxmode: 'group'
				};
			
				Plotly.newPlot("plotResultsDistributionByGenerationMethod", traces, add_default_layout_data(layout));
				$("#plotResultsDistributionByGenerationMethod").data("loaded", "true");
			}
			
			function plotJobStatusDistribution() {
				if ($("#plotJobStatusDistribution").data("loaded") === "true") {
					return;
				}
			
				var status_col = "trial_status";
				var status_counts = {};
			
				tab_results_csv_json.forEach(row => {
					var status = row[tab_results_headers_json.indexOf(status_col)];
					if (status) {
						status_counts[status] = (status_counts[status] || 0) + 1;
					}
				});
			
				var statuses = Object.keys(status_counts);
				var counts = Object.values(status_counts);
			
				var colors = statuses.map((status, i) =>
					status === "FAILED" ? "#FF0000" : `hsl(${30 + ((i * 137) % 330)}, 70%, 50%)`
				);
			
				var trace = {
					x: statuses,
					y: counts,
					type: 'bar',
					marker: { color: colors }
				};
			
				var layout = {
					title: 'Distribution of Job Status',
					xaxis: { title: 'Trial Status' },
					yaxis: { title: 'Nr. of jobs' }
				};
			
				Plotly.newPlot("plotJobStatusDistribution", [trace], add_default_layout_data(layout));
				$("#plotJobStatusDistribution").data("loaded", "true");
			}
			
			function _colorize_table_entries_by_generation_method () {
				document.querySelectorAll('[data-column-id="generation_node"]').forEach(el => {
					let text = el.textContent.toLowerCase();
					let color = text.includes("manual") ? "green" :
						text.includes("sobol") ? "orange" :
						text.includes("saasbo") ? "pink" :
						text.includes("uniform") ? "lightblue" :
						text.includes("legacy_gpei") ? "sienna" :
						text.includes("bo_mixed") ? "aqua" :
						text.includes("randomforest") ? "darkseagreen" :
						text.includes("external_generator") ? "purple" :
						text.includes("botorch") ? "yellow" : "";
					if (color !== "") {
						el.style.backgroundColor = color;
					}
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_trial_status () {
				document.querySelectorAll('[data-column-id="trial_status"]').forEach(el => {
					let color = el.textContent.includes("COMPLETED") ? "lightgreen" :
						el.textContent.includes("RUNNING") ? "orange" :
						el.textContent.includes("FAILED") ? "red" :
						el.textContent.includes("ABANDONED") ? "yellow" : "";
					if (color) el.style.backgroundColor = color;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_run_time() {
				let cells = [...document.querySelectorAll('[data-column-id="run_time"]')];
				if (cells.length === 0) return;
			
				let values = cells.map(el => parseFloat(el.textContent)).filter(v => !isNaN(v));
				if (values.length === 0) return;
			
				let min = Math.min(...values);
				let max = Math.max(...values);
				let range = max - min || 1;
			
				cells.forEach(el => {
					let value = parseFloat(el.textContent);
					if (isNaN(value)) return;
			
					let ratio = (value - min) / range;
					let red = Math.round(255 * ratio);
					let green = Math.round(255 * (1 - ratio));
			
					el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
					el.classList.add("invert_in_dark_mode");
				});
			}
			
			function _colorize_table_entries_by_results() {
				result_names.forEach((name, index) => {
					let minMax = result_min_max[index];
					let selector_query = `[data-column-id="${name}"]`;
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let values = cells.map(el => parseFloat(el.textContent)).filter(v => v > 0 && !isNaN(v));
					if (values.length === 0) return;
			
					let logValues = values.map(v => Math.log(v));
					let logMin = Math.min(...logValues);
					let logMax = Math.max(...logValues);
					let logRange = logMax - logMin || 1;
			
					cells.forEach(el => {
						let value = parseFloat(el.textContent);
						if (isNaN(value) || value <= 0) return;
			
						let logValue = Math.log(value);
						let ratio = (logValue - logMin) / logRange;
						if (minMax === "max") ratio = 1 - ratio;
			
						let red = Math.round(255 * ratio);
						let green = Math.round(255 * (1 - ratio));
			
						el.style.backgroundColor = `rgb(${red}, ${green}, 0)`;
						el.classList.add("invert_in_dark_mode");
					});
				});
			}
			
			function _colorize_table_entries_by_generation_node_or_hostname() {
				["hostname", "generation_node"].forEach(element => {
					let selector_query = '[data-column-id="' + element + '"]:not(.gridjs-th)';
					let cells = [...document.querySelectorAll(selector_query)];
					if (cells.length === 0) return;
			
					let uniqueValues = [...new Set(cells.map(el => el.textContent.trim()))];
					let colorMap = {};
			
					uniqueValues.forEach((value, index) => {
						let hue = Math.round((360 / uniqueValues.length) * index);
						colorMap[value] = `hsl(${hue}, 70%, 60%)`;
					});
			
					cells.forEach(el => {
						let value = el.textContent.trim();
						if (colorMap[value]) {
							el.style.backgroundColor = colorMap[value];
							el.classList.add("invert_in_dark_mode");
						}
					});
				});
			}
			
			function colorize_table_entries () {
				setTimeout(() => {
					if (typeof result_names !== "undefined" && Array.isArray(result_names) && result_names.length > 0) {
						_colorize_table_entries_by_trial_status();
						_colorize_table_entries_by_results();
						_colorize_table_entries_by_run_time();
						_colorize_table_entries_by_generation_method();
						_colorize_table_entries_by_generation_node_or_hostname();
						if (typeof apply_theme_based_on_system_preferences === 'function') {
							apply_theme_based_on_system_preferences();
						}
					}
				}, 300);
			}
			
			function add_colorize_to_gridjs_table () {
				let searchInput = document.querySelector(".gridjs-search-input");
				if (searchInput) {
					searchInput.addEventListener("input", colorize_table_entries);
				}
			}
			
			function updatePreWidths() {
				var width = window.innerWidth * 0.95;
				var pres = document.getElementsByTagName('pre');
				for (var i = 0; i < pres.length; i++) {
					pres[i].style.width = width + 'px';
				}
			}
			
			function demo_mode(nr_sec = 3) {
				let i = 0;
				let tabs = $('menu[role="tablist"] > button');
			
				setInterval(() => {
					tabs.attr('aria-selected', 'false').removeClass('active');
			
					let tab = tabs.eq(i % tabs.length);
					tab.attr('aria-selected', 'true').addClass('active');
			
					tab.trigger('click');
			
					i++;
				}, nr_sec * 1000);
			}
			
			function resizePlotlyCharts() {
				const plotlyElements = document.querySelectorAll('.js-plotly-plot');
			
				if (plotlyElements.length) {
					const windowWidth = window.innerWidth;
					const windowHeight = window.innerHeight;
			
					const newWidth = windowWidth * 0.9;
					const newHeight = windowHeight * 0.9;
			
					plotlyElements.forEach(function(element, index) {
						const layout = {
							width: newWidth,
							height: newHeight,
							plot_bgcolor: 'rgba(0, 0, 0, 0)',
							paper_bgcolor: 'rgba(0, 0, 0, 0)',
						};
			
						Plotly.relayout(element, layout)
					});
				}
			
				make_text_in_parallel_plot_nicer();
				apply_theme_based_on_system_preferences();
			}
			
			window.addEventListener('load', updatePreWidths);
			window.addEventListener('resize', updatePreWidths);
			
			$(document).ready(function() {
				colorize_table_entries();
			
				add_up_down_arrows_for_scrolling();
			
				add_colorize_to_gridjs_table();
			});
			
			window.addEventListener('resize', function() {
				resizePlotlyCharts();
			});
			
			"use strict";
			
			function get_row_by_index(idx) {
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
			
				var trial_index_col_idx = tab_results_headers_json.indexOf("trial_index");
			
				if(trial_index_col_idx == -1) {
					error(`"trial_index" could not be found in tab_results_headers_json. Cannot continue`);
			
					return null;
				}
			
				for (var i = 0; i < tab_results_csv_json.length; i++) {
					var row = tab_results_csv_json[i];
					var trial_index = row[trial_index_col_idx];
			
					if (trial_index == idx) {
						return row;
					}
				}
			
				return null;
			}
			
			function load_pareto_graph_from_idxs () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				if(pareto_idxs === null) {
					var err_msg = "pareto_idxs is null. Cannot plot or create tables from empty data. This can be caused by a defective <tt>pareto_idxs.json</tt> file. Please try reloading, or re-calculating the pareto-front and re-submitting if this problem persists.";
					$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
					return;	
				}
			
				var table = get_pareto_table_data_from_idx();
			
				var html_tables = createParetoTablesFromData(table);
			
				$("#pareto_from_idxs_table").html(html_tables);
			
				renderParetoFrontPlots(table);
			
				apply_theme_based_on_system_preferences();
			}
			
			function renderParetoFrontPlots(data) {
				try {
					let container = document.getElementById("pareto_front_idxs_plot_container");
					if (!container) {
						console.error("DIV with id 'pareto_front_idxs_plot_container' not found.");
						return;
					}
			
					container.innerHTML = "";
			
					if(data === undefined || data === null) {
						var err_msg = "There was an error getting the data for Pareto-Fronts. See the developer's console to see further details.";
						$("#pareto_from_idxs_table").html(`<div class="caveat alarm">${err_msg}</div>`);
						return;
					}
			
					Object.keys(data).forEach((key, idx) => {
						if (!key.startsWith("Pareto front for ")) return;
			
						let label = key.replace("Pareto front for ", "");
						let [xKey, yKey] = label.split("/");
			
						if (!xKey || !yKey) {
							console.warn("Could not extract two objectives from key:", key);
							return;
						}
			
						let entries = data[key];
						let x = [];
						let y = [];
						let hoverTexts = [];
			
						entries.forEach((entry) => {
							let results = entry.results || {};
							let values = entry.values || {};
			
							let xVal = (results[xKey] || [])[0];
							let yVal = (results[yKey] || [])[0];
			
							if (xVal === undefined || yVal === undefined) {
								console.warn("Missing values for", xKey, yKey, "in", entry);
								return;
							}
			
							x.push(xVal);
							y.push(yVal);
			
							let hoverInfo = [];
			
							if ("trial_index" in values) {
								hoverInfo.push(`<b>Trial Index:</b> ${values.trial_index[0]}`);
							}
			
							Object.keys(values)
								.filter(k => k !== "trial_index")
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${values[k][0]}`);
								});
			
							Object.keys(results)
								.sort()
								.forEach(k => {
									hoverInfo.push(`<b>${k}:</b> ${results[k][0]}`);
								});
			
							hoverTexts.push(hoverInfo.join("<br>"));
						});
			
						let wrapper = document.createElement("div");
						wrapper.style.marginBottom = "30px";
			
						let titleEl = document.createElement("h3");
						titleEl.textContent = `Pareto Front: ${xKey} (${getMinMaxByResultName(xKey)}) vs ${yKey} (${getMinMaxByResultName(yKey)})`;
						wrapper.appendChild(titleEl);
			
						let divId = `pareto_plot_${idx}`;
						let plotDiv = document.createElement("div");
						plotDiv.id = divId;
						plotDiv.style.width = "100%";
						plotDiv.style.height = "400px";
			
						wrapper.appendChild(plotDiv);
						container.appendChild(wrapper);
			
						let trace = {
							x: x,
							y: y,
							text: hoverTexts,
							hoverinfo: "text",
							mode: "markers",
							type: "scatter",
							marker: {
								size: 8,
								color: 'rgb(31, 119, 180)',
								line: {
									width: 1,
									color: 'black'
								}
							},
							name: label
						};
			
						let layout = {
							xaxis: { title: { text: xKey } },
							yaxis: { title: { text: yKey } },
							margin: { t: 10, l: 60, r: 20, b: 50 },
							hovermode: "closest",
							showlegend: false
						};
			
						Plotly.newPlot(divId, [trace], add_default_layout_data(layout, 1));
					});
				} catch (e) {
					console.error("Error while rendering Pareto front plots:", e);
				}
			}
			
			function createParetoTablesFromData(data) {
				try {
					var container = document.createElement("div");
			
					var parsedData;
					try {
						parsedData = typeof data === "string" ? JSON.parse(data) : data;
					} catch (e) {
						console.error("JSON parsing failed:", e);
						return container;
					}
			
					for (var sectionTitle in parsedData) {
						if (!parsedData.hasOwnProperty(sectionTitle)) {
							continue;
						}
			
						var sectionData = parsedData[sectionTitle];
						var heading = document.createElement("h2");
						heading.textContent = sectionTitle;
						container.appendChild(heading);
			
						var table = document.createElement("table");
						table.style.borderCollapse = "collapse";
						table.style.marginBottom = "2em";
						table.style.width = "100%";
			
						var thead = document.createElement("thead");
						var headerRow = document.createElement("tr");
			
						var allValueKeys = new Set();
						var allResultKeys = new Set();
			
						sectionData.forEach(entry => {
							var values = entry.values || {};
							var results = entry.results || {};
			
							Object.keys(values).forEach(key => {
								allValueKeys.add(key);
							});
			
							Object.keys(results).forEach(key => {
								allResultKeys.add(key);
							});
						});
			
						var sortedValueKeys = Array.from(allValueKeys).sort();
						var sortedResultKeys = Array.from(allResultKeys).sort();
			
						if (sortedValueKeys.includes("trial_index")) {
							sortedValueKeys = sortedValueKeys.filter(k => k !== "trial_index");
							sortedValueKeys.unshift("trial_index");
						}
			
						var allColumns = [...sortedValueKeys, ...sortedResultKeys];
			
						allColumns.forEach(col => {
							var th = document.createElement("th");
							th.textContent = col;
							th.style.border = "1px solid black";
							th.style.padding = "4px";
							headerRow.appendChild(th);
						});
			
						thead.appendChild(headerRow);
						table.appendChild(thead);
			
						var tbody = document.createElement("tbody");
			
						sectionData.forEach(entry => {
							var tr = document.createElement("tr");
			
							allColumns.forEach(col => {
								var td = document.createElement("td");
								td.style.border = "1px solid black";
								td.style.padding = "4px";
			
								var value = null;
			
								if (col in entry.values) {
									value = entry.values[col];
								} else if (col in entry.results) {
									value = entry.results[col];
								}
			
								if (Array.isArray(value)) {
									td.textContent = value.join(", ");
								} else {
									td.textContent = value !== null && value !== undefined ? value : "";
								}
			
								tr.appendChild(td);
							});
			
							tbody.appendChild(tr);
						});
			
						table.appendChild(tbody);
						container.appendChild(table);
					}
			
					return container;
				} catch (err) {
					console.error("Unexpected error:", err);
					var errorDiv = document.createElement("div");
					errorDiv.textContent = "Error generating tables.";
					return errorDiv;
				}
			}
			
			function get_pareto_table_data_from_idx () {
				if (!Object.keys(window).includes("pareto_idxs")) {
					error("pareto_idxs is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_csv_json")) {
					error("tab_results_csv_json is not defined");
					return;
				}
			
				if (!Object.keys(window).includes("tab_results_headers_json")) {
					error("tab_results_headers_json is not defined");
					return;
				}
			
				var x_keys = Object.keys(pareto_idxs);
			
				var tables = {};
			
				for (var i = 0; i < x_keys.length; i++) {
					var x_key = x_keys[i];
					var y_keys = Object.keys(pareto_idxs[x_key]);
			
					for (var j = 0; j < y_keys.length; j++) {
						var y_key = y_keys[j];
			
						var indices = pareto_idxs[x_key][y_key];
			
						for (var k = 0; k < indices.length; k++) {
							var idx = indices[k];
							var row = get_row_by_index(idx);
			
							if(row === null) {
								error(`Error getting the row for index ${idx}`);
								return;
							}
			
							var row_dict = {
								"results": {},
								"values": {},
							};
			
							for (var l = 0; l < tab_results_headers_json.length; l++) {
								var header = tab_results_headers_json[l];
			
								if (!special_col_names.includes(header) || header == "trial_index") {
									var val = row[l];
			
									if (result_names.includes(header)) {
										if (!Object.keys(row_dict["results"]).includes(header)) {
											row_dict["results"][header] = [];
										}
			
										row_dict["results"][header].push(val);
									} else {
										if (!Object.keys(row_dict["values"]).includes(header)) {
											row_dict["values"][header] = [];
										}
										row_dict["values"][header].push(val);
									}
								}
								
							}
			
							var table_key = `Pareto front for ${x_key}/${y_key}`;
			
							if(!Object.keys(tables).includes(table_key)) {
								tables[table_key] = [];
							}
			
							tables[table_key].push(row_dict);
						}
			
					}
				}
			
				return tables;
			}
			
			function getMinMaxByResultName(resultName) {
				try {
					if (typeof resultName !== "string") {
						error("Parameter resultName must be a string");
						return;
					}
			
					if (!Array.isArray(result_names)) {
						error("Global variable result_names is not an array or undefined");
						return;
					}
					if (!Array.isArray(result_min_max)) {
						error("Global variable result_min_max is not an array or undefined");
						return;
					}
			
					if (result_names.length !== result_min_max.length) {
						error("Global arrays result_names and result_min_max must have the same length");
						return;
					}
			
					var index = result_names.indexOf(resultName);
					if (index === -1) {
						error("Result name '" + resultName + "' not found in result_names");
						return;
					}
			
					var minMaxValue = result_min_max[index];
			
					if (minMaxValue !== "min" && minMaxValue !== "max") {
						error("Value for result name '" + resultName + "' is invalid: expected 'min' or 'max'");
						return;
					}
			
					return minMaxValue;
			
				} catch (e) {
					error("Unexpected error: " + e.message);
				}
			}
			

			$(document).ready(function() {
				colorize_table_entries();;
				plotWorkerUsage();;
				plotCPUAndRAMUsage();;
				createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names);;
				plotScatter2d();;
				plotScatter3d();
				plotJobStatusDistribution();;
				plotBoxplot();;
				plotViolin();;
				plotHistogram();;
				plotHeatmap();;
				plotResultPairs();;
				plotResultEvolution();

				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>1000  </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>500   </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> significance</td><td>float</td><td>0.001</td><td>0.999</td><td>float</td><td>No         </td></tr><tr><td> gamma</td><td>float</td><td>0.001</td><td>0.999</td><td>float</td><td>No         </td></tr><tr><td> max_node_size</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr><tr><td> max_tree_depth</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr><tr><td> max_time_stationary</td><td>int</td><td>1</td><td>5000</td><td>int</td><td>No         </td></tr></tbody></table><h2>Number of evaluations</h2>
			<table>
			<tbody>
			<tr>
			<th>Failed</th>
			<th>Succeeded</th>
			<th>Running</th>
			<th>Total</th>
			</tr>
			<tr>
			<td>2</td>
			<td>658</td>
			<td>1</td>
			<td>661</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,significance,gamma,max_node_size,max_tree_depth,max_time_stationary
0,0_0,COMPLETED,Sobol,GenerationStep_0,0.560000000000000053290705182008,383.000000000000000000000000000000,3705,0.382970793128013631267947403103,0.132435032725334161929353626874,675,3948,552
1,1_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,79.000000000000000000000000000000,212,0.686101888617500654810044125043,0.700632570682093502867360257369,2801,798,4078
2,2_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,51.000000000000000000000000000000,2058,0.109031318141147498534948567794,0.274144770946353699692110694741,2050,1304,2577
3,3_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,380.000000000000000000000000000000,4340,0.835051510892808490638117291383,0.830656039118766731377263567992,3850,3126,1545
4,4_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,366.000000000000000000000000000000,4960,0.214945914911106233935456089057,0.542063118070364002853978036001,4759,3047,909
5,5_0,COMPLETED,Sobol,GenerationStep_0,0.560000000000000053290705182008,332.000000000000000000000000000000,1456,0.970349102105945382490403972042,0.094742452736943955082793422662,1842,2368,4424
6,6_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,205.000000000000000000000000000000,803,0.299906355280429137710740405964,0.926580100683495389013444309967,3631,375,3464
7,7_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,177.000000000000000000000000000000,3095,0.511386128583922960899599274853,0.498745436364784855420850817609,395,4726,2455
8,8_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,162.000000000000000000000000000000,2705,0.051516235465183857211712847857,0.958500651787966506667260091490,1404,1043,1682
9,9_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,242.000000000000000000000000000000,1194,0.760016331616789053704508205556,0.403962511792778977692819353251,4575,4213,3026
10,10_0,COMPLETED,Sobol,GenerationStep_0,0.560000000000000053290705182008,351.000000000000000000000000000000,1847,0.463823577355593430482372241386,0.571067048082128159158799007855,267,3706,3943
11,11_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,401.000000000000000000000000000000,4568,0.722206441702321177977808019932,0.004825505567714572299764519414,3131,1865,101
12,12_0,COMPLETED,Sobol,GenerationStep_0,0.560000000000000053290705182008,346.000000000000000000000000000000,3950,0.359397782064974302684845497424,0.370869296414777616099911483616,2949,1964,1966
13,13_0,COMPLETED,Sobol,GenerationStep_0,0.530000000000000026645352591004,123.000000000000000000000000000000,2449,0.584438301382586344878689033067,0.796793887117877575043678461952,1155,2624,3289
14,14_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,149.000000000000000000000000000000,601,0.132117723470553755094059056319,0.224278351590037339224892320999,4308,4617,4910
15,15_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,279.000000000000000000000000000000,3314,0.936228507265448595120460595354,0.669702268045395565643218560581,2215,285,1087
16,16_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,277.000000000000000000000000000000,3221,0.173596299543976789747645739226,0.411858104731887553207059227134,3456,3354,3228
17,17_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,101.000000000000000000000000000000,382,0.882079236006364175715077635687,0.981975357592105857484909847699,567,1434,2066
18,18_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,78.000000000000000000000000000000,2190,0.336399843661114583692750557020,0.058589068615809085371903819350,4895,693,1153
19,19_0,COMPLETED,Sobol,GenerationStep_0,0.560000000000000053290705182008,344.000000000000000000000000000000,3896,0.594765544600784790141290159227,0.609221272228285704031236491574,1709,3785,4805
20,20_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,370.000000000000000000000000000000,4466,0.481965126665309051556818076278,0.757771112410351665999996839673,1910,4889,2960
21,21_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,324.000000000000000000000000000000,1636,0.706988542061299130025986414694,0.316268598550930646329248929760,3988,479,1787
22,22_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,182.000000000000000000000000000000,945,0.005181266579777001925199986232,0.647065648823976546921699082304,854,2238,162
23,23_0,COMPLETED,Sobol,GenerationStep_0,0.530000000000000026645352591004,162.000000000000000000000000000000,2642,0.809274950170889462164325323101,0.217250357445329417283019779461,2624,2820,3843
24,24_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,192.000000000000000000000000000000,2875,0.255551301488652848892257907210,0.738924685785546930816281019361,4175,1658,4670
25,25_0,COMPLETED,Sobol,GenerationStep_0,0.540000000000000035527136788005,176.000000000000000000000000000000,710,0.558665307927876719773507829814,0.186304356230422851758987690118,2351,3558,702
26,26_0,COMPLETED,Sobol,GenerationStep_0,0.550000000000000044408920985006,280.000000000000000000000000000000,1403,0.231108025010675205423993361364,0.854510384690016500108811214886,3121,4298,2204
27,27_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,323.000000000000000000000000000000,4701,0.957111117558553825546141524683,0.282391681149601947442562277502,980,1226,3676
28,28_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,325.000000000000000000000000000000,4131,0.088013766996562478595045320162,0.087578233227133747695880572337,90,102,4330
29,29_0,COMPLETED,Sobol,GenerationStep_0,0.570000000000000062172489379009,362.000000000000000000000000000000,1955,0.843399794502183830502417549724,0.519319071870297244153391602595,3310,4531,339
30,30_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,44.000000000000000000000000000000,2017,0.001000000000000000020816681712,0.692911757709346209921363879403,655,1,1
31,31_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,414.000000000000000000000000000000,1999,0.001000000000000000020816681712,0.001000000000000000020816681712,1624,1706,4443
32,32_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,44.000000000000000000000000000000,2003,0.001000000000000000020816681712,0.998999999999999999111821580300,2201,1,5000
33,33_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2038,0.001000000000000000020816681712,0.001000000000000000020816681712,1,2305,1
34,34_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,356.000000000000000000000000000000,1975,0.001000000000000000020816681712,0.001000000000000000020816681712,1923,1,1
35,35_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2051,0.001000000000000000020816681712,0.998999999999999999111821580300,1,4098,1
36,36_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,354.000000000000000000000000000000,1955,0.001000000000000000020816681712,0.001000000000000000020816681712,3434,1,5000
37,37_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2065,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,5000
38,38_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,341.000000000000000000000000000000,4790,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,1,5000
39,39_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,48.000000000000000000000000000000,2016,0.001000000000000000020816681712,0.998999999999999999111821580300,2203,5000,5000
40,40_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,311.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.001000000000000000020816681712,272,1,4970
41,41_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,345.000000000000000000000000000000,4997,0.998999999999999999111821580300,0.998999999999999999111821580300,342,1,1
42,42_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2049,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,5000
43,43_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2049,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,5000
44,44_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,306.000000000000000000000000000000,4774,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,5000,5000
45,45_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,86.000000000000000000000000000000,2003,0.001000000000000000020816681712,0.998999999999999999111821580300,1663,1,1
46,46_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2044,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,1
47,47_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2054,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,5000
48,48_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2060,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,1
49,49_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,709.000000000000000000000000000000,1966,0.001000000000000000020816681712,0.998999999999999999111821580300,3215,918,1
50,50_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4336,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,5000
51,51_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,357.000000000000000000000000000000,1986,0.001000000000000000020816681712,0.001000000000000000020816681712,2199,5000,5000
52,52_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,351.000000000000000000000000000000,4930,0.998999999999999999111821580300,0.001000000000000000020816681712,2321,5000,5000
53,53_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,363.000000000000000000000000000000,1987,0.474707219752674158819161220890,0.001000000000000000020816681712,1221,1,5000
54,54_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4198,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,1
55,55_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,691.000000000000000000000000000000,4836,0.998999999999999999111821580300,0.998999999999999999111821580300,2331,5000,1
56,56_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,365.000000000000000000000000000000,4828,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,5000,5000
57,57_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2092,0.001000000000000000020816681712,0.998999999999999999111821580300,1,2579,1
58,58_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2048,0.998999999999999999111821580300,0.873429617158550830602337100572,1,1,1
59,59_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2034,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,1
60,60_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,333.000000000000000000000000000000,1859,0.001000000000000000020816681712,0.960232758938263097903131892963,2007,2374,4005
61,61_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,477.000000000000000000000000000000,1870,0.241034694654261971713538059703,0.777499975091470174604069143243,710,328,2423
62,62_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3886,0.001000000000000000020816681712,0.935909173831703911083934599446,1,3635,993
63,63_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,271.000000000000000000000000000000,1751,0.630110006702171543402357656305,0.923653517418937308747217684868,321,2446,1209
64,64_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,284.000000000000000000000000000000,1882,0.001000000000000000020816681712,0.998999999999999999111821580300,1988,3705,1550
65,65_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,396.000000000000000000000000000000,1891,0.998999999999999999111821580300,0.366091342007472564379355617348,2087,2617,426
66,66_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,367.000000000000000000000000000000,1856,0.998999999999999999111821580300,0.880920828557453905460761234281,760,3406,2972
67,67_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,372.000000000000000000000000000000,1867,0.001000000000000000020816681712,0.896766320976646769125295577396,2039,2234,180
68,68_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2729,0.998999999999999999111821580300,0.944716508527014275919952979166,1,1646,4290
69,69_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,283.000000000000000000000000000000,1836,0.001000000000000000020816681712,0.807209571401033665338786704524,474,1748,1358
70,70_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,339.000000000000000000000000000000,1886,0.998999999999999999111821580300,0.998999999999999999111821580300,949,4357,4688
71,71_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,355.000000000000000000000000000000,1946,0.998999999999999999111821580300,0.704947362398735233313118442311,990,2471,2545
72,72_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,358.000000000000000000000000000000,1802,0.001000000000000000020816681712,0.365320099518264440607850929155,1786,532,98
73,73_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,374.000000000000000000000000000000,4009,0.126981423685632366371578427788,0.654018381434046558453587749682,624,104,2804
74,74_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3689,0.001000000000000000020816681712,0.998999999999999999111821580300,1,473,2265
75,75_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,284.000000000000000000000000000000,3909,0.057880418489914362001336201047,0.836066083980355312377241716604,205,4222,4611
76,76_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,342.000000000000000000000000000000,1834,0.998999999999999999111821580300,0.910286690391369224251150171767,1817,3307,4837
77,77_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3343,0.998999999999999999111821580300,0.961630753946818739308355361572,1,513,4551
78,78_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,327.000000000000000000000000000000,3891,0.395827350490321361320411597262,0.767689484095943730501687696233,342,1150,3438
79,79_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,364.000000000000000000000000000000,1894,0.998999999999999999111821580300,0.434313210095596424764607945690,2099,4837,762
80,80_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,340.000000000000000000000000000000,1856,0.998999999999999999111821580300,0.649210022123204333333035265241,1193,801,537
81,81_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,314.000000000000000000000000000000,1711,0.001000000000000000020816681712,0.798313361480939898129349785449,1944,489,2449
82,82_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,396.000000000000000000000000000000,1835,0.001000000000000000020816681712,0.520678531876462402649963223666,2201,2131,2532
83,83_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,397.000000000000000000000000000000,4876,0.001000000000000000020816681712,0.569049599085594492997586257843,635,3325,1605
84,84_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,342.000000000000000000000000000000,1898,0.001000000000000000020816681712,0.429366039492749984596287049499,1044,1483,1888
85,85_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,331.000000000000000000000000000000,1804,0.827330434444273121741275645036,0.289385293496746687225140703958,1516,2194,485
86,86_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,368.000000000000000000000000000000,4640,0.589133190250918703512184038118,0.301240105898542886997404366412,2005,575,1283
87,87_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,373.000000000000000000000000000000,1913,0.998999999999999999111821580300,0.544060250012813106934572715545,1047,438,3168
88,88_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,351.000000000000000000000000000000,1904,0.998999999999999999111821580300,0.816601795973848965104480157606,2232,693,13
89,89_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,328.000000000000000000000000000000,1795,0.001000000000000000020816681712,0.330159329354095865127760589530,1072,582,1045
90,90_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,256.000000000000000000000000000000,3998,0.958423366887511285483469691826,0.170328061498515426208655298979,6,4273,251
91,91_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,50.000000000000000000000000000000,2021,0.001000000000000000020816681712,0.998999999999999999111821580300,2304,1149,4629
92,92_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,364.000000000000000000000000000000,4838,0.727482481573468620084099711676,0.129513279983914847415249482765,2037,875,3171
93,93_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4923,0.998999999999999999111821580300,0.998999999999999999111821580300,1,2296,3524
94,94_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,353.000000000000000000000000000000,4919,0.470492339754779331784106943815,0.006743966166250957121330866784,2066,1299,2681
95,95_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,351.000000000000000000000000000000,4807,0.998999999999999999111821580300,0.927626520754051608896872949117,1283,2923,3526
96,96_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,287.000000000000000000000000000000,4973,0.998999999999999999111821580300,0.928122157075243148227627898450,85,2225,6
97,97_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,42.000000000000000000000000000000,2003,0.100758611788448360080394650140,0.275879898246137456041537916462,2024,4935,3241
98,98_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,301.000000000000000000000000000000,4944,0.998999999999999999111821580300,0.001000000000000000020816681712,102,1925,1
99,99_0,COMPLETED,BoTorch,GenerationStep_1,0.600000000000000088817841970013,44.000000000000000000000000000000,2012,0.998999999999999999111821580300,0.728319890528892011083428315033,2668,3614,3327
100,100_0,COMPLETED,BoTorch,GenerationStep_1,0.589999999999999968913755310496,47.000000000000000000000000000000,2005,0.001000000000000000020816681712,0.998999999999999999111821580300,1611,4020,1494
101,101_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,375.000000000000000000000000000000,4750,0.998999999999999999111821580300,0.779118520552432913817142434709,2907,2855,4916
102,102_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,327.000000000000000000000000000000,4873,0.998999999999999999111821580300,0.998678196359896630518449001102,98,4402,1993
103,103_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,545.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.998999999999999999111821580300,661,2302,1
104,104_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,44.000000000000000000000000000000,2008,0.704718102659969036771769879124,0.489874176773472336243742120132,2739,2345,4803
105,105_0,COMPLETED,BoTorch,GenerationStep_1,0.589999999999999968913755310496,45.000000000000000000000000000000,2016,0.967648761247734023882571818831,0.998999999999999999111821580300,2806,1,3544
106,106_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,354.000000000000000000000000000000,4565,0.998999999999999999111821580300,0.823150704272085476098652634391,2840,3641,2510
107,107_0,COMPLETED,BoTorch,GenerationStep_1,0.600000000000000088817841970013,43.000000000000000000000000000000,2014,0.001000000000000000020816681712,0.995194979983472061135785224906,2832,3260,5000
108,108_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,366.000000000000000000000000000000,4167,0.001000000000000000020816681712,0.250125658266315886724129313734,2028,288,3676
109,109_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,472.000000000000000000000000000000,4731,0.998999999999999999111821580300,0.409066184251732356536024326488,2844,4865,5000
110,110_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,469.000000000000000000000000000000,4649,0.576445684487263854123284545494,0.641100518489048143422337489028,2676,3962,4759
111,111_0,COMPLETED,BoTorch,GenerationStep_1,0.600000000000000088817841970013,51.000000000000000000000000000000,2015,0.998999999999999999111821580300,0.853603560777899672551427556755,3001,1753,4445
112,112_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,369.000000000000000000000000000000,4887,0.998999999999999999111821580300,0.737594056622523086552689619566,1304,1036,3820
113,113_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,347.000000000000000000000000000000,4562,0.998999999999999999111821580300,0.998999999999999999111821580300,2348,1115,5000
114,114_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,48.000000000000000000000000000000,2024,0.998999999999999999111821580300,0.960765657675824336081404908327,2667,4956,4423
115,115_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,277.000000000000000000000000000000,4944,0.998999999999999999111821580300,0.317860559873782810846876145661,37,2273,2
116,116_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.063752349017532378150363570057,1,3553,1186
117,117_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,277.000000000000000000000000000000,4866,0.001000000000000000020816681712,0.718053674869599256602725745324,115,742,683
118,118_0,COMPLETED,BoTorch,GenerationStep_1,0.600000000000000088817841970013,45.000000000000000000000000000000,2015,0.701580228897493829443021695624,0.625391836556756564036163581477,2561,2783,3823
119,119_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,47.000000000000000000000000000000,2008,0.001000000000000000020816681712,0.998999999999999999111821580300,2410,3021,4215
120,120_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,322.000000000000000000000000000000,1753,0.525154722930391781865466782619,0.859800221001184583613508038979,2894,2722,4147
121,121_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,317.000000000000000000000000000000,1811,0.001000000000000000020816681712,0.718770723485686935383398576960,2676,2862,3790
122,122_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,352.000000000000000000000000000000,1960,0.998999999999999999111821580300,0.884964461101389043840015347087,2885,3006,5000
123,123_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,392.000000000000000000000000000000,1971,0.001000000000000000020816681712,0.923852470681538751051675717463,2927,3516,3643
124,124_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,346.000000000000000000000000000000,1522,0.694418434928178007758958756312,0.826901161242258653238934584806,2769,2680,4450
125,125_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,344.000000000000000000000000000000,1860,0.998999999999999999111821580300,0.798769525568640892387861640600,2501,3823,2127
126,126_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1709,0.279043936225404187734255856412,0.451371387162806059212272202785,1,2850,2449
127,127_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,324.000000000000000000000000000000,1780,0.001000000000000000020816681712,0.764974356301475921782184741460,2778,1977,3578
128,128_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,374.000000000000000000000000000000,1936,0.001000000000000000020816681712,0.757226165132794282186523560085,2540,3606,1854
129,129_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,283.000000000000000000000000000000,1503,0.034956373916400558521377917032,0.835593047769520369527640468732,2934,68,4576
130,130_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,318.000000000000000000000000000000,1580,0.001000000000000000020816681712,0.747554324327758701329571522365,2557,1326,5000
131,131_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,334.000000000000000000000000000000,1997,0.001000000000000000020816681712,0.905308472772552441654170252150,2890,1141,1234
132,132_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,346.000000000000000000000000000000,1896,0.665813223793772168690452417650,0.679947482684014725684562563401,2590,4556,38
133,133_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,296.000000000000000000000000000000,1449,0.998999999999999999111821580300,0.719107970904854898464009238523,2880,1422,4736
134,134_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4885,0.998999999999999999111821580300,0.461596331825629424550072599231,1,1844,4991
135,135_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,364.000000000000000000000000000000,1887,0.998999999999999999111821580300,0.777198253245094949903659653501,2920,2362,3311
136,136_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,93.000000000000000000000000000000,2202,0.001000000000000000020816681712,0.947248882255567803412077410030,3056,403,5000
137,137_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2423,0.001000000000000000020816681712,0.426849028644849970426378149568,1,2011,2182
138,138_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,292.000000000000000000000000000000,1359,0.001000000000000000020816681712,0.827865321396365483330725965061,2720,74,3552
139,139_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,325.000000000000000000000000000000,1572,0.998999999999999999111821580300,0.822167244986347300894635736768,2484,118,5000
140,140_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,67.000000000000000000000000000000,2119,0.001000000000000000020816681712,0.842164544240072809877517556743,2900,1936,3113
141,141_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,373.000000000000000000000000000000,1885,0.998999999999999999111821580300,0.889486410362608892476998789789,2913,3804,1109
142,142_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,58.000000000000000000000000000000,2076,0.001000000000000000020816681712,0.932169012676693164998198426474,2936,4017,5000
143,143_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,97.000000000000000000000000000000,2287,0.998999999999999999111821580300,0.849595803082760614444168822956,2449,4227,5000
144,144_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,286.000000000000000000000000000000,1435,0.001000000000000000020816681712,0.720188863238402587896302975423,2623,239,3378
145,145_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,285.000000000000000000000000000000,1387,0.998999999999999999111821580300,0.718974083341940684022119967267,2557,2111,436
146,146_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1073,0.390997333803147772979258434134,0.387270856596462598187002868144,1,1458,1
147,147_0,COMPLETED,BoTorch,GenerationStep_1,0.530000000000000026645352591004,122.000000000000000000000000000000,2427,0.001000000000000000020816681712,0.841810715117773389337685330247,2769,4914,3289
148,148_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,328.000000000000000000000000000000,1768,0.001000000000000000020816681712,0.758180268126265155537168993760,2460,3700,1477
149,149_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,258.000000000000000000000000000000,1621,0.453116179068624502779272233965,0.416432817870202698351533854293,78,690,486
150,150_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,59.000000000000000000000000000000,2084,0.998999999999999999111821580300,0.773477884664006243298217668780,2248,2422,3723
151,151_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,58.000000000000000000000000000000,2097,0.568374591987174992979703347373,0.842810001561160149208262737375,1704,4742,3144
152,152_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,54.000000000000000000000000000000,2059,0.998999999999999999111821580300,0.936738535328643928679070995713,2333,1954,3383
153,153_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,60.000000000000000000000000000000,2091,0.998999999999999999111821580300,0.688893582192391273899545467430,2608,1382,5000
154,154_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,61.000000000000000000000000000000,2092,0.998999999999999999111821580300,0.605924025818648237518004862068,2346,5000,2604
155,155_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,61.000000000000000000000000000000,2092,0.998999999999999999111821580300,0.902914272450691113292009504221,2089,1,4458
156,156_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,65.000000000000000000000000000000,2120,0.998999999999999999111821580300,0.180649747836218621532822226072,2955,4622,2925
157,157_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,62.000000000000000000000000000000,2110,0.998999999999999999111821580300,0.710900329046333823157510778401,1605,4365,1667
158,158_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,62.000000000000000000000000000000,2103,0.001000000000000000020816681712,0.673465917102637590119229571428,898,3018,1672
159,159_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,63.000000000000000000000000000000,2105,0.998999999999999999111821580300,0.570478677678977641463120562548,2037,4539,3844
160,160_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,61.000000000000000000000000000000,2095,0.998999999999999999111821580300,0.998999999999999999111821580300,1919,5000,2964
161,161_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,63.000000000000000000000000000000,2121,0.998999999999999999111821580300,0.178935922673695013696004707526,3398,5000,4083
162,162_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,60.000000000000000000000000000000,2091,0.092045286910429152671397901031,0.998999999999999999111821580300,1494,1,3232
163,163_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,62.000000000000000000000000000000,2096,0.998999999999999999111821580300,0.643070491990727188813536940870,2636,1,3567
164,164_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,66.000000000000000000000000000000,2125,0.901651403253457495168277091580,0.530150241150713519289183750516,514,4692,2980
165,165_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,68.000000000000000000000000000000,2140,0.804983553774702542682462080847,0.998999999999999999111821580300,1535,1,1842
166,166_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,54.000000000000000000000000000000,2057,0.998999999999999999111821580300,0.750478410468840895219955200446,2469,5000,3786
167,167_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,66.000000000000000000000000000000,2132,0.998999999999999999111821580300,0.998999999999999999111821580300,1102,3405,2877
168,168_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,70.000000000000000000000000000000,2143,0.998999999999999999111821580300,0.587383414668467218611169755604,1595,3060,4622
169,169_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3518,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1771,4428
170,170_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,61.000000000000000000000000000000,2106,0.998999999999999999111821580300,0.446353332044307049564224598726,3245,992,5000
171,171_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,58.000000000000000000000000000000,2095,0.267756346338854533950524228203,0.776893067763986922003027757455,1930,187,4263
172,172_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,67.000000000000000000000000000000,2129,0.998999999999999999111821580300,0.362302708143186213973763187823,1052,2453,2276
173,173_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,64.000000000000000000000000000000,2114,0.998999999999999999111821580300,0.540173766933357502040280451183,2457,5000,4815
174,174_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,64.000000000000000000000000000000,2134,0.998999999999999999111821580300,0.511332876998525920342331119173,4166,304,5000
175,175_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,59.000000000000000000000000000000,2090,0.998999999999999999111821580300,0.415914518717082792864658813414,2642,5000,3571
176,176_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,55.000000000000000000000000000000,2069,0.998999999999999999111821580300,0.998999999999999999111821580300,2437,1,4589
177,177_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,65.000000000000000000000000000000,2112,0.998999999999999999111821580300,0.998999999999999999111821580300,2327,1,5000
178,178_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,56.000000000000000000000000000000,2045,0.998999999999999999111821580300,0.998999999999999999111821580300,2411,2072,3014
179,179_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,72.000000000000000000000000000000,2158,0.998999999999999999111821580300,0.058821936054239909452689971658,2134,402,4670
180,180_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,50.000000000000000000000000000000,2048,0.349572444443037033678933767078,0.937408323616530037014626941527,2340,4875,3608
181,181_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,64.000000000000000000000000000000,2059,0.001000000000000000020816681712,0.998999999999999999111821580300,2089,5000,2572
182,182_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4495,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1372,5000
183,183_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,403.000000000000000000000000000000,1997,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,5000,5000
184,184_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,399.000000000000000000000000000000,1993,0.655423251321376798550488729234,0.998999999999999999111821580300,2882,5000,5000
185,185_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4398,0.607931544657917877216846136434,0.641823346094240743120451497816,1,5000,2384
186,186_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3832,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,1
187,187_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4449,0.998999999999999999111821580300,0.001000000000000000020816681712,1,3399,5000
188,188_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4562,0.001000000000000000020816681712,0.001000000000000000020816681712,1,230,1
189,189_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,45.000000000000000000000000000000,2022,0.998999999999999999111821580300,0.155668994026962520527135325210,5000,5000,4846
190,190_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2267,0.001000000000000000020816681712,0.215470413154577294934099995771,1,320,10
191,191_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2277,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,3701
192,192_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,460.000000000000000000000000000000,4180,0.001000000000000000020816681712,0.001000000000000000020816681712,4361,1164,5000
193,193_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,45.000000000000000000000000000000,2003,0.998999999999999999111821580300,0.001000000000000000020816681712,4375,4735,5000
194,194_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,327.000000000000000000000000000000,4249,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,1256,1
195,195_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4936,0.483646169106755841049505306728,0.998999999999999999111821580300,1,1,5000
196,196_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,376.000000000000000000000000000000,4443,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,1543,5000
197,197_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,334.000000000000000000000000000000,4510,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,5000,5000
198,198_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2867,0.998999999999999999111821580300,0.998999999999999999111821580300,1,3846,4907
199,199_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,365.000000000000000000000000000000,4175,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,3401,4956
200,200_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4059,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1396,1
201,201_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,399.000000000000000000000000000000,4547,0.001000000000000000020816681712,0.998999999999999999111821580300,209,4656,1
202,202_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,52.000000000000000000000000000000,2026,0.411240593816145305616771565838,0.998999999999999999111821580300,2342,798,3697
203,203_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,379.000000000000000000000000000000,4225,0.998999999999999999111821580300,0.001000000000000000020816681712,388,1,12
204,204_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2271,0.001000000000000000020816681712,0.998999999999999999111821580300,1,4351,2459
205,205_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,300.000000000000000000000000000000,4580,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,2685,4524
206,206_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,314.000000000000000000000000000000,3701,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,5000,4056
207,207_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,361.000000000000000000000000000000,2000,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,2675,289
208,208_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2826,0.998999999999999999111821580300,0.263149376052362993227973220201,1,4790,1268
209,209_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,410.000000000000000000000000000000,4295,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,2718,5000
210,210_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,263.000000000000000000000000000000,3575,0.001000000000000000020816681712,0.998999999999999999111821580300,1936,5000,5000
211,211_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,723.000000000000000000000000000000,4198,0.001000000000000000020816681712,0.998999999999999999111821580300,1801,5000,1
212,212_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,100.000000000000000000000000000000,2323,0.001000000000000000020816681712,0.266399385567726576518055026099,1557,5000,2191
213,213_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,160.000000000000000000000000000000,2898,0.001000000000000000020816681712,0.998999999999999999111821580300,1983,5000,5000
214,214_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,374.000000000000000000000000000000,3951,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,5000,5000
215,215_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,665.000000000000000000000000000000,3616,0.001000000000000000020816681712,0.998999999999999999111821580300,2122,5000,1
216,216_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,275.000000000000000000000000000000,3505,0.001000000000000000020816681712,0.998999999999999999111821580300,1746,1,5000
217,217_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,515.000000000000000000000000000000,3500,0.001000000000000000020816681712,0.998999999999999999111821580300,1222,5000,1
218,218_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,571.000000000000000000000000000000,2942,0.001000000000000000020816681712,0.998999999999999999111821580300,1927,5000,1
219,219_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,779.000000000000000000000000000000,3770,0.998999999999999999111821580300,0.998999999999999999111821580300,1861,5000,1
220,220_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,359.000000000000000000000000000000,4466,0.001000000000000000020816681712,0.001000000000000000020816681712,917,1,67
221,221_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,219.000000000000000000000000000000,2845,0.001000000000000000020816681712,0.433739029300483303064339679622,1485,5000,4299
222,222_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,397.000000000000000000000000000000,3818,0.001000000000000000020816681712,0.998999999999999999111821580300,1750,1,1
223,223_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,333.000000000000000000000000000000,4269,0.001000000000000000020816681712,0.998999999999999999111821580300,1086,338,2712
224,224_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,553.000000000000000000000000000000,2333,0.001000000000000000020816681712,0.998999999999999999111821580300,1510,3531,1
225,225_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,806.000000000000000000000000000000,4087,0.001000000000000000020816681712,0.998999999999999999111821580300,2165,5000,1
226,226_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,363.000000000000000000000000000000,3678,0.998999999999999999111821580300,0.998999999999999999111821580300,2658,5000,5000
227,227_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,657.000000000000000000000000000000,3587,0.998999999999999999111821580300,0.998999999999999999111821580300,3549,5000,1
228,228_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,98.000000000000000000000000000000,2304,0.001000000000000000020816681712,0.001000000000000000020816681712,2034,5000,938
229,229_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,100.000000000000000000000000000000,2315,0.001000000000000000020816681712,0.324902484270620961481768063095,1378,302,5000
230,230_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,390.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,3125,5000
231,231_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,613.000000000000000000000000000000,3355,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,5000,1
232,232_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,774.000000000000000000000000000000,4000,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,5000,1
233,233_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,276.000000000000000000000000000000,3534,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,5000,5000
234,234_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,737.000000000000000000000000000000,4631,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,5000,1
235,235_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,102.000000000000000000000000000000,2295,0.998999999999999999111821580300,0.392773255375790442123218326742,5000,5000,5000
236,236_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,399.000000000000000000000000000000,4217,0.001000000000000000020816681712,0.998999999999999999111821580300,2332,5000,5000
237,237_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,241.000000000000000000000000000000,3470,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,5000,5000
238,238_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,215.000000000000000000000000000000,2885,0.001000000000000000020816681712,0.001000000000000000020816681712,1670,5000,1
239,239_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,238.000000000000000000000000000000,2883,0.947432593993701277490515622048,0.735837641328374592042393942393,1474,2116,1
240,240_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,46.000000000000000000000000000000,2068,0.001000000000000000020816681712,0.740165259293622312952720676549,2393,2871,4452
241,241_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,60.000000000000000000000000000000,2070,0.998999999999999999111821580300,0.001000000000000000020816681712,4892,1267,5000
242,242_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4662,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,2020
243,243_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4312,0.998999999999999999111821580300,0.810447079100424683240078138624,1,1,4747
244,244_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4786,0.001000000000000000020816681712,0.001000000000000000020816681712,1,288,4447
245,245_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,52.000000000000000000000000000000,2051,0.998999999999999999111821580300,0.001000000000000000020816681712,4520,1,5000
246,246_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,54.000000000000000000000000000000,2064,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,3836,5000
247,247_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4570,0.001000000000000000020816681712,0.001000000000000000020816681712,1,2714,2831
248,248_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,65.000000000000000000000000000000,2098,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,4606,5000
249,249_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1642,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,5000
250,250_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,339.000000000000000000000000000000,1972,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,1,5000
251,251_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,52.000000000000000000000000000000,2042,0.998999999999999999111821580300,0.001000000000000000020816681712,4145,1,3767
252,252_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.735795438908774523945055534568,0.769247586107714820258252075291,1695,3227,2487
253,253_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3934,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,1
254,254_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,412.000000000000000000000000000000,1973,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,1,5000
255,255_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.685326732440785346689438028989,0.705455822676239518997931554622,4345,4679,2344
256,256_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3405,0.001000000000000000020816681712,0.198565824778902277891745598026,1,3022,4836
257,257_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,45.000000000000000000000000000000,1,0.998999999999999999111821580300,0.001000000000000000020816681712,3243,2603,3749
258,258_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,375.000000000000000000000000000000,3981,0.001000000000000000020816681712,0.001000000000000000020816681712,2786,2412,5000
259,259_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4997,0.998999999999999999111821580300,0.998999999999999999111821580300,1,967,5000
260,260_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4779,0.998999999999999999111821580300,0.998999999999999999111821580300,1,4915,5000
261,261_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,439.000000000000000000000000000000,1992,0.998999999999999999111821580300,0.001000000000000000020816681712,3341,1,3339
262,262_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,320.000000000000000000000000000000,1987,0.001000000000000000020816681712,0.998999999999999999111821580300,2505,1739,5000
263,263_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4383,0.001000000000000000020816681712,0.233189802825437220157311912772,1,1649,4436
264,264_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1662,0.998999999999999999111821580300,0.001000000000000000020816681712,1,5000,4692
265,265_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,404.000000000000000000000000000000,1,0.001000000000000000020816681712,0.998999999999999999111821580300,3368,4437,1
266,266_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4229,0.998999999999999999111821580300,0.998999999999999999111821580300,1,4560,3004
267,267_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4815,0.001000000000000000020816681712,0.998999999999999999111821580300,1,4998,5000
268,268_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,308.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.998999999999999999111821580300,3677,1753,5000
269,269_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,61.000000000000000000000000000000,2095,0.165017817336071931366703324784,0.001000000000000000020816681712,4666,1,5000
270,270_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,62.000000000000000000000000000000,2085,0.998999999999999999111821580300,0.001000000000000000020816681712,4400,5000,4003
271,271_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,40.000000000000000000000000000000,1,0.998999999999999999111821580300,0.272026389226228348938718681893,4470,4268,5000
272,272_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1482,0.001000000000000000020816681712,0.294922602681146062142403252437,1,5000,4013
273,273_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,52.000000000000000000000000000000,2054,0.998999999999999999111821580300,0.001000000000000000020816681712,4382,5000,5000
274,274_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,4825,132,3734
275,275_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,62.000000000000000000000000000000,2128,0.998999999999999999111821580300,0.001000000000000000020816681712,4379,5000,4145
276,276_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,39.000000000000000000000000000000,1,0.998999999999999999111821580300,0.255394595653948064395422079542,1787,156,4996
277,277_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,48.000000000000000000000000000000,1,0.092846263766501124781171938594,0.998999999999999999111821580300,566,4041,1145
278,278_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,40.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,1320,1,1059
279,279_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.998999999999999999111821580300,0.998999999999999999111821580300,2193,1781,5000
280,280_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,44.000000000000000000000000000000,1,0.998999999999999999111821580300,0.998999999999999999111821580300,724,1332,4432
281,281_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,16.000000000000000000000000000000,1,0.998999999999999999111821580300,0.556093855430373595893911442545,37,5000,1
282,282_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.998999999999999999111821580300,0.001000000000000000020816681712,2205,5000,4222
283,283_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,50.000000000000000000000000000000,2044,0.001000000000000000020816681712,0.001000000000000000020816681712,4387,5000,3803
284,284_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4509,0.001000000000000000020816681712,0.856468866051512178749760551000,1,1,4670
285,285_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.001000000000000000020816681712,0.998999999999999999111821580300,4016,1,5000
286,286_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,1915,5000
287,287_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,44.000000000000000000000000000000,78,0.001000000000000000020816681712,0.001000000000000000020816681712,332,826,4144
288,288_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,1,1909
289,289_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1378,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,5000
290,290_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,40.000000000000000000000000000000,1,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,1,808
291,291_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1192,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,4215
292,292_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,40.000000000000000000000000000000,1,0.998999999999999999111821580300,0.335295246027957016821119395900,5000,5000,4438
293,293_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,60.000000000000000000000000000000,66,0.998999999999999999111821580300,0.001000000000000000020816681712,4862,5000,3122
294,294_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,42.000000000000000000000000000000,1,0.998999999999999999111821580300,0.615623778532994436751835110044,3663,5000,5000
295,295_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,60.000000000000000000000000000000,77,0.001000000000000000020816681712,0.453972765034577785403513416895,5000,1,4996
296,296_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,5000,1745
297,297_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2266,0.001000000000000000020816681712,0.998999999999999999111821580300,1,859,5000
298,298_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,4179,1,5000
299,299_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,67.000000000000000000000000000000,104,0.998999999999999999111821580300,0.001000000000000000020816681712,1468,1,1680
300,300_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,58.000000000000000000000000000000,66,0.001000000000000000020816681712,0.001000000000000000020816681712,578,5000,1702
301,301_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,97,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,1
302,302_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,107,0.998999999999999999111821580300,0.726068893069183096677932098828,1,636,1200
303,303_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,161,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,1
304,304_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,70.000000000000000000000000000000,137,0.001000000000000000020816681712,0.615105245869220551568901100836,5000,3655,1455
305,305_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,65.000000000000000000000000000000,102,0.001000000000000000020816681712,0.575295007736076779991662988323,1249,5000,4930
306,306_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,90,0.998999999999999999111821580300,0.769958412723721785653197002830,1,5000,2652
307,307_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,67.000000000000000000000000000000,117,0.001000000000000000020816681712,0.998999999999999999111821580300,4413,5000,4711
308,308_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,65.000000000000000000000000000000,103,0.998999999999999999111821580300,0.582045050766772376071855887858,871,1,2446
309,309_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,48.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,820,5000,3998
310,310_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,86.000000000000000000000000000000,102,0.001000000000000000020816681712,0.001000000000000000020816681712,3371,1,5000
311,311_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,66.000000000000000000000000000000,82,0.998999999999999999111821580300,0.001000000000000000020816681712,931,5000,1
312,312_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,145,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,5000
313,313_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,73.000000000000000000000000000000,125,0.001000000000000000020816681712,0.523229161390922459240471198427,877,3798,1
314,314_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,64.000000000000000000000000000000,119,0.001000000000000000020816681712,0.001000000000000000020816681712,1314,5000,5000
315,315_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,121.000000000000000000000000000000,419,0.998999999999999999111821580300,0.778124153252975458983087264642,5000,1651,247
316,316_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,87,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,1
317,317_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,65.000000000000000000000000000000,107,0.998999999999999999111821580300,0.998999999999999999111821580300,1495,1,4808
318,318_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,1810
319,319_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,100.000000000000000000000000000000,120,0.001000000000000000020816681712,0.998999999999999999111821580300,1175,1,1
320,320_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,76,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,1635
321,321_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,53.000000000000000000000000000000,55,0.998999999999999999111821580300,0.001000000000000000020816681712,2319,1,1
322,322_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,69.000000000000000000000000000000,142,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,1,1
323,323_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2716,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,592
324,324_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,39.000000000000000000000000000000,44,0.998999999999999999111821580300,0.001000000000000000020816681712,369,1,1
325,325_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,75.000000000000000000000000000000,200,0.001000000000000000020816681712,0.662455124009408757856931515562,5000,1,1
326,326_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,75.000000000000000000000000000000,144,0.998999999999999999111821580300,0.326172824203752209637485748317,1337,1,5000
327,327_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,2721
328,328_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,55.000000000000000000000000000000,80,0.998999999999999999111821580300,0.001000000000000000020816681712,798,5000,3092
329,329_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,72.000000000000000000000000000000,110,0.998999999999999999111821580300,0.001000000000000000020816681712,3914,1,2436
330,330_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,60.000000000000000000000000000000,74,0.001000000000000000020816681712,0.001000000000000000020816681712,2487,730,3405
331,331_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,69.000000000000000000000000000000,119,0.001000000000000000020816681712,0.001000000000000000020816681712,2643,5000,2637
332,332_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,63.000000000000000000000000000000,101,0.998999999999999999111821580300,0.955061569813945521190134968492,4553,1,4005
333,333_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,56.000000000000000000000000000000,69,0.998999999999999999111821580300,0.259506036151793517685604228973,2572,1,5000
334,334_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,58.000000000000000000000000000000,81,0.998999999999999999111821580300,0.001000000000000000020816681712,2641,5000,5000
335,335_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3490,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,5000
336,336_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,58.000000000000000000000000000000,79,0.998999999999999999111821580300,0.998999999999999999111821580300,3196,1,5000
337,337_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4503,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,2812
338,338_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1215,0.001000000000000000020816681712,0.998999999999999999111821580300,1,452,2847
339,339_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,53.000000000000000000000000000000,57,0.001000000000000000020816681712,0.001000000000000000020816681712,2105,2420,2304
340,340_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,61.000000000000000000000000000000,99,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,1,2408
341,341_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1242,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,1155
342,342_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,505,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,1
343,343_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,56.000000000000000000000000000000,78,0.001000000000000000020816681712,0.998999999999999999111821580300,2405,5000,5000
344,344_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,576,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,5000
345,345_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1062,0.001000000000000000020816681712,0.705082138699009486337843100046,1,5000,5000
346,346_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2778,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,1
347,347_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,78.000000000000000000000000000000,181,0.998999999999999999111821580300,0.001000000000000000020816681712,2724,4809,1
348,348_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,73.000000000000000000000000000000,174,0.001000000000000000020816681712,0.001000000000000000020816681712,4797,56,3095
349,349_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1124,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,3212
350,350_0,COMPLETED,BoTorch,GenerationStep_1,0.589999999999999968913755310496,44.000000000000000000000000000000,14,0.001000000000000000020816681712,0.001000000000000000020816681712,2328,1,3164
351,351_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,70.000000000000000000000000000000,134,0.998999999999999999111821580300,0.001000000000000000020816681712,3456,5000,5000
352,352_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2263,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,2280
353,353_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,44,0.998999999999999999111821580300,0.001000000000000000020816681712,1,2388,5000
354,354_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,55.000000000000000000000000000000,82,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,2597,3041
355,355_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1125,0.998999999999999999111821580300,0.998999999999999999111821580300,1,4747,994
356,356_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4679,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,5000
357,357_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3472,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,3139
358,358_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,45,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,5000
359,359_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,655,0.001000000000000000020816681712,0.321744723981110980481901151506,1,3056,4837
360,360_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,510,0.998999999999999999111821580300,0.001000000000000000020816681712,1,5000,4856
361,361_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,627,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,1744
362,362_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1112,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,2477
363,363_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2657,0.998999999999999999111821580300,0.001000000000000000020816681712,1,4900,4662
364,364_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3211,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,5000
365,365_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,550,0.998999999999999999111821580300,0.001000000000000000020816681712,1,3878,2799
366,366_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,66.000000000000000000000000000000,101,0.001000000000000000020816681712,0.998999999999999999111821580300,1746,5000,3132
367,367_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,485.000000000000000000000000000000,455,0.998999999999999999111821580300,0.998999999999999999111821580300,3306,4033,1
368,368_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,48.000000000000000000000000000000,36,0.001000000000000000020816681712,0.001000000000000000020816681712,3877,5000,3352
369,369_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,54.000000000000000000000000000000,47,0.001000000000000000020816681712,0.001000000000000000020816681712,1704,5000,1
370,370_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,477,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,5000
371,371_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,139.000000000000000000000000000000,513,0.001000000000000000020816681712,0.050542841040825951803849847010,3607,1,1
372,372_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1272,0.001000000000000000020816681712,0.691827182195422274446627852740,1,5000,5000
373,373_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,137.000000000000000000000000000000,515,0.998999999999999999111821580300,0.174178742726780050320556370025,1088,5000,5000
374,374_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,2861
375,375_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,66.000000000000000000000000000000,97,0.001000000000000000020816681712,0.001000000000000000020816681712,4553,5000,1
376,376_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3010,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,5000
377,377_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,734,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1077,5000
378,378_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4304,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,5000
379,379_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,397.000000000000000000000000000000,587,0.001000000000000000020816681712,0.998999999999999999111821580300,859,2909,1
380,380_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,144.000000000000000000000000000000,565,0.001000000000000000020816681712,0.001000000000000000020816681712,1423,464,3555
381,381_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3549,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,5000
382,382_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,352.000000000000000000000000000000,1992,0.998999999999999999111821580300,0.998999999999999999111821580300,2521,1642,4603
383,383_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,646,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1819,1
384,384_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,832,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,3600
385,385_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,151.000000000000000000000000000000,595,0.998999999999999999111821580300,0.001000000000000000020816681712,681,5000,2827
386,386_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,51.000000000000000000000000000000,51,0.001000000000000000020816681712,0.998999999999999999111821580300,2118,1,3051
387,387_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,122.000000000000000000000000000000,511,0.998999999999999999111821580300,0.998999999999999999111821580300,2506,5000,5000
388,388_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,145.000000000000000000000000000000,570,0.001000000000000000020816681712,0.452910903317551849500688376793,1077,154,5000
389,389_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3140,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,1
390,390_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,291.000000000000000000000000000000,1988,0.001000000000000000020816681712,0.998999999999999999111821580300,2483,3267,3563
391,391_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,48.000000000000000000000000000000,2022,0.001000000000000000020816681712,0.998999999999999999111821580300,2232,5000,3420
392,392_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,190,0.001000000000000000020816681712,0.400947451381354125210521033296,1,5000,5000
393,393_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1506,0.998999999999999999111821580300,0.998999999999999999111821580300,1,4907,5000
394,394_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3443,0.998999999999999999111821580300,0.731085680964263628922594762116,1,1,1
395,395_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,53.000000000000000000000000000000,53,0.001000000000000000020816681712,0.001000000000000000020816681712,2036,1,1
396,396_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2321,0.998999999999999999111821580300,0.336970466878185603842865702973,1,4914,5000
397,397_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3327,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,3309
398,398_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2693,0.001000000000000000020816681712,0.931031909010412217497787423781,1,5000,1938
399,399_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,163.000000000000000000000000000000,659,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,1,456
400,400_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2784,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,5000
401,401_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,364.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.001000000000000000020816681712,3408,211,1
402,402_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,1888,5000,2013
403,403_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,53.000000000000000000000000000000,65,0.001000000000000000020816681712,0.998999999999999999111821580300,2035,1,5000
404,404_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,506.000000000000000000000000000000,2615,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,2171,1
405,405_0,COMPLETED,BoTorch,GenerationStep_1,0.589999999999999968913755310496,43.000000000000000000000000000000,10,0.001000000000000000020816681712,0.474193886210390103119749483085,1865,1,4162
406,406_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,254.000000000000000000000000000000,1156,0.998999999999999999111821580300,0.001000000000000000020816681712,712,4258,5000
407,407_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,178.000000000000000000000000000000,835,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,1,1
408,408_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,72.000000000000000000000000000000,150,0.001000000000000000020816681712,0.001000000000000000020816681712,2093,1,1868
409,409_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2770,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,3500
410,410_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2942,0.998999999999999999111821580300,0.001000000000000000020816681712,1,1,1785
411,411_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,52.000000000000000000000000000000,47,0.001000000000000000020816681712,0.001000000000000000020816681712,2249,5000,1
412,412_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,57.000000000000000000000000000000,92,0.001000000000000000020816681712,0.001000000000000000020816681712,1958,5000,1929
413,413_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1447,0.998999999999999999111821580300,0.001000000000000000020816681712,1,5000,2254
414,414_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,220,0.001000000000000000020816681712,0.329801541261335595667247844176,1,1,2837
415,415_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1,0.001000000000000000020816681712,0.887978294464385475848189344106,1,1,1
416,416_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,272.000000000000000000000000000000,3391,0.001000000000000000020816681712,0.001000000000000000020816681712,859,1,5000
417,417_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,1751,1,1
418,418_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,172.000000000000000000000000000000,2711,0.001000000000000000020816681712,0.766398375084678007418403922202,5000,3268,1
419,419_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,305.000000000000000000000000000000,1983,0.001000000000000000020816681712,0.998999999999999999111821580300,2644,5000,4062
420,420_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,345.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.998999999999999999111821580300,711,1,5000
421,421_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,75.000000000000000000000000000000,2194,0.998999999999999999111821580300,0.001000000000000000020816681712,4440,5000,5000
422,422_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,368.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.001000000000000000020816681712,4504,1,5000
423,423_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,156.000000000000000000000000000000,652,0.001000000000000000020816681712,0.001000000000000000020816681712,2519,5000,5000
424,424_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,165.000000000000000000000000000000,2655,0.998999999999999999111821580300,0.001000000000000000020816681712,640,1,2425
425,425_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,162.000000000000000000000000000000,2646,0.998999999999999999111821580300,0.730116814240261868818038237805,613,1,5000
426,426_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,368.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.998999999999999999111821580300,2658,1,5000
427,427_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,90.000000000000000000000000000000,2222,0.001000000000000000020816681712,0.329416553995832528389797744239,2646,5000,3694
428,428_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,350.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.001000000000000000020816681712,698,1,1
429,429_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,310.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.998999999999999999111821580300,4351,3856,5000
430,430_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,364.000000000000000000000000000000,4506,0.998999999999999999111821580300,0.001000000000000000020816681712,647,1,5000
431,431_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,357.000000000000000000000000000000,5000,0.998999999999999999111821580300,0.001000000000000000020816681712,3824,1,5000
432,432_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,113.000000000000000000000000000000,2314,0.001000000000000000020816681712,0.001000000000000000020816681712,3205,5000,5000
433,433_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,227.000000000000000000000000000000,3266,0.001000000000000000020816681712,0.998999999999999999111821580300,2618,969,5000
434,434_0,COMPLETED,BoTorch,GenerationStep_1,0.530000000000000026645352591004,113.000000000000000000000000000000,403,0.001000000000000000020816681712,0.001000000000000000020816681712,2305,151,5000
435,435_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,357.000000000000000000000000000000,4629,0.998999999999999999111821580300,0.001000000000000000020816681712,619,1,1
436,436_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,153.000000000000000000000000000000,2800,0.998999999999999999111821580300,0.001000000000000000020816681712,582,1,1
437,437_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,111.000000000000000000000000000000,550,0.001000000000000000020816681712,0.001000000000000000020816681712,2753,5000,5000
438,438_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,89.000000000000000000000000000000,2264,0.001000000000000000020816681712,0.001000000000000000020816681712,4324,1,5000
439,439_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,169.000000000000000000000000000000,2692,0.998999999999999999111821580300,0.001000000000000000020816681712,617,5000,1
440,440_0,COMPLETED,BoTorch,GenerationStep_1,0.530000000000000026645352591004,142.000000000000000000000000000000,2536,0.001000000000000000020816681712,0.001000000000000000020816681712,597,1469,3294
441,441_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,269.000000000000000000000000000000,3249,0.001000000000000000020816681712,0.001000000000000000020816681712,2549,1,5000
442,442_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,356.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.998999999999999999111821580300,4624,1,5000
443,443_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,389.000000000000000000000000000000,5000,0.001000000000000000020816681712,0.998999999999999999111821580300,4252,1,1
444,444_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,209.000000000000000000000000000000,2910,0.998999999999999999111821580300,0.001000000000000000020816681712,4784,1,1
445,445_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,584.000000000000000000000000000000,1043,0.001000000000000000020816681712,0.998999999999999999111821580300,2273,5000,1
446,446_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,158.000000000000000000000000000000,610,0.001000000000000000020816681712,0.001000000000000000020816681712,2723,1,5000
447,447_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,433.000000000000000000000000000000,1,0.001000000000000000020816681712,0.998999999999999999111821580300,2004,3556,1
448,448_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,228.000000000000000000000000000000,986,0.001000000000000000020816681712,0.001000000000000000020816681712,2485,5000,1
449,449_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,191.000000000000000000000000000000,787,0.001000000000000000020816681712,0.001000000000000000020816681712,2358,3294,5000
450,450_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,407.000000000000000000000000000000,4280,0.998999999999999999111821580300,0.001000000000000000020816681712,3269,1,1
451,451_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,4691,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,5000
452,452_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,930,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,1996
453,453_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,91,0.001000000000000000020816681712,0.459303553129571995317093069389,1,1271,2355
454,454_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,54.000000000000000000000000000000,56,0.001000000000000000020816681712,0.001000000000000000020816681712,3237,89,1
455,455_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1553,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,5000
456,456_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,747,0.998999999999999999111821580300,0.430093222762811089321388635653,1,5000,1983
457,457_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,353.000000000000000000000000000000,1983,0.001000000000000000020816681712,0.998999999999999999111821580300,2807,1,4988
458,458_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,65.000000000000000000000000000000,71,0.001000000000000000020816681712,0.573768148354241169784017984057,3720,5000,5000
459,459_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,40.000000000000000000000000000000,3,0.001000000000000000020816681712,0.461313899864062459954539008322,4546,1,2949
460,460_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,52.000000000000000000000000000000,50,0.998999999999999999111821580300,0.001000000000000000020816681712,4447,1,1933
461,461_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,60.000000000000000000000000000000,97,0.001000000000000000020816681712,0.379526196668601600858750089174,4342,1,5000
462,462_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3055,0.998999999999999999111821580300,0.998999999999999999111821580300,1,490,5000
463,463_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3287,0.001000000000000000020816681712,0.998999999999999999111821580300,1,3460,1
464,464_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,57.000000000000000000000000000000,56,0.001000000000000000020816681712,0.462646483321048906933725675117,2229,4764,5000
465,465_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,52.000000000000000000000000000000,2035,0.001000000000000000020816681712,0.921074974887893582753406462871,2156,2258,3457
466,466_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.001000000000000000020816681712,0.655257157066279183332824231911,2604,1987,5000
467,467_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,2134,0.001000000000000000020816681712,0.629523339314953522816153963504,1,3200,2679
468,468_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,390.000000000000000000000000000000,4346,0.001000000000000000020816681712,0.001000000000000000020816681712,2965,1,1
469,469_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,368.000000000000000000000000000000,4440,0.998999999999999999111821580300,0.001000000000000000020816681712,3527,5000,5000
470,470_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,427.000000000000000000000000000000,1988,0.001000000000000000020816681712,0.384570022710660042175589978797,3747,5000,5000
471,471_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,62.000000000000000000000000000000,119,0.001000000000000000020816681712,0.998999999999999999111821580300,237,4861,1659
472,472_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,904,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1386,4377
473,473_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3339,0.001000000000000000020816681712,0.001000000000000000020816681712,1,520,1
474,474_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1438,0.998999999999999999111821580300,0.998999999999999999111821580300,1,450,1262
475,475_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,48.000000000000000000000000000000,27,0.998999999999999999111821580300,0.001000000000000000020816681712,3933,2451,1
476,476_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,51.000000000000000000000000000000,44,0.001000000000000000020816681712,0.998999999999999999111821580300,1055,5000,5000
477,477_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,332.000000000000000000000000000000,4449,0.001000000000000000020816681712,0.998999999999999999111821580300,3691,562,5000
478,478_0,COMPLETED,BoTorch,GenerationStep_1,0.530000000000000026645352591004,106.000000000000000000000000000000,379,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,5000,3832
479,479_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,53.000000000000000000000000000000,45,0.998999999999999999111821580300,0.001000000000000000020816681712,1918,1,2571
480,480_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,54.000000000000000000000000000000,55,0.998999999999999999111821580300,0.571241508763125072078992161551,5000,1258,1
481,481_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1286,0.001000000000000000020816681712,0.998999999999999999111821580300,1,3910,1
482,482_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,317.000000000000000000000000000000,1996,0.998999999999999999111821580300,0.998999999999999999111821580300,2335,4931,3589
483,483_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,888,0.001000000000000000020816681712,0.001000000000000000020816681712,1,2158,610
484,484_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3402,0.998999999999999999111821580300,0.998999999999999999111821580300,1,2998,2034
485,485_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,235.000000000000000000000000000000,3079,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,2419,5000
486,486_0,COMPLETED,BoTorch,GenerationStep_1,0.579999999999999960031971113494,53.000000000000000000000000000000,51,0.001000000000000000020816681712,0.001000000000000000020816681712,3341,1,1645
487,487_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,89.000000000000000000000000000000,223,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,1462,5000
488,488_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1367,0.998999999999999999111821580300,0.998999999999999999111821580300,1,30,4053
489,489_0,COMPLETED,BoTorch,GenerationStep_1,0.570000000000000062172489379009,58.000000000000000000000000000000,76,0.998999999999999999111821580300,0.001000000000000000020816681712,3300,1,2029
490,490_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,41.000000000000000000000000000000,1,0.001000000000000000020816681712,0.617973814998244219687251188589,5000,757,1
491,491_0,COMPLETED,BoTorch,GenerationStep_1,0.600000000000000088817841970013,49.000000000000000000000000000000,2006,0.001000000000000000020816681712,0.998999999999999999111821580300,2247,5000,2983
492,492_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,44.000000000000000000000000000000,2136,0.001000000000000000020816681712,0.001000000000000000020816681712,200,259,1
493,493_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,488.000000000000000000000000000000,1067,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,2904,1
494,494_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,1293,0.998999999999999999111821580300,0.789661683060529751010392374155,1,370,1961
495,495_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3099,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,687
496,496_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,2.000000000000000000000000000000,3352,0.998999999999999999111821580300,0.475030541731023658869048631459,1,3058,1916
497,497_0,COMPLETED,BoTorch,GenerationStep_1,0.540000000000000035527136788005,173.000000000000000000000000000000,3008,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,2090,5000
498,498_0,COMPLETED,BoTorch,GenerationStep_1,0.560000000000000053290705182008,433.000000000000000000000000000000,67,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,225,1
499,499_0,COMPLETED,BoTorch,GenerationStep_1,0.550000000000000044408920985006,195.000000000000000000000000000000,3132,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,1986,5000
500,500_0,COMPLETED,Sobol,SOBOL,0.579999999999999960031971113494,52.000000000000000000000000000000,2030,0.769822901606559750753433490900,0.116178741380572325692099866501,1201,4100,2449
501,501_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,393.000000000000000000000000000000,4751,0.420292748181149367070474909269,0.653679883657023341747560607473,3852,875,2543
502,502_0,COMPLETED,Sobol,SOBOL,0.560000000000000053290705182008,389.000000000000000000000000000000,3702,0.723883657721802631357377322274,0.472985742552205934430276101921,2321,1512,4526
503,503_0,COMPLETED,Sobol,SOBOL,0.540000000000000035527136788005,235.000000000000000000000000000000,808,0.093931327927857632964503409312,0.764892867684364263780594228592,2785,3443,488
504,504_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,72.000000000000000000000000000000,78,0.528046754516661165368418551225,0.580909054661169599320658107899,3596,3069,1820
505,505_0,COMPLETED,Sobol,SOBOL,0.540000000000000035527136788005,257.000000000000000000000000000000,2953,0.162946710327640187365716428758,0.180843047659844158303599215287,1256,1879,3173
506,506_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,373.000000000000000000000000000000,4250,0.981131191411986902650710362650,0.937971060600131800732981446345,4760,31,3906
507,507_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,296.000000000000000000000000000000,1510,0.335561373211443414454890898924,0.292295945743098861679953870407,234,4936,1109
508,508_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,402.000000000000000000000000000000,1874,0.660259993368759734444495279604,0.921690523363649871768643606629,1697,949,200
509,509_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,395.000000000000000000000000000000,3969,0.030733322761952876212010465906,0.339365426843985906746326008943,3413,4018,4795
510,510_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,171.000000000000000000000000000000,2609,0.832349622927606058730987115268,0.533901605715975113852778122236,574,3361,2831
511,511_0,COMPLETED,Sobol,SOBOL,0.540000000000000035527136788005,84.000000000000000000000000000000,338,0.484343030923977513335643152459,0.197185750894248473796821485848,4474,1587,2181
512,512_0,COMPLETED,Sobol,SOBOL,0.560000000000000053290705182008,252.000000000000000000000000000000,1171,0.917568079514428980303364369320,0.396221541019156575647031104381,4132,2430,830
513,513_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,321.000000000000000000000000000000,3423,0.272547657642513541098594487266,0.872329429063946060196599319170,857,2525,4165
514,514_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,327.000000000000000000000000000000,4406,0.590757529351860322108791478968,0.008680147845298052944329469938,2974,4393,3450
515,515_0,COMPLETED,Sobol,SOBOL,0.540000000000000035527136788005,85.000000000000000000000000000000,2292,0.227057307584211220952141729867,0.730381919192150230735194327281,1883,582,1562
516,516_0,FAILED,Sobol,SOBOL,,,2438,0.615951864290982475935720685811,0.359930213890969741274972193423,4867,3631,4313
517,517_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,342.000000000000000000000000000000,4534,0.199902481405064474939692331645,0.901314037462696449054533331946,30,1343,694
518,518_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,301.000000000000000000000000000000,3256,0.881641709474846768657130269276,0.221391933297738430219681049493,3489,731,1370
519,519_0,COMPLETED,Sobol,SOBOL,0.540000000000000035527136788005,221.000000000000000000000000000000,986,0.310411736000329230300565086509,0.509384998567402380587054722128,1461,4224,3620
520,520_0,COMPLETED,Sobol,SOBOL,0.530000000000000026645352591004,160.000000000000000000000000000000,485,0.873175600089132752934517611720,0.832761662738397689942360102577,2428,4787,4933
521,521_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,224.000000000000000000000000000000,2736,0.441556324580684278480191551353,0.436579422641545533689821922962,2581,161,74
522,522_0,COMPLETED,Sobol,SOBOL,0.560000000000000053290705182008,394.000000000000000000000000000000,3803,0.639889362135902084460781225062,0.693991216067224692132242580556,1094,2063,1999
523,523_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,340.000000000000000000000000000000,1689,0.053041900254786014667907068088,0.044402859272435306337012406175,4056,2905,2990
524,524_0,FAILED,Sobol,SOBOL,,,1345,0.942768402034416808099592799408,0.678137241452932304497380755492,2866,1731,3352
525,525_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,382.000000000000000000000000000000,4064,0.371963611863553533787296601076,0.091898085070773960492118703769,2089,3237,1657
526,526_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,248.000000000000000000000000000000,3100,0.553728230558335754452059518371,0.785206300882622554304646200762,4240,3830,963
527,527_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,84.000000000000000000000000000000,204,0.139202883118763554026742212955,0.452373127356171633728365577554,652,1118,4024
528,528_0,COMPLETED,Sobol,SOBOL,0.530000000000000026645352591004,162.000000000000000000000000000000,641,0.701076369209215011224500813114,0.145175778517499576292237861708,466,398,2732
529,529_0,COMPLETED,Sobol,SOBOL,0.550000000000000044408920985006,320.000000000000000000000000000000,3518,0.114777827773243190634389065963,0.617370424624532510016194919444,4679,4557,2277
530,530_0,COMPLETED,Sobol,SOBOL,0.569999999999999951150186916493,415.000000000000000000000000000000,4896,0.811136255953460949541522495565,0.252004923891276100267333504235,1806,2674,333
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2037,0.998999999999999999111821580300,0.001000000000000000020816681712,1,4328,2124
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,50.000000000000000000000000000000,29,0.998999999999999999111821580300,0.001000000000000000020816681712,4048,4655,1570
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,72.000000000000000000000000000000,2120,0.001000000000000000020816681712,0.771300723490472961429986753501,2181,2103,3588
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,49.000000000000000000000000000000,27,0.998999999999999999111821580300,0.001000000000000000020816681712,2927,2871,2099
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,4563,0.001000000000000000020816681712,0.456939869776912421794889951343,1,3426,5000
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,68.000000000000000000000000000000,59,0.998999999999999999111821580300,0.382920644386281261439819445513,5000,5000,2763
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,48.000000000000000000000000000000,1,0.998999999999999999111821580300,0.298586427550020294674482101982,3812,1,2756
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,62.000000000000000000000000000000,56,0.001000000000000000020816681712,0.001000000000000000020816681712,2674,1,2153
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2964,0.001000000000000000020816681712,0.998999999999999999111821580300,1,2748,3063
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,71.000000000000000000000000000000,70,0.001000000000000000020816681712,0.001000000000000000020816681712,4059,5000,1
541,541_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3637,0.001000000000000000020816681712,0.998999999999999999111821580300,1,3812,1
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,1877,0.001000000000000000020816681712,0.001000000000000000020816681712,1,3745,3445
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,550.000000000000000000000000000000,1995,0.001000000000000000020816681712,0.915645268160136915902569398895,2424,5000,3911
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.589999999999999968913755310496,52.000000000000000000000000000000,2050,0.001000000000000000020816681712,0.801229489927046234498675403302,2158,2779,3393
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.599999999999999977795539507497,43.000000000000000000000000000000,2006,0.998999999999999999111821580300,0.760047253395907396189556948229,2306,1,3636
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.589999999999999968913755310496,49.000000000000000000000000000000,2034,0.998999999999999999111821580300,0.803486427780501832884851864947,2212,921,3553
547,547_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,65.000000000000000000000000000000,74,0.998999999999999999111821580300,0.599292791745273167869356711890,4830,3005,3244
548,548_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,51.000000000000000000000000000000,2046,0.998999999999999999111821580300,0.777131626611356707279298916546,2202,1,3492
549,549_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,478.000000000000000000000000000000,1994,0.001000000000000000020816681712,0.693925714561366646648821188137,2365,1616,3247
550,550_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,441.000000000000000000000000000000,1989,0.998999999999999999111821580300,0.753929670976074661759014361451,2604,1,3541
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,53.000000000000000000000000000000,2019,0.998999999999999999111821580300,0.998999999999999999111821580300,2176,1,3908
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,55.000000000000000000000000000000,21,0.001000000000000000020816681712,0.614931636085832789007099563605,1026,1,5000
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,63.000000000000000000000000000000,60,0.001000000000000000020816681712,0.001000000000000000020816681712,2909,5000,3249
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,4576,0.001000000000000000020816681712,0.998999999999999999111821580300,1,4454,5000
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,68.000000000000000000000000000000,2038,0.998999999999999999111821580300,0.998999999999999999111821580300,2097,4002,4119
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,166.000000000000000000000000000000,2442,0.001000000000000000020816681712,0.001000000000000000020816681712,4664,5000,4014
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,429.000000000000000000000000000000,1993,0.998999999999999999111821580300,0.998999999999999999111821580300,2178,102,3721
558,558_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,64.000000000000000000000000000000,2057,0.998999999999999999111821580300,0.998999999999999999111821580300,2071,1769,3664
559,559_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,64.000000000000000000000000000000,76,0.998999999999999999111821580300,0.001000000000000000020816681712,4705,1,1
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,421.000000000000000000000000000000,1978,0.998999999999999999111821580300,0.001000000000000000020816681712,4135,3754,5000
561,561_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,4992,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,3929
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.589999999999999968913755310496,68.000000000000000000000000000000,2007,0.998999999999999999111821580300,0.643529381964494384682495820016,2124,5000,3581
563,563_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,76.000000000000000000000000000000,2148,0.001000000000000000020816681712,0.998999999999999999111821580300,2113,4394,4142
564,564_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,51.000000000000000000000000000000,2025,0.998999999999999999111821580300,0.998999999999999999111821580300,2127,4597,2930
565,565_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,77.000000000000000000000000000000,75,0.998999999999999999111821580300,0.001000000000000000020816681712,4499,5000,2171
566,566_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,72.000000000000000000000000000000,64,0.998999999999999999111821580300,0.743681789231322887268049726117,4403,5000,5000
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,501.000000000000000000000000000000,1981,0.998999999999999999111821580300,0.998999999999999999111821580300,2178,5000,4684
568,568_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,3.000000000000000000000000000000,4056,0.001000000000000000020816681712,0.998999999999999999111821580300,1,5000,5000
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,53.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,2014,2352,5000
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,473.000000000000000000000000000000,1973,0.998999999999999999111821580300,0.998999999999999999111821580300,1820,1,3690
571,571_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,53.000000000000000000000000000000,47,0.998999999999999999111821580300,0.998999999999999999111821580300,1673,1,3697
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,76.000000000000000000000000000000,59,0.998999999999999999111821580300,0.001000000000000000020816681712,2328,881,2004
573,573_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,87.000000000000000000000000000000,69,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,5000,1
574,574_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,83.000000000000000000000000000000,67,0.998999999999999999111821580300,0.001000000000000000020816681712,4168,1,1
575,575_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,91.000000000000000000000000000000,110,0.998999999999999999111821580300,0.001000000000000000020816681712,1914,4317,3896
576,576_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,72.000000000000000000000000000000,2032,0.998999999999999999111821580300,0.489561338665735312769555775958,2197,4317,3364
577,577_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,56.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,961,746,1
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,526.000000000000000000000000000000,1988,0.998999999999999999111821580300,0.402027486371680176091558678309,2294,5000,3284
579,579_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,557.000000000000000000000000000000,2002,0.001000000000000000020816681712,0.998999999999999999111821580300,2092,2733,1
580,580_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,435.000000000000000000000000000000,1976,0.001000000000000000020816681712,0.998999999999999999111821580300,1857,5000,4125
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,376.000000000000000000000000000000,1971,0.998999999999999999111821580300,0.998999999999999999111821580300,4312,5000,5000
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,511.000000000000000000000000000000,1978,0.998999999999999999111821580300,0.001000000000000000020816681712,2222,1954,2540
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,72.000000000000000000000000000000,69,0.998999999999999999111821580300,0.001000000000000000020816681712,4379,2116,3610
584,584_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,4199,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1438,5000
585,585_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,68.000000000000000000000000000000,54,0.998999999999999999111821580300,0.446938756886335220031014614506,1924,4883,3154
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,65.000000000000000000000000000000,56,0.001000000000000000020816681712,0.578142831275240909327806093643,1832,460,3164
587,587_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,70.000000000000000000000000000000,49,0.001000000000000000020816681712,0.630629648033993683853282163909,1860,5000,3718
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,380,0.001000000000000000020816681712,0.998999999999999999111821580300,1,2062,1787
589,589_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2120,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1,2454
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,66.000000000000000000000000000000,43,0.998999999999999999111821580300,0.534496147489301520749904739205,802,4522,2714
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,3.000000000000000000000000000000,3939,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,5000
592,592_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,68.000000000000000000000000000000,2061,0.001000000000000000020816681712,0.998999999999999999111821580300,2284,4746,3812
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,440,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1842,5000
594,594_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,63.000000000000000000000000000000,57,0.998999999999999999111821580300,0.284412009720618752517395932955,4548,1,4979
595,595_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,1059,0.998999999999999999111821580300,0.001000000000000000020816681712,1,4049,2151
596,596_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,414.000000000000000000000000000000,1977,0.001000000000000000020816681712,0.998999999999999999111821580300,2013,1,3738
597,597_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3683,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1857,5000
598,598_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,1892,0.001000000000000000020816681712,0.998999999999999999111821580300,1,834,3580
599,599_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,406.000000000000000000000000000000,1970,0.998999999999999999111821580300,0.653796340091102434755043759651,2006,1165,3578
600,600_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,87.000000000000000000000000000000,2127,0.001000000000000000020816681712,0.998999999999999999111821580300,2317,4728,4171
601,601_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,68.000000000000000000000000000000,2040,0.001000000000000000020816681712,0.998999999999999999111821580300,2431,5000,4010
602,602_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,89.000000000000000000000000000000,88,0.998999999999999999111821580300,0.998999999999999999111821580300,493,3921,3181
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,65.000000000000000000000000000000,56,0.998999999999999999111821580300,0.001000000000000000020816681712,1937,5000,1187
604,604_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,355,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1969,1964
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,438.000000000000000000000000000000,1970,0.998999999999999999111821580300,0.001000000000000000020816681712,4522,427,2704
606,606_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,62.000000000000000000000000000000,44,0.001000000000000000020816681712,0.998999999999999999111821580300,1713,5000,3943
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,81.000000000000000000000000000000,2141,0.998999999999999999111821580300,0.998999999999999999111821580300,2597,2242,4950
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,71.000000000000000000000000000000,2134,0.998999999999999999111821580300,0.998999999999999999111821580300,2469,4827,3701
609,609_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,60.000000000000000000000000000000,46,0.998999999999999999111821580300,0.001000000000000000020816681712,4763,5000,5000
610,610_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,67.000000000000000000000000000000,2115,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,885,5000
611,611_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,39.000000000000000000000000000000,1,0.998999999999999999111821580300,0.001000000000000000020816681712,987,1,2380
612,612_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,269.000000000000000000000000000000,1498,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,1340,5000
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,293,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1741,5000
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,187,0.998999999999999999111821580300,0.998999999999999999111821580300,1,77,1
615,615_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,333.000000000000000000000000000000,1998,0.001000000000000000020816681712,0.998999999999999999111821580300,2111,5000,1667
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,965,0.001000000000000000020816681712,0.001000000000000000020816681712,1,3720,3499
617,617_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3242,0.001000000000000000020816681712,0.001000000000000000020816681712,1,4601,341
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,70.000000000000000000000000000000,63,0.998999999999999999111821580300,0.001000000000000000020816681712,4133,5000,5000
619,619_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,80.000000000000000000000000000000,2141,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,5000,5000
620,620_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2355,0.998999999999999999111821580300,0.998999999999999999111821580300,1,3359,4259
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,83.000000000000000000000000000000,105,0.001000000000000000020816681712,0.001000000000000000020816681712,1689,289,1
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,1,0.998999999999999999111821580300,0.425280555286932870906468906469,1,4761,5000
623,623_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.540000000000000035527136788005,326.000000000000000000000000000000,1417,0.001000000000000000020816681712,0.001000000000000000020816681712,5000,4961,177
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,71.000000000000000000000000000000,59,0.001000000000000000020816681712,0.001000000000000000020816681712,1785,1,1108
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,54.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,1115,1,5000
626,626_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,61.000000000000000000000000000000,55,0.001000000000000000020816681712,0.001000000000000000020816681712,1987,311,5000
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.540000000000000035527136788005,266.000000000000000000000000000000,1086,0.998999999999999999111821580300,0.001000000000000000020816681712,3772,1833,5000
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.540000000000000035527136788005,260.000000000000000000000000000000,1058,0.998999999999999999111821580300,0.001000000000000000020816681712,4605,4333,5000
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,51.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,2995,5000,2212
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,55.000000000000000000000000000000,2050,0.001000000000000000020816681712,0.998999999999999999111821580300,2437,1,4307
631,631_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,3.000000000000000000000000000000,4870,0.001000000000000000020816681712,0.001000000000000000020816681712,1,5000,5000
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,83.000000000000000000000000000000,2096,0.998999999999999999111821580300,0.001000000000000000020816681712,1299,1478,1
633,633_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,48.000000000000000000000000000000,1,0.001000000000000000020816681712,0.998999999999999999111821580300,5000,1022,5000
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,64.000000000000000000000000000000,142,0.998999999999999999111821580300,0.998999999999999999111821580300,5000,2074,5000
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.579999999999999960031971113494,62.000000000000000000000000000000,2039,0.998999999999999999111821580300,0.998999999999999999111821580300,2666,3576,5000
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,49.000000000000000000000000000000,2030,0.001000000000000000020816681712,0.998999999999999999111821580300,2623,5000,5000
637,637_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,55.000000000000000000000000000000,2056,0.001000000000000000020816681712,0.998999999999999999111821580300,2584,4575,5000
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2834,0.001000000000000000020816681712,0.998999999999999999111821580300,1,47,2085
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,2055,0.998999999999999999111821580300,0.998999999999999999111821580300,1,5000,2659
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,65.000000000000000000000000000000,144,0.998999999999999999111821580300,0.001000000000000000020816681712,3781,1,1
641,641_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3180,0.998999999999999999111821580300,0.998999999999999999111821580300,1,5000,5000
642,642_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,67.000000000000000000000000000000,2067,0.001000000000000000020816681712,0.998999999999999999111821580300,2517,5000,5000
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3581,0.001000000000000000020816681712,0.998999999999999999111821580300,1,1,2871
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,67.000000000000000000000000000000,2138,0.001000000000000000020816681712,0.001000000000000000020816681712,2486,3226,408
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3008,0.998999999999999999111821580300,0.998999999999999999111821580300,1,284,1
646,646_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,61.000000000000000000000000000000,120,0.998999999999999999111821580300,0.998999999999999999111821580300,2457,1593,5000
647,647_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,62.000000000000000000000000000000,2083,0.001000000000000000020816681712,0.998999999999999999111821580300,2490,4918,4960
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,40.000000000000000000000000000000,1,0.001000000000000000020816681712,0.001000000000000000020816681712,4012,176,2326
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.998999999999999999111821580300,0.001000000000000000020816681712,3222,385,5000
650,650_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,68.000000000000000000000000000000,159,0.998999999999999999111821580300,0.001000000000000000020816681712,5000,4897,4642
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3533,0.998999999999999999111821580300,0.001000000000000000020816681712,1,962,1
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,61.000000000000000000000000000000,2120,0.001000000000000000020816681712,0.001000000000000000020816681712,1364,4664,1
653,653_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,3.000000000000000000000000000000,4405,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,5000
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,43.000000000000000000000000000000,1,0.001000000000000000020816681712,0.419036050403635229599785816390,594,3469,5000
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.540000000000000035527136788005,72.000000000000000000000000000000,171,0.998999999999999999111821580300,0.001000000000000000020816681712,1089,5000,1
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.569999999999999951150186916493,358.000000000000000000000000000000,4317,0.001000000000000000020816681712,0.001000000000000000020816681712,2346,1,5000
657,657_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,4041,0.998999999999999999111821580300,0.998999999999999999111821580300,1,1,1064
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.560000000000000053290705182008,63.000000000000000000000000000000,2124,0.001000000000000000020816681712,0.998999999999999999111821580300,3506,1032,4013
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.550000000000000044408920985006,2.000000000000000000000000000000,3144,0.001000000000000000020816681712,0.001000000000000000020816681712,1,1952,2546
660,660_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3668,0.001000000000000000020816681712,0.001000000000000000020816681712,1,4022,5000
</pre>
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				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 4512527 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4512527/4512527_0_result.pkl
has not produced any output (state: NODE_FAIL)
No output/error stream produced ! Check: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4512527/4512527_0_log.out


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4512527/4512527_0_log.out not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4512527/4512527_0_log.err not found


⚠ Job 4513196 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4513196/4513196_0_result.pkl
has not produced any output (state: CANCELLED by 0)
No output/error stream produced ! Check: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4513196/4513196_0_log.out


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4513196/4513196_0_log.out not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CDLEEDS_OutdoorObjects_HoeffdingTreeClassifier_ACCURACY-RUNTIME/1/single_runs/4513196/4513196_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>None                                                                                                                                 </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/CDLEEDS_OutdoorObjects_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>30                                                                                                                                   </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">1744908680.5412745,20,0,0
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1745190717.1814766,20,1,5
1745190729.7668903,20,1,5
1745190742.9362993,20,1,5
1745190755.930742,20,1,5
1745190768.8297048,20,1,5
1745190781.518478,20,1,5
1745190793.920002,20,1,5
1745190806.7640734,20,1,5
1745190818.660912,20,1,5
1745190824.1842737,20,1,5
1745190832.5842998,20,0,0
1745190847.3369186,20,0,0
1745195597.3862255,20,0,0
1745195597.678736,20,0,0
1745195599.2398002,20,1,5
1745195606.6867898,20,1,5
1745199228.84524,20,1,5
1745199229.3667526,20,1,5
1745199231.1580977,20,2,10
1745199231.8735933,20,2,10
1745199243.4902656,20,1,5
1745199243.5619526,20,1,5
1745203121.9071665,20,1,5
1745203122.295894,20,1,5
1745203124.1219244,20,2,10
1745203124.76286,20,2,10
1745203136.714677,20,1,5
1745203136.905377,20,1,5
1745207347.0458145,20,1,5
1745207347.3749506,20,1,5
1745207349.1429257,20,2,10
1745207349.6839302,20,2,10
1745207360.232905,20,1,5
1745207360.477301,20,1,5
1745210402.3183036,20,1,5
1745210402.8840177,20,1,5
1745210404.3141932,20,2,10
1745210404.9131527,20,2,10
1745210417.7101495,20,1,5
1745210417.890233,20,1,5
1745214744.8703759,20,1,5
1745214745.2591248,20,1,5
1745214747.1691113,20,2,10
1745214747.91513,20,2,10
1745214759.7585924,20,1,5
1745214759.940607,20,1,5
1745219421.7596319,20,1,5
1745219422.1442175,20,1,5
1745219424.0526702,20,2,10
1745219424.799267,20,2,10
1745219437.8706958,20,1,5
1745219437.9423864,20,1,5
1745223420.347787,20,1,5
1745223420.938611,20,1,5
1745223423.0942304,20,2,10
1745223423.6396856,20,2,10
1745223433.866033,20,1,5
1745223434.0359292,20,1,5
1745226188.52487,20,1,5
1745226189.0129545,20,1,5
1745226190.4223614,20,2,10
1745226190.9139378,20,2,10
1745226200.8791606,20,1,5
1745226201.0339618,20,1,5
1745229726.6054265,20,1,5
1745229727.0085618,20,1,5
1745229728.4208758,20,2,10
1745229728.9333956,20,2,10
1745229738.1539016,20,1,5
1745229738.3353639,20,1,5
1745234296.3623784,20,1,5
1745234297.1682937,20,1,5
1745234299.1628325,20,2,10
1745234300.2351213,20,2,10
1745234314.5069427,20,1,5
1745234314.6008446,20,1,5
1745239852.3669724,20,1,5
1745239853.1911457,20,1,5
1745239855.12981,20,2,10
1745239856.1546667,20,2,10
1745239869.9167502,20,1,5
1745239870.1241229,20,1,5
1745244239.1138012,20,1,5
1745244239.6003308,20,1,5
1745244241.426957,20,2,10
1745244242.2888517,20,2,10
1745244256.0443943,20,1,5
1745244256.1292167,20,1,5
1745248484.4944377,20,1,5
1745248485.0695221,20,1,5
1745248486.9873319,20,2,10
1745248487.5905943,20,2,10
1745248497.886425,20,1,5
1745248498.0707865,20,1,5
1745251767.6729548,20,1,5
1745251768.1962001,20,1,5
1745251769.9920607,20,2,10
1745251770.5393503,20,2,10
1745251780.3676424,20,1,5
1745251780.4362407,20,1,5
1745255983.6394534,20,1,5
1745255984.1476648,20,1,5
1745255985.9618037,20,2,10
1745255986.4967675,20,2,10
1745255996.1400995,20,1,5
1745255996.309626,20,1,5
1745259192.1322527,20,1,5
1745259192.688151,20,1,5
1745259194.1380758,20,2,10
1745259194.5956447,20,2,10
1745259204.0533292,20,1,5
1745259204.216748,20,1,5
1745262667.730444,20,1,5
1745262668.1977823,20,1,5
1745262669.9504313,20,2,10
1745262670.506156,20,2,10
1745262680.084507,20,1,5
1745262680.1388245,20,1,5
1745267703.9163327,20,1,5
1745267704.3149161,20,1,5
1745267706.2161777,20,2,10
1745267706.8789885,20,2,10
1745267717.6870012,20,1,5
1745267717.8635478,20,1,5
1745271680.7011936,20,1,5
1745271681.0424492,20,1,5
1745271682.9387121,20,2,10
1745271683.3630245,20,2,10
1745271693.0983975,20,1,5
1745271693.1915853,20,1,5
1745271700.3868394,20,1,5
1745271711.3614113,20,1,5
1745271722.4062989,20,1,5
1745271733.3639414,20,1,5
1745271738.762389,20,1,5
1745271745.334906,20,0,0
1745271755.983224,20,0,0
1745275029.8973598,20,0,0
1745275030.1120434,20,0,0
1745275033.1529481,20,1,5
1745275039.3807125,20,1,5
1745278459.6931298,20,1,5
1745278460.3273299,20,1,5
1745278462.0593853,20,2,10
1745278462.5952485,20,2,10
1745278472.3753293,20,1,5
1745278472.8092222,20,1,5
1745282840.4373982,20,1,5
1745282841.025466,20,1,5
1745282842.7080295,20,2,10
1745282843.2023437,20,2,10
1745282852.890385,20,1,5
1745282853.0536919,20,1,5
1745286775.5905435,20,1,5
1745286776.0150392,20,1,5
1745286777.5286608,20,2,10
1745286778.0168478,20,2,10
1745286787.788723,20,1,5
1745286787.9666245,20,1,5
1745290588.4023519,20,1,5
1745290588.9611254,20,1,5
1745290590.3992882,20,2,10
1745290590.8928194,20,2,10
1745290600.6781304,20,1,5
1745290600.855554,20,1,5
1745294232.597949,20,1,5
1745294232.9252646,20,1,5
1745294235.3890824,20,2,10
1745294235.8949642,20,2,10
1745294245.584995,20,1,5
1745294245.6491246,20,1,5
1745297623.6851952,20,1,5
1745297623.9773798,20,1,5
1745297625.435702,20,2,10
1745297625.9535286,20,2,10
1745297635.712665,20,1,5
1745297635.8791406,20,1,5
1745301265.009242,20,1,5
1745301265.3450267,20,1,5
1745301267.042567,20,2,10
1745301267.4920237,20,2,10
1745301277.2436275,20,1,5
1745301277.410046,20,1,5
1745304822.0569975,20,1,5
1745304822.4671497,20,1,5
1745304824.1043563,20,2,10
1745304824.619017,20,2,10
1745304834.4846637,20,1,5
1745304834.8517394,20,1,5
1745308312.679241,20,1,5
1745308313.2283766,20,1,5
1745308315.113132,20,2,10
1745308316.1410182,20,2,10
1745308330.2405825,20,1,5
1745308330.3351533,20,1,5
1745313394.4453986,20,1,5
1745313394.9800782,20,1,5
1745313396.384841,20,2,10
1745313396.8432324,20,2,10
1745313406.4123235,20,1,5
1745313406.4720974,20,1,5
1745317059.5336542,20,1,5
1745317060.0889645,20,1,5
1745317061.509965,20,2,10
1745317062.0179696,20,2,10
1745317072.0252242,20,1,5
1745317072.1959429,20,1,5
1745321676.5049493,20,1,5
1745321677.0097039,20,1,5
1745321678.39602,20,2,10
1745321678.8553574,20,2,10
1745321688.820221,20,1,5
1745321688.9757473,20,1,5
1745326046.0778658,20,1,5
1745326046.6268327,20,1,5
1745326048.103931,20,2,10
1745326048.612912,20,2,10
1745326058.8803773,20,1,5
1745326058.9399533,20,1,5
1745330902.703171,20,1,5
1745330903.0925024,20,1,5
1745330904.5566497,20,2,10
1745330905.0608811,20,2,10
1745330915.463627,20,1,5
1745330915.8373454,20,1,5
1745335597.3598537,20,1,5
1745335597.9512813,20,1,5
1745335599.3954003,20,2,10
1745335599.9803786,20,2,10
1745335610.4936132,20,1,5
1745335610.826363,20,1,5
1745339833.2572317,20,1,5
1745339833.8152602,20,1,5
1745339835.2637594,20,2,10
1745339835.7635975,20,2,10
1745339845.4780161,20,1,5
1745339845.5334647,20,1,5
1745343324.286567,20,1,5
1745343324.7620106,20,1,5
1745343326.1524324,20,2,10
1745343326.61505,20,2,10
1745343336.853251,20,1,5
1745343337.00778,20,1,5
1745347400.7231936,20,1,5
1745347401.1115866,20,1,5
1745347402.5706263,20,2,10
1745347403.0431879,20,2,10
1745347412.920366,20,1,5
1745347413.0831172,20,1,5
1745351139.4267921,20,1,5
1745351139.972345,20,1,5
1745351141.4389682,20,2,10
1745351141.9020834,20,2,10
1745351152.1725647,20,1,5
1745351152.370006,20,1,5
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'> Download &raquo;worker_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;CPU/RAM-Usage (main)</h1>
			<div class='invert_in_dark_mode' id='mainWorkerCPURAM'></div><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download &raquo;cpu_ram_usage.csv&laquo; as file</button>
<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1744908680,642.28515625,17.1
1744908680,642.2890625,13.7
1744908680,642.2890625,14.5
1744908680,642.2890625,15.3
1744908680,642.2890625,14.3
1744908680,642.2890625,15.1
1744908680,642.2890625,13.3
1744909399,705.0234375,23.2
1744909399,705.0234375,19.2
1744909399,705.0234375,19.2
1744909399,705.0234375,18.4
1744929987,934.73828125,35.9
1744929987,934.73828125,42.9
1744929987,934.73828125,43.1
1744929987,934.73828125,32.4
1744980842,978.1875,37.9
1744980842,978.1875,32.4
1744980842,978.1875,31.4
1744980842,978.1875,25.8
1745049502,1042.08203125,48.0
1745049502,1042.08203125,47.0
1745049503,1042.08203125,45.3
1745049503,1042.08203125,44.0
1745119715,979.515625,32.3
1745119715,979.515625,14.3
1745119715,979.515625,14.3
1745119715,979.515625,13.6
1745190703,1026.01953125,20.5
1745190703,1026.01953125,23.3
1745190703,1026.01953125,24.2
1745190703,1026.01953125,25.0
1745271700,1070.85546875,28.5
1745271700,1070.85546875,4.2
1745271700,1070.85546875,4.6
1745271700,1070.85546875,5.1
1745351159,1109.765625,17.9
1745351159,1109.765625,24.7
1745351159,1109.765625,24.9
1745351159,1109.765625,12.5
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'> Copy raw data to clipboard</button>
			<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'> Download &raquo;cpu_ram_usage.csv&laquo; as file</button>
			
			<h1>&nbsp;Parallel Plot</h1>
			<div class="invert_in_dark_mode" id="parallel-plot"></div>
			<h1>&nbsp;Scatter-2D</h1>
			<div class='invert_in_dark_mode' id='plotScatter2d'></div>
			<h1>&nbsp;Scatter-3D</h1>
			<div class='invert_in_dark_mode' id='plotScatter3d'></div>
			<h1>&nbsp;Job Status Distribution</h1>
			<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
			<h1>&nbsp;Boxplots</h1>
			<div class="invert_in_dark_mode" id="plotBoxplot"></div>
			<h1>&nbsp;Violin</h1>
			<div class="invert_in_dark_mode" id="plotViolin"></div>
			<h1>&nbsp;Histogram</h1>
			<div class="invert_in_dark_mode" id="plotHistogram"></div>
			<h1>&nbsp;Heatmap</h1>
			<div class="invert_in_dark_mode" id="plotHeatmap"></div><br>
			    <h1>Correlation Heatmap Explanation</h1>
			
			    <p>
			        This is a heatmap that visualizes the correlation between numerical columns in a dataset. The values represented in the heatmap show the strength and direction of relationships between different variables.
			    </p>
			
			    <h2>How It Works</h2>
			    <p>
			        The heatmap uses a matrix to represent correlations between each pair of numerical columns. The calculation behind this is based on the concept of "correlation," which measures how strongly two variables are related. A correlation can be positive, negative, or zero:
			    </p>
			    <ul>
			        <li><strong>Positive correlation</strong>: Both variables increase or decrease together (e.g., if the temperature rises, ice cream sales increase).</li>
			        <li><strong>Negative correlation</strong>: As one variable increases, the other decreases (e.g., as the price of a product rises, the demand for it decreases).</li>
			        <li><strong>Zero correlation</strong>: There is no relationship between the two variables (e.g., height and shoe size might show zero correlation in some contexts).</li>
			    </ul>
			
			    <h2>Color Scale: Yellow to Purple (Viridis)</h2>
			    <p>
			        The heatmap uses a color scale called "Viridis," which ranges from yellow to purple. Here's what the colors represent:
			    </p>
			    <ul>
			        <li><strong>Yellow (brightest)</strong>: A strong positive correlation (close to +1). This indicates that as one variable increases, the other increases in a very predictable manner.</li>
			        <li><strong>Green</strong>: A moderate positive correlation. Variables are still positively related, but the relationship is not as strong.</li>
			        <li><strong>Blue</strong>: A weak or near-zero correlation. There is a small or no discernible relationship between the variables.</li>
			        <li><strong>Purple (darkest)</strong>: A strong negative correlation (close to -1). This indicates that as one variable increases, the other decreases in a very predictable manner.</li>
			    </ul>
			
			    <h2>What the Heatmap Shows</h2>
			    <p>
			        In the heatmap, each cell represents the correlation between two numerical columns. The color of the cell is determined by the correlation coefficient: from yellow for strong positive correlations, through green and blue for weaker correlations, to purple for strong negative correlations.
			    </p>
			
			<h1>&nbsp;Result-Pairs</h1>
			<div class="invert_in_dark_mode" id="plotResultPairs"></div>
			<h1>&nbsp;Evolution</h1>
			<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
	</body>
</html>