OmniOpt2

Setting	Value
Max. nr. evaluations	50444
Max. nr. evaluations (from arguments)	50000
Number random steps	20
Nr. of workers (parameter)	50
Main process memory (GB)	8
Worker memory (GB)	32
Nr. imported jobs	444
Generation Node	Total	COMPLETED	FAILED	RUNNING
SOBOL	30	29	1	0
BOTORCH_MODULAR	651	448	197	6
Name	Type	Lower bound	Upper bound	Values	Type	Log Scale?
recent_samples_size	int	1	5000		int	No
n_samples	int	1	5000		int	No
confidence	choice			0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001
feature_proportion	float	0.001	0.999		float	No
n_clusters	int	1	50		int	No
Failed	Succeeded	Running	Total
198	477	6	681
name	min/max
ACCURACY	max
RUNTIME	min
Key	Value
config_yaml	None
config_toml	None
config_json	None
num_random_steps	20
max_eval	50000
run_program	None
experiment_name	None
mem_gb	32
parameter	None
continue_previous_job	/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/4/
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	50
worker_timeout	120
slurm_use_srun	False
time
partition
reservation	None
force_local_execution	False
slurm_signal_delay_s	0
nodes_per_job	1
cpus_per_task	32
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
Parameter	Min	Max	Mean	Std Dev	Count
generation_method	No numerical statistics available
ACCURACY	0.19	0.93	0.8658	0.0698	477
RUNTIME	171	7065	521.1048	769.4002	477
recent_samples_size	1	5000	2678.7812	1576.675	681
n_samples	1	5000	1997.9736	1604.5651	681
feature_proportion	0.001	0.999	0.6116	0.2857	681
n_clusters	1	50	23.558	17.2457	681
confidence	0.001	0.25	0.0522	0.0773	681
Skipped tabs:
Job-Infos
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		<title>Exported &raquo;s4122485/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/0&laquo; from OmniOpt2-Share</title>
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.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;
	border: solid 1px;
}

#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: sans-serif;
}

.gridjs-th-content {
	overflow: visible !important;
}

.error_text {
	color: red;
}

h1, h2, h3, h4, h5, h6 {
	margin-top: 1em;
	font-weight: bold;
	color: #333;
	border-left: 5px solid #ccc;
	padding-left: 0.5em;
}

.no_cursive {
	font-style: normal;	
}

.caveat {
	background-color: #fff8b3;
	border: 1px solid #f2d600;
	padding: 1em 1em 1em 70px;
	position: relative;
	font-family: sans-serif;
	color: #665500;
	margin: 1em 0;
	border-radius: 4px;
}

.caveat h1, .caveat h2, .caveat h3, .caveat h4 {
	margin-top: 0;
	margin-bottom: 0.5em;
	font-weight: bold;
}

.caveat::before {
	content: "⚠️";
	font-size: 50px;
	line-height: 1;
	position: absolute;
	left: 10px;
	top: 50%;
	transform: translateY(-50%);
	pointer-events: none;
	user-select: none;
}

.caveat.warning::before { content: "⚠️"; }
.caveat.stop::before { content: "🛑"; }
.caveat.exclamation::before { content: "❗"; }
.caveat.alarm::before { content: "🚨"; }
.caveat.tip::before { content: "💡"; }

.tutorial_icon {
	display: inline-block;
	font-size: 1.3em;
	line-height: 1;
	vertical-align: middle;
	transform: translateY(-10%);
	padding: 0.2em 0;
}

.highlight {
	background-color: yellow;
	font-weight: bold;
}

#searchResults li {
	opacity: 0;
	transform: translateY(8px);
	animation: fadeInUp 0.3s ease-out forwards;
	animation-delay: 0.05s;
	list-style: none;
	margin-bottom: 5px;
}

@keyframes fadeInUp {
	to {
		opacity: 1;
		transform: translateY(0);
	}
}

.search_headline {
	font-weight: bold;
	margin-top: 1em;
	margin-bottom: 0.3em;
	color: #444;
}

.search_share_path {
	color: black;
	display: block ruby;
	margin-top: 20px;
}

@media print {
	#scads_bar {
		display: none !important;
	}
}

/*! XP.css v0.2.6 - https: //botoxparty.github.io/XP.css/ */
body{
	color: #222
}

.surface{
	background: #ece9d8
}

u{
	text-decoration: none;
	border-bottom: .5px solid #222
}

a{
	color: #00f
}

a: focus{
	outline: 1px dotted #00f
}

code,code *{
	font-family: monospace
}

pre{
	display: block;
	padding: 12px 8px;
	background-color: #000;
	color: silver;
	font-size: 1rem;
	margin: 0;
	overflow: scroll;
}

summary: focus{
	outline: 1px dotted #000
}

: :-webkit-scrollbar{
	width: 16px
}

: :-webkit-scrollbar: horizontal{
	height: 17px
}

: :-webkit-scrollbar-track{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='2' height='2' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 0H0v1h1v1h1V1H1V0z' fill='silver'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 0H1v1H0v1h1V1h1V0z' fill='%23fff'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-thumb{
	background-color: #dfdfdf;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}

: :-webkit-scrollbar-button: horizontal: end: increment,: :-webkit-scrollbar-button: horizontal: start: decrement,: :-webkit-scrollbar-button: vertical: end: increment,: :-webkit-scrollbar-button: vertical: start: decrement{
	display: block
}

: :-webkit-scrollbar-button: vertical: start{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 6H7v1H6v1H5v1H4v1h7V9h-1V8H9V7H8V6z' fill='%23000'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: vertical: end{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 6H4v1h1v1h1v1h1v1h1V9h1V8h1V7h1V6z' fill='%23000'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: horizontal: start{
	width: 16px;
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 4H8v1H7v1H6v1H5v1h1v1h1v1h1v1h1V4z' fill='%23000'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: horizontal: end{
	width: 16px;
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='16' height='17' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 0H0v16h1V1h14V0z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M2 1H1v14h1V2h12V1H2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M16 17H0v-1h15V0h1v17z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M15 1h-1v14H1v1h14V1z' fill='gray'/%3E%3Cpath fill='silver' d='M2 2h12v13H2z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M7 4H6v7h1v-1h1V9h1V8h1V7H9V6H8V5H7V4z' fill='%23000'/%3E%3C/svg%3E")
}

button{
	border: none;
	background: #ece9d8;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf;
	border-radius: 0;
	min-width: 75px;
	min-height: 23px;
	padding: 0 12px
}

button: not(: disabled).active,button: not(: disabled): active{
	box-shadow: inset -1px -1px #fff,inset 1px 1px #0a0a0a,inset -2px -2px #dfdfdf,inset 2px 2px grey
}

button.focused,button: focus{
	outline: 1px dotted #000;
	outline-offset: -4px
}

label{
	display: inline-flex;
	align-items: center
}

textarea{
	padding: 3px 4px;
	border: none;
	background-color: #fff;
	box-sizing: border-box;
	-webkit-appearance: none;
	-moz-appearance: none;
	appearance: none;
	border-radius: 0
}

textarea: focus{
	outline: none
}

select: focus option{
	color: #000;
	background-color: #fff
}

.vertical-bar{
	width: 4px;
	height: 20px;
	background: silver;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #fff,inset -2px -2px grey,inset 2px 2px #dfdfdf
}

&: disabled,&: disabled+label{
	color: grey;
	text-shadow: 1px 1px 0 #fff
}

input[type=radio]+label{
	line-height: 13px;
	position: relative;
	margin-left: 19px
}

input[type=radio]+label: before{
	content: "";
	position: absolute;
	top: 0;
	left: -19px;
	display: inline-block;
	width: 13px;
	height: 13px;
	margin-right: 6px;
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='%23fff'/%3E%3C/svg%3E")
}

input[type=radio]: active+label: before{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}

input[type=radio]: checked+label: after{
	content: "";
	display: block;
	width: 5px;
	height: 5px;
	top: 5px;
	left: -14px;
	position: absolute;
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=radio][disabled]+label: before{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='12' height='12' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 0H4v1H2v1H1v2H0v4h1v2h1V8H1V4h1V2h2V1h4v1h2V1H8V0z' fill='gray'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M8 1H4v1H2v2H1v4h1v1h1V8H2V4h1V3h1V2h4v1h2V2H8V1z' fill='%23000'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 3h1v1H9V3zm1 5V4h1v4h-1zm-2 2V9h1V8h1v2H8zm-4 0v1h4v-1H4zm0 0V9H2v1h2z' fill='%23DFDFDF'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M11 2h-1v2h1v4h-1v2H8v1H4v-1H2v1h2v1h4v-1h2v-1h1V8h1V4h-1V2z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M4 2h4v1h1v1h1v4H9v1H8v1H4V9H3V8H2V4h1V3h1V2z' fill='silver'/%3E%3C/svg%3E")
}

input[type=radio][disabled]: checked+label: after{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='4' height='4' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M3 0H1v1H0v2h1v1h2V3h1V1H3V0z' fill='gray'/%3E%3C/svg%3E")
}

input[type=email],input[type=password]{
	padding: 3px 4px;
	border: 1px solid #7f9db9;
	background-color: #fff;
	box-sizing: border-box;
	-webkit-appearance: none;
	-moz-appearance: none;
	appearance: none;
	border-radius: 0;
	height: 21px;
	line-height: 2
}

input[type=email]: focus,input[type=password]: focus{
	outline: none
}

input[type=range]{
	-webkit-appearance: none;
	width: 100%;
	background: transparent
}

input[type=range]: focus{
	outline: none
}

input[type=range]: :-webkit-slider-thumb{
	-webkit-appearance: none;
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=range]: :-moz-range-thumb{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v16h2v2h2v2h1v-1H3v-2H1V1h9V0z' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M1 1v15h1v1h1v1h1v1h2v-1h1v-1h1v-1h1V1z' fill='%23C0C7C8'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v15H8v2H6v2H5v-1h2v-2h2z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v16H9v2H7v2H5v1h1v-2h2v-2h2z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=range]: :-webkit-slider-runnable-track{
	background: #000;
	border-right: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}

input[type=range]: :-moz-range-track{
	background: #000;
	border-right: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: 1px 0 0 #fff,1px 1px 0 #fff,0 1px 0 #fff,-1px 0 0 #a9a9a9,-1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,-1px 1px 0 #fff,1px -1px #a9a9a9
}

input[type=range].has-box-indicator: :-webkit-slider-thumb{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}

input[type=range].has-box-indicator: :-moz-range-thumb{
	background: url("data: image/svg+xml;charset=utf-8,%3Csvg width='11' height='21' fill='none' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0v20h1V1h9V0z' fill='%23fff'/%3E%3Cpath fill='%23C0C7C8' d='M1 1h8v18H1z'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M9 1h1v19H1v-1h8z' fill='%2387888F'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M10 0h1v21H0v-1h10z' fill='%23000'/%3E%3C/svg%3E")
}

.is-vertical{
	display: inline-block;
	width: 4px;
	height: 150px;
	transform: translateY(50%)
}

.is-vertical>input[type=range]{
	width: 150px;
	height: 4px;
	margin: 0 16px 0 10px;
	transform-origin: left;
	transform: rotate(270deg) translateX(calc(-50% + 8px))
}

.is-vertical>input[type=range]: :-webkit-slider-runnable-track{
	border-left: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}

.is-vertical>input[type=range]: :-moz-range-track{
	border-left: 1px solid grey;
	border-bottom: 1px solid grey;
	box-shadow: -1px 0 0 #fff,-1px 1px 0 #fff,0 1px 0 #fff,1px 0 0 #a9a9a9,1px -1px 0 #a9a9a9,0 -1px 0 #a9a9a9,1px 1px 0 #fff,-1px -1px #a9a9a9
}

.is-vertical>input[type=range]: :-webkit-slider-thumb{
	transform: translateY(-8px) scaleX(-1)
}

.is-vertical>input[type=range]: :-moz-range-thumb{
	transform: translateY(2px) scaleX(-1)
}

.is-vertical>input[type=range].has-box-indicator: :-webkit-slider-thumb{
	transform: translateY(-10px) scaleX(-1)
}

.is-vertical>input[type=range].has-box-indicator: :-moz-range-thumb{
	transform: translateY(0) scaleX(-1)
}

.window{
	font-size: 11px;
	box-shadow: inset -1px -1px #0a0a0a,inset 1px 1px #dfdfdf,inset -2px -2px grey,inset 2px 2px #fff;
	background: #ece9d8;
	padding: 3px
}

.window fieldset{
	margin-bottom: 9px
}

.title-bar{
	background: #000;
	padding: 3px 2px 3px 3px;
	display: flex;
	justify-content: space-between;
	align-items: center
}

.title-bar-text{
	font-weight: 700;
	color: #fff;
	letter-spacing: 0;
	margin-right: 24px
}

.title-bar-controls button{
	padding: 0;
	display: block;
	min-width: 16px;
	min-height: 14px
}

.title-bar-controls button: focus{
	outline: none
}

.window-body{
	margin: 8px
}

.window-body pre{
	margin: -8px
}

.status-bar{
	margin: 0 1px;
	display: flex;
	gap: 1px
}

.status-bar-field{
	box-shadow: inset -1px -1px #dfdfdf,inset 1px 1px grey;
	flex-grow: 1;
	padding: 2px 3px;
	margin: 0
}

ul.tree-view{
	display: block;
	background: #fff;
	padding: 6px;
	margin: 0
}

ul.tree-view li{
	list-style-type: none;
	margin-top: 3px
}

ul.tree-view a{
	text-decoration: none;
	color: #000
}

ul.tree-view a: focus{
	background-color: #2267cb;
	color: #fff
}

ul.tree-view ul{
	margin-top: 3px;
	margin-left: 16px;
	padding-left: 16px;
	border-left: 1px dotted grey
}

ul.tree-view ul>li{
	position: relative
}

ul.tree-view ul>li: before{
	content: "";
	display: block;
	position: absolute;
	left: -16px;
	top: 6px;
	width: 12px;
	border-bottom: 1px dotted grey
}

ul.tree-view ul>li: last-child: after{
	content: "";
	display: block;
	position: absolute;
	left: -20px;
	top: 7px;
	bottom: 0;
	width: 8px;
	background: #fff
}

ul.tree-view ul details>summary: before{
	margin-left: -22px;
	position: relative;
	z-index: 1
}

ul.tree-view details{
	margin-top: 0
}

ul.tree-view details>summary: before{
	text-align: center;
	display: block;
	float: left;
	content: "+";
	border: 1px solid grey;
	width: 8px;
	height: 9px;
	line-height: 9px;
	margin-right: 5px;
	padding-left: 1px;
	background-color: #fff
}

ul.tree-view details[open] summary{
	margin-bottom: 0
}

ul.tree-view details[open]>summary: before{
	content: "-"
}

fieldset{
	border-image: url("data: image/svg+xml;charset=utf-8,%3Csvg width='5' height='5' fill='gray' xmlns='http: //www.w3.org/2000/svg'%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h5v5H0V2h2v1h1V2H0' fill='%23fff'/%3E%3Cpath fill-rule='evenodd' clip-rule='evenodd' d='M0 0h4v4H0V1h1v2h2V1H0'/%3E%3C/svg%3E") 2;
	padding: 10px;
	padding-block-start: 8px;
	margin: 0
}

legend{
	background: #ece9d8
}

menu[role=tablist]{
	position: relative;
	margin: 0 0 -2px;
	text-indent: 0;
	list-style-type: none;
	display: flex;
	padding-left: 3px
}

menu[role=tablist] button{
	z-index: 1;
	display: block;
	color: #222;
	text-decoration: none;
	min-width: unset
}

menu[role=tablist] button[aria-selected=true]{
	padding-bottom: 2px;margin-top: -2px;background-color: #ece9d8;position: relative;z-index: 8;margin-left: -3px;margin-bottom: 1px
}

menu[role=tablist] button: focus{
	outline: 1px dotted #222;outline-offset: -4px
}

menu[role=tablist].justified button{
	flex-grow: 1;text-align: center
}

[role=tabpanel]{
	padding: 14px;clear: both;background: linear-gradient(180deg,#fcfcfe,#f4f3ee);border: 1px solid #919b9c;position: relative;z-index: 2;margin-bottom: 9px
}

: :-webkit-scrollbar{
	width: 17px
}

: :-webkit-scrollbar-corner{
	background: #dfdfdf
}

: :-webkit-scrollbar-track: vertical{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 1' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1'/%3E%3Cpath stroke='%23f3f1ec' d='M1 0h1'/%3E%3Cpath stroke='%23f4f1ec' d='M2 0h1'/%3E%3Cpath stroke='%23f4f3ee' d='M3 0h1'/%3E%3Cpath stroke='%23f5f4ef' d='M4 0h1'/%3E%3Cpath stroke='%23f6f5f0' d='M5 0h1'/%3E%3Cpath stroke='%23f7f7f3' d='M6 0h1'/%3E%3Cpath stroke='%23f9f8f4' d='M7 0h1'/%3E%3Cpath stroke='%23f9f9f7' d='M8 0h1'/%3E%3Cpath stroke='%23fbfbf8' d='M9 0h1'/%3E%3Cpath stroke='%23fbfbf9' d='M10 0h2'/%3E%3Cpath stroke='%23fdfdfa' d='M12 0h1'/%3E%3Cpath stroke='%23fefefb' d='M13 0h3'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-track: horizontal{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 1 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1M0 16h1'/%3E%3Cpath stroke='%23f3f1ec' d='M0 1h1'/%3E%3Cpath stroke='%23f4f1ec' d='M0 2h1'/%3E%3Cpath stroke='%23f4f3ee' d='M0 3h1'/%3E%3Cpath stroke='%23f5f4ef' d='M0 4h1'/%3E%3Cpath stroke='%23f6f5f0' d='M0 5h1'/%3E%3Cpath stroke='%23f7f7f3' d='M0 6h1'/%3E%3Cpath stroke='%23f9f8f4' d='M0 7h1'/%3E%3Cpath stroke='%23f9f9f7' d='M0 8h1'/%3E%3Cpath stroke='%23fbfbf8' d='M0 9h1'/%3E%3Cpath stroke='%23fbfbf9' d='M0 10h1m-1 1h1'/%3E%3Cpath stroke='%23fdfdfa' d='M0 12h1'/%3E%3Cpath stroke='%23fefefb' d='M0 13h1m-1 1h1m-1 1h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-thumb{
	background-position: 50%;
	background-repeat: no-repeat;
	background-color: #c8d6fb;
	background-size: 7px;
	border: 1px solid #fff;
	border-radius: 2px;
	box-shadow: inset -3px 0 #bad1fc,inset 1px 1px #b7caf5
}

: :-webkit-scrollbar-thumb: vertical{
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 7 8' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h6M0 2h6M0 4h6M0 6h6'/%3E%3Cpath stroke='%23bad1fc' d='M6 0h1M6 2h1M6 4h1'/%3E%3Cpath stroke='%23c8d6fb' d='M0 1h1M0 3h1M0 5h1M0 7h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h6M1 3h6M1 5h6M1 7h6'/%3E%3Cpath stroke='%23bad3fc' d='M6 6h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-thumb: horizontal{
	background-size: 8px;background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 8 7' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eef4fe' d='M0 0h1m1 0h1m1 0h1m1 0h1M0 1h1m1 0h1m1 0h1m1 0h1M0 2h1m1 0h1m1 0h1m1 0h1M0 3h1m1 0h1m1 0h1m1 0h1M0 4h1m1 0h1m1 0h1m1 0h1M0 5h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23c8d6fb' d='M1 0h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%238cb0f8' d='M1 1h1m1 0h1m1 0h1m1 0h1M1 2h1m1 0h1m1 0h1m1 0h1M1 3h1m1 0h1m1 0h1m1 0h1M1 4h1m1 0h1m1 0h1m1 0h1M1 5h1m1 0h1m1 0h1m1 0h1M1 6h1m1 0h1m1 0h1m1 0h1'/%3E%3Cpath stroke='%23bad1fc' d='M0 6h1m1 0h1'/%3E%3Cpath stroke='%23bad3fc' d='M4 6h1m1 0h1'/%3E%3C/svg%3E")
}

: :-webkit-scrollbar-button: vertical: start{
	height: 17px;
	background-image: url("data: image/svg+xml;charset=utf-8,%3Csvg xmlns='http: //www.w3.org/2000/svg' viewBox='0 -0.5 17 17' shape-rendering='crispEdges'%3E%3Cpath stroke='%23eeede5' d='M0 0h1m15 0h1M0 1h1M0 2h1M0 3h1M0 4h1M0 5h1M0 6h1M0 7h1M0 8h1M0 9h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m-1 1h1m15 0h1M0 16h1m15 0h1'/%3E%3Cpath stroke='%23fdfdfa' d='M1 0h1'/%3E%3Cpath stroke='%23fff' d='M2 0h14M1 1h1m13 0h1M1 2h1m13 0h1M1 3h1m13 0h1M1 4h1m13 0h1M1 5h1m13 0h1M1 6h1m13 0h1M1 7h1m13 0h1M1 8h1m13 0h1M1 9h1m13 0h1M1 10h1m13 0h1M1 11h1m13 0h1M1 12h1m13 0h1M1 13h1m13 0h1M1 14h1m13 0h1M2 15h13'/%3E%3Cpath stroke='%23e6eefc' d='M2 1h1'/%3E%3Cpath stroke='%23d0dffc' d='M3 1h1M2 2h1'/%3E%3Cpath stroke='%23cad8f9' d='M4 1h1M2 3h1'/%3E%3Cpath stroke='%23c4d2f7' d='M5 1h1'/%3E%3Cpath stroke='%23c0d0f7' d='M6 1h1'/%3E%3Cpath stroke='%23bdcef7' d='M7 1h1M2 6h1'/%3E%3Cpath stroke='%23bbcdf5' d='M8 1h1'/%3E%3Cpath stroke='%23b8cbf6' d='M9 1h1M2 7h1'/%3E%3Cpath stroke='%23b7caf5' d='M10 1h1M2 8h1'/%3E%3Cpath stroke='%23b5c8f7' d='M11 1h1'/%3E%3Cpath stroke='%23b3c7f5' d='M12 1h1'/%3E%3Cpath stroke='%23afc5f4' d='M13 1h1'/%3E%3Cpath stroke='%23dce6f9' d='M14 1h1'/%3E%3Cpath stroke='%23dfe2e1' d='M16 1h1'/%3E%3Cpath stroke='%23e1eafe' d='M3 2h1'/%3E%3Cpath stroke='%23dae6fe' d='M4 2h1M3 3h1'/%3E%3Cpath stroke='%23d4e1fc' d='M5 2h1M3 4h1'/%3E%3Cpath stroke='%23d1e0fd' d='M6 2h1M4 4h1'/%3E%3Cpath stroke='%23d0ddfc' d='M7 2h1M3 5h1'/%3E%3Cpath stroke='%23cedbfd' d='M8 2h1M6 3h1'/%3E%3Cpath stroke='%23cad9fd' d='M9 2h1M7 3h1M5 5h1'/%3E%3Cpath stroke='%23c8d8fb' d='M10 2h1'/%3E%3Cpath stroke='%23c5d6fc' d='M11 2h1m-8 8h1m1 0h1'/%3E%3Cpath stroke='%23c2d3fc' d='M12 2h1m-2 1h1m-9 7h1m0 1h1'/%3E%3Cpath stroke='%23bccefa' d='M13 2h1m-1 2h1m-9 9h2'/%3E%3Cpath stroke='%23b9c9f3' d='M14 2h1M5 14h3'/%3E%3Cpath stroke='%23cfd7dd' d='M16 2h1'/%3E%3Cpath stroke='%23d8e3fc' d='M4 3h1'/%3E%3Cpath stroke='%23d1defd' d='M5 3h1'/%3E%3Cpath stroke='%23c9d8fc' d='M8 3h1M6 4h2M5 6h2M3 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: :-webkit-scrollbar-button: vertical: end{
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}

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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: "";
	position: absolute;
	top: 1px;
	left: 2px;
	width: 100%;
	height: calc(100% - 2px);
	padding: 1px 2px;
	border-radius: 2px;
	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]): after,progress: not([value]): after: not([value]){
	animation: sliding 2s linear 0s infinite
}

progress: not([value]): after: not([value]){
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        0.91,
        377,
        3140,
        1103,
        0.999,
        1,
        0.001
    ],
    [
        669,
        "669_0",
        "FAILED",
        "BoTorch",
        "BOTORCH_MODULAR",
        "",
        "",
        1655,
        617,
        0.999,
        33,
        0.005
    ],
    [
        670,
        "670_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.9,
        269,
        1734,
        2864,
        0.001,
        1,
        0.25
    ],
    [
        671,
        "671_0",
        "FAILED",
        "BoTorch",
        "BOTORCH_MODULAR",
        "",
        "",
        2685,
        510,
        0.999,
        29,
        0.005
    ],
    [
        672,
        "672_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.84,
        5961,
        4153,
        4711,
        0.44740439376783364,
        30,
        0.005
    ],
    [
        673,
        "673_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.88,
        292,
        1359,
        2230,
        0.4761603033433401,
        11,
        0.005
    ],
    [
        674,
        "674_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.8,
        4634,
        2438,
        2301,
        0.30770916915833,
        50,
        0.1
    ],
    [
        675,
        "675_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.9,
        330,
        3142,
        1406,
        0.7560898567110358,
        1,
        0.1
    ],
    [
        676,
        "676_0",
        "FAILED",
        "BoTorch",
        "BOTORCH_MODULAR",
        "",
        "",
        4861,
        692,
        0.9985161138330911,
        31,
        0.005
    ],
    [
        677,
        "677_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.91,
        339,
        4630,
        1569,
        0.24870298045187494,
        1,
        0.005
    ],
    [
        678,
        "678_0",
        "COMPLETED",
        "BoTorch",
        "BOTORCH_MODULAR",
        0.68,
        178,
        2023,
        876,
        0.2504291419370374,
        1,
        0.005
    ],
    [
        679,
        "679_0",
        "RUNNING",
        "BoTorch",
        "BOTORCH_MODULAR",
        "",
        "",
        4682,
        1779,
        0.4716847634435087,
        24,
        0.1
    ],
    [
        680,
        "680_0",
        "RUNNING",
        "BoTorch",
        "BOTORCH_MODULAR",
        "",
        "",
        423,
        1,
        0.6809234943805991,
        21,
        0.005
    ]
];
var tab_worker_usage_csv_json = [
    [
        1746862358.2331367,
        50,
        0,
        0
    ]
];
var tab_main_worker_cpu_ram_csv_json = [
    [
        1746862358,
        646.03125,
        4.6
    ],
    [
        1746862358,
        640.390625,
        3.9
    ],
    [
        1746862358,
        640.390625,
        4.7
    ],
    [
        1746862358,
        640.390625,
        6
    ],
    [
        1746862358,
        640.390625,
        3
    ],
    [
        1746862358,
        640.390625,
        5.6
    ],
    [
        1746862358,
        640.390625,
        4
    ]
];
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 = [], reload = false) {
	try {
		if ($("#parallel-plot").data("loaded") === "true" && !reload) {
			return;
		}

		// Filter rows ohne leere Werte (wie in deinem Originalcode)
		dataArray = filterNonEmptyRows(dataArray);

		const ignoreSet = new Set(ignoreColumns);
		const numericalCols = [];
		const categoricalCols = [];
		const categoryMappings = {};
		const enable_slurm_id_if_exists = $("#enable_slurm_id_if_exists").is(":checked");

		// Spalten einteilen in numerisch oder kategorisch + category mappings aufbauen
		headers.forEach((header, colIndex) => {
			if (ignoreSet.has(header)) return;
			if (!enable_slurm_id_if_exists && header === "OO_Info_SLURM_JOB_ID") 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]));
			}
		});

		// Erzeuge UI für Checkboxen und Min/Max Inputs für numerische Spalten
		const controlContainerId = "parallel-plot-controls";
		let controlContainer = $("#" + controlContainerId);
		if (controlContainer.length === 0) {
			controlContainer = $('<div id="' + controlContainerId + '" style="margin-bottom:10px; display: flex;"></div>');
			$("#parallel-plot").before(controlContainer);
		} else {
			controlContainer.empty();
		}

		// Map um Checkbox-Zustände und Min/Max-Werte zu speichern
		const columnVisibility = {};
		const minMaxLimits = {};

		// Checkboxen + Min/Max Felder generieren mit Boxen, max-Breite, Umbruch und Zeilenumbruch nach jeder Box
		headers.forEach((header) => {
			try {
				if (ignoreSet.has(header)) return;
				if (!enable_slurm_id_if_exists && header === "OO_Info_SLURM_JOB_ID") return;

				const isNumerical = numericalCols.some(col => col.name === header);

				const checkboxId = `chk_${header}`;
				const minInputId = `min_${header}`;
				const maxInputId = `max_${header}`;

				columnVisibility[header] = true;
				minMaxLimits[header] = { min: null, max: null };

				// Wrapper Box mit max-Breite, Umbruch, Block-Level-Element für newline nach jeder Box
				const boxWrapper = $('<div></div>').css({
					border: "1px solid #ddd",
					borderRadius: "8px",
					padding: "12px 16px",
					marginBottom: "12px",
					boxShadow: "0 2px 6px rgba(0,0,0,0.1)",
					backgroundColor: "#fff",
					display: "flex",
					flexWrap: "wrap",
					alignItems: "center",
					gap: "15px",
					maxWidth: "350px",
					width: "100%", // damit bei kleinen Screens die Box maximal voll breit ist
					boxSizing: "border-box"
				});

				// Innerer Container mit Flexbox für Ausrichtung der Elemente, flex-grow damit Inputs genug Platz bekommen
				const container = $('<div></div>').css({
					display: "flex",
					alignItems: "center",
					gap: "10px",
					flexWrap: "wrap",
					flexGrow: 1,
					minWidth: "0" // wichtig für flexbox Overflow Handling
				});

				// Checkbox mit Label
				const checkbox = $(`<input type="checkbox" id="${checkboxId}" checked />`);
				const label = $(`<label for="${checkboxId}" style="font-weight: 600; min-width: 140px; cursor: pointer; white-space: nowrap;">${header}</label>`);

				container.append(checkbox).append(label);

				if (isNumerical) {
					// Werte ermitteln (nur gültige Zahlen)
					const numericValues = dataArray
						.map(row => parseFloat(row[headers.indexOf(header)]))
						.filter(val => !isNaN(val));

					const minVal = numericValues.length > 0 ? Math.min(...numericValues) : 0;
					const maxVal = numericValues.length > 0 ? Math.max(...numericValues) : 100;

					// Min Input mit Label
					const minWrapper = $('<div></div>').css({
						display: "flex",
						flexDirection: "column",
						alignItems: "flex-start",
						minWidth: "90px"
					});
					const minLabel = $('<label></label>').attr("for", minInputId).text("Min").css({
						fontSize: "0.75rem",
						color: "#555",
						marginBottom: "2px"
					});
					const minInput = $(`<input type="number" id="${minInputId}" placeholder="min" />`).css({
						width: "80px",
						padding: "5px 8px",
						borderRadius: "5px",
						border: "1px solid #ccc",
						boxShadow: "inset 0 1px 3px rgba(0,0,0,0.1)",
						transition: "border-color 0.3s ease"
					});
					minInput.attr("min", minVal);
					minInput.attr("max", maxVal);

					minInput.on("focus", function () {
						$(this).css("border-color", "#007BFF");
					});
					minInput.on("blur", function () {
						$(this).css("border-color", "#ccc");
					});

					minWrapper.append(minLabel).append(minInput);

					// Max Input mit Label
					const maxWrapper = $('<div></div>').css({
						display: "flex",
						flexDirection: "column",
						alignItems: "flex-start",
						minWidth: "90px"
					});
					const maxLabel = $('<label></label>').attr("for", maxInputId).text("Max").css({
						fontSize: "0.75rem",
						color: "#555",
						marginBottom: "2px"
					});
					const maxInput = $(`<input type="number" id="${maxInputId}" placeholder="max" />`).css({
						width: "80px",
						padding: "5px 8px",
						borderRadius: "5px",
						border: "1px solid #ccc",
						boxShadow: "inset 0 1px 3px rgba(0,0,0,0.1)",
						transition: "border-color 0.3s ease"
					});
					maxInput.attr("min", minVal);
					maxInput.attr("max", maxVal);

					maxInput.on("focus", function () {
						$(this).css("border-color", "#007BFF");
					});
					maxInput.on("blur", function () {
						$(this).css("border-color", "#ccc");
					});

					maxWrapper.append(maxLabel).append(maxInput);

					// Events für min/max Eingaben
					minInput.on("input", function () {
						const val = parseFloat($(this).val());
						minMaxLimits[header].min = isNaN(val) ? null : val;
						updatePlot();
					});

					maxInput.on("input", function () {
						const val = parseFloat($(this).val());
						minMaxLimits[header].max = isNaN(val) ? null : val;
						updatePlot();
					});

					container.append(minWrapper).append(maxWrapper);
				}

				// Checkbox Change Event
				checkbox.on("change", function () {
					columnVisibility[header] = $(this).is(":checked");
					updatePlot();
				});

				boxWrapper.append(container);

				// Jede Box bekommt ihren eigenen Block (also newline)
				controlContainer.append(boxWrapper);
			} catch (error) {
				console.error(`Fehler bei Header '${header}':`, error);
			}
		});



		// Erzeuge Ergebnis-Auswahl für Farbskala (color by result)
		const resultSelectId = "result-select";
		let resultSelect = $(`#${resultSelectId}`);
		if (resultSelect.length === 0) {
			resultSelect = $(`<select id="${resultSelectId}"></select>`);
			controlContainer.before(resultSelect);
		} else {
			resultSelect.empty();
		}

		resultSelect.append('<option value="none">No color</option>');

		for (let i = 0; i < resultNames.length; i++) {
			let minMaxInfo = "min [auto]";
			if (typeof result_min_max !== "undefined" && result_min_max[i] !== undefined) {
				minMaxInfo = result_min_max[i];
			}
			resultSelect.append(`<option value="${resultNames[i]}">${resultNames[i]} (${minMaxInfo})</option>`);
		}

		let colorValues = null;
		let colorScale = null;

		resultSelect.off("change").on("change", function () {
			const selectedResult = $(this).val();
			if (selectedResult === "none") {
				colorValues = null;
				colorScale = null;
			} else {
				const col = numericalCols.find(c => c.name.toLowerCase() === selectedResult.toLowerCase());
				if (!col) {
					colorValues = null;
					colorScale = null;
					updatePlot();
					return;
				}
				colorValues = dataArray.map(row => parseFloat(row[col.index]));

				let invertColor = false;
				if (typeof result_min_max !== "undefined") {
					const idx = resultNames.indexOf(selectedResult);
					if (idx !== -1) {
						invertColor = result_min_max[idx] === "max";
					}
				}

				colorScale = invertColor
					? [[0, 'red'], [1, 'green']]
					: [[0, 'green'], [1, 'red']];
			}
			updatePlot();
		});

		// Initial Auswahl: kein Farbwert, oder erstes Ergebnis falls nur eins
		if (resultNames.length === 1) {
			resultSelect.val(resultNames[0]).trigger("change");
		} else {
			resultSelect.val("none").trigger("change");
		}

		function updatePlot() {
			try {
				// Filter Spalten nach Checkboxen
				const filteredNumericalCols = numericalCols.filter(col => columnVisibility[col.name]);
				const filteredCategoricalCols = categoricalCols.filter(col => columnVisibility[col.name]);

				// Filtere die Datenzeilen, um nur die zu behalten, die innerhalb aller gesetzten Min/Max Limits liegen
				const filteredData = dataArray.filter(row => {
					for (let col of filteredNumericalCols) {
						const val = parseFloat(row[col.index]);
						if (isNaN(val)) return false; // ungültiger Wert raus

						const limits = minMaxLimits[col.name];
						if (limits.min !== null && val < limits.min) return false;
						if (limits.max !== null && val > limits.max) return false;
					}
					// Kategorische Werte ignorieren Filter (könntest hier evtl. erweitern)
					return true;
				});

				const dimensions = [];

				// Füge numerische Dimensionen hinzu mit Min/Max Limits (Range anhand gefilterter Daten)
				filteredNumericalCols.forEach(col => {
					let vals = filteredData.map(row => parseFloat(row[col.index]));

					// Fallback falls alle Werte NaN (sollte eigentlich nicht vorkommen)
					const realMin = vals.length > 0 ? Math.min(...vals) : 0;
					const realMax = vals.length > 0 ? Math.max(...vals) : 100;

					dimensions.push({
						label: col.name,
						values: vals,
						range: [realMin, realMax]
					});
				});

				// Kategorische Dimensionen (aus gefilterten Daten)
				filteredCategoricalCols.forEach(col => {
					const vals = filteredData.map(row => categoryMappings[col.name][row[col.index]]);
					dimensions.push({
						label: col.name,
						values: vals,
						tickvals: Object.values(categoryMappings[col.name]),
						ticktext: Object.keys(categoryMappings[col.name])
					});
				});

				// Linienfarbe bestimmen, falls Farbskala gesetzt ist
				let filteredColorValues = null;
				if (colorValues) {
					// Da colorValues für alle Daten sind, filtere sie auch entsprechend
					filteredColorValues = filteredData.map(row => {
						const col = numericalCols.find(c => c.name.toLowerCase() === resultSelect.val().toLowerCase());
						return col ? parseFloat(row[col.index]) : null;
					});
				}

				const trace = {
					type: 'parcoords',
					dimensions: dimensions,
					line: filteredColorValues ? { color: filteredColorValues, 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();
			} catch (error) {
				console.error("Fehler in updatePlot():", error);
			}
		}


		updatePlot();

		$("#parallel-plot").data("loaded", "true");

		make_text_in_parallel_plot_nicer();

	} catch (err) {
		console.error("Error in createParallelPlot:", err);
	}
}

function plotWorkerUsage() {
	if($("#workerUsagePlot").data("loaded") == "true") {
		return;
	}
	var data = tab_worker_usage_csv_json;
	if (!Array.isArray(data) || data.length === 0) {
		console.error("Invalid or empty data provided.");
		return;
	}

	let timestamps = [];
	let desiredWorkers = [];
	let realWorkers = [];

	for (let i = 0; i < data.length; i++) {
		let entry = data[i];

		if (!Array.isArray(entry) || entry.length < 3) {
			console.warn("Skipping invalid entry:", entry);
			continue;
		}

		let unixTime = parseFloat(entry[0]);
		let desired = parseInt(entry[1], 10);
		let real = parseInt(entry[2], 10);

		if (isNaN(unixTime) || isNaN(desired) || isNaN(real)) {
			console.warn("Skipping invalid numerical values:", entry);
			continue;
		}

		timestamps.push(new Date(unixTime * 1000).toISOString());
		desiredWorkers.push(desired);
		realWorkers.push(real);
	}

	let trace1 = {
		x: timestamps,
		y: desiredWorkers,
		mode: 'lines+markers',
		name: 'Desired Workers',
		line: {
			color: 'blue'
		}
	};

	let trace2 = {
		x: timestamps,
		y: realWorkers,
		mode: 'lines+markers',
		name: 'Real Workers',
		line: {
			color: 'red'
		}
	};

	let layout = {
		title: "Worker Usage Over Time",
		xaxis: {
			title: get_axis_title_data("Time", "date")
		},
		yaxis: {
			title: get_axis_title_data("Number of Workers")
		},
		legend: {
			x: 0,
			y: 1
		}
	};

	Plotly.newPlot('workerUsagePlot', [trace1, trace2], add_default_layout_data(layout));
	$("#workerUsagePlot").data("loaded", "true");
}

function plotCPUAndRAMUsage() {
	if($("#mainWorkerCPURAM").data("loaded") == "true") {
		return;
	}
	var timestamps = tab_main_worker_cpu_ram_csv_json.map(row => new Date(row[0] * 1000));
	var ramUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[1]);
	var cpuUsage = tab_main_worker_cpu_ram_csv_json.map(row => row[2]);

	var trace1 = {
		x: timestamps,
		y: cpuUsage,
		mode: 'lines+markers',
		marker: {
			size: get_marker_size(),
		},
		name: 'CPU Usage (%)',
		type: 'scatter',
		yaxis: 'y1'
	};

	var trace2 = {
		x: timestamps,
		y: ramUsage,
		mode: 'lines+markers',
		marker: {
			size: get_marker_size(),
		},
		name: 'RAM Usage (MB)',
		type: 'scatter',
		yaxis: 'y2'
	};

	var layout = {
		title: 'CPU and RAM Usage Over Time',
		xaxis: {
			title: get_axis_title_data("Timestamp", "date"),
			tickmode: 'array',
			tickvals: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0),
			ticktext: timestamps.filter((_, index) => index % Math.max(Math.floor(timestamps.length / 10), 1) === 0).map(t => t.toLocaleString()),
			tickangle: -45
		},
		yaxis: {
			title: get_axis_title_data("CPU Usage (%)"),
			rangemode: 'tozero'
		},
		yaxis2: {
			title: get_axis_title_data("RAM Usage (MB)"),
			overlaying: 'y',
			side: 'right',
			rangemode: 'tozero'
		},
		legend: {
			x: 0.1,
			y: 0.9
		}
	};

	var data = [trace1, trace2];
	Plotly.newPlot('mainWorkerCPURAM', data, add_default_layout_data(layout));
	$("#mainWorkerCPURAM").data("loaded", "true");
}

function plotScatter2d() {
	if ($("#plotScatter2d").data("loaded") == "true") {
		return;
	}

	var plotDiv = document.getElementById("plotScatter2d");

	var minInput = document.getElementById("minValue");
	var maxInput = document.getElementById("maxValue");

	if (!minInput || !maxInput) {
		minInput = document.createElement("input");
		minInput.id = "minValue";
		minInput.type = "number";
		minInput.placeholder = "Min Value";
		minInput.step = "any";

		maxInput = document.createElement("input");
		maxInput.id = "maxValue";
		maxInput.type = "number";
		maxInput.placeholder = "Max Value";
		maxInput.step = "any";

		var inputContainer = document.createElement("div");
		inputContainer.style.marginBottom = "10px";
		inputContainer.appendChild(minInput);
		inputContainer.appendChild(maxInput);
		plotDiv.appendChild(inputContainer);
	}

	var resultSelect = document.getElementById("resultSelect");
	if (result_names.length > 1 && !resultSelect) {
		resultSelect = document.createElement("select");
		resultSelect.id = "resultSelect";
		resultSelect.style.marginBottom = "10px";

		var sortedResults = [...result_names].sort();
		sortedResults.forEach(result => {
			var option = document.createElement("option");
			option.value = result;
			option.textContent = result;
			resultSelect.appendChild(option);
		});

		var selectContainer = document.createElement("div");
		selectContainer.style.marginBottom = "10px";
		selectContainer.appendChild(resultSelect);
		plotDiv.appendChild(selectContainer);
	}

	minInput.addEventListener("input", updatePlots);
	maxInput.addEventListener("input", updatePlots);
	if (resultSelect) {
		resultSelect.addEventListener("change", updatePlots);
	}

	updatePlots();

	async function updatePlots() {
		var minValue = parseFloat(minInput.value);
		var maxValue = parseFloat(maxInput.value);
		if (isNaN(minValue)) minValue = -Infinity;
		if (isNaN(maxValue)) maxValue = Infinity;

		while (plotDiv.children.length > 2) {
			plotDiv.removeChild(plotDiv.lastChild);
		}

		var selectedResult = resultSelect ? resultSelect.value : result_names[0];

		var resultIndex = tab_results_headers_json.findIndex(header =>
			header.toLowerCase() === selectedResult.toLowerCase()
		);
		var resultValues = tab_results_csv_json.map(row => row[resultIndex]);

		var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
		var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));

		if (minValue !== -Infinity) minResult = Math.max(minResult, minValue);
		if (maxValue !== Infinity) maxResult = Math.min(maxResult, maxValue);

		var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";

		var numericColumns = tab_results_headers_json.filter(col =>
			!special_col_names.includes(col) && !result_names.includes(col) &&
			!col.startsWith("OO_Info") &&
			tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
		);

		if (numericColumns.length < 2) {
			console.error("Not enough columns for Scatter-Plots");
			return;
		}

		for (let i = 0; i < numericColumns.length; i++) {
			for (let j = i + 1; j < numericColumns.length; j++) {
				let xCol = numericColumns[i];
				let yCol = numericColumns[j];

				let xIndex = tab_results_headers_json.indexOf(xCol);
				let yIndex = tab_results_headers_json.indexOf(yCol);

				let data = tab_results_csv_json.map(row => ({
					x: parseFloat(row[xIndex]),
					y: parseFloat(row[yIndex]),
					result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
				}));

				data = data.filter(d => d.result >= minResult && d.result <= maxResult);

				let layoutTitle = `${xCol} (x) vs ${yCol} (y), result: ${selectedResult}`;
				let layout = {
					title: layoutTitle,
					xaxis: {
						title: get_axis_title_data(xCol)
					},
					yaxis: {
						title: get_axis_title_data(yCol)
					},
					showlegend: false
				};
				let subDiv = document.createElement("div");

				let spinnerContainer = document.createElement("div");
				spinnerContainer.style.display = "flex";
				spinnerContainer.style.alignItems = "center";
				spinnerContainer.style.justifyContent = "center";
				spinnerContainer.style.width = layout.width + "px";
				spinnerContainer.style.height = layout.height + "px";
				spinnerContainer.style.position = "relative";

				let spinner = document.createElement("div");
				spinner.className = "spinner";
				spinner.style.width = "40px";
				spinner.style.height = "40px";

				let loadingText = document.createElement("span");
				loadingText.innerText = `Loading ${layoutTitle}`;
				loadingText.style.marginLeft = "10px";

				spinnerContainer.appendChild(spinner);
				spinnerContainer.appendChild(loadingText);

				plotDiv.appendChild(spinnerContainer);

				await new Promise(resolve => setTimeout(resolve, 50));

				let colors = data.map(d => {
					if (d.result === null) {
						return 'rgb(0, 0, 0)';
					} else {
						let norm = (d.result - minResult) / (maxResult - minResult);
						if (invertColor) {
							norm = 1 - norm;
						}
						return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
					}
				});

				let trace = {
					x: data.map(d => d.x),
					y: data.map(d => d.y),
					mode: 'markers',
					marker: {
						size: get_marker_size(),
						color: data.map(d => d.result !== null ? d.result : null),
						colorscale: invertColor ? [
							[0, 'red'],
							[1, 'green']
						] : [
							[0, 'green'],
							[1, 'red']
						],
						colorbar: {
							title: 'Result',
							tickvals: [minResult, maxResult],
							ticktext: [`${minResult}`, `${maxResult}`]
						},
						symbol: data.map(d => d.result === null ? 'x' : 'circle'),
					},
					text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
					type: 'scatter',
					showlegend: false
				};

				try {
					plotDiv.replaceChild(subDiv, spinnerContainer);
				} catch (err) {
					//
				}
				Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
			}
		}
	}

	$("#plotScatter2d").data("loaded", "true");
}

function plotScatter3d() {
	if ($("#plotScatter3d").data("loaded") == "true") {
		return;
	}

	var plotDiv = document.getElementById("plotScatter3d");
	if (!plotDiv) {
		console.error("Div element with id 'plotScatter3d' not found");
		return;
	}
	plotDiv.innerHTML = "";

	var minInput3d = document.getElementById("minValue3d");
	var maxInput3d = document.getElementById("maxValue3d");

	if (!minInput3d || !maxInput3d) {
		minInput3d = document.createElement("input");
		minInput3d.id = "minValue3d";
		minInput3d.type = "number";
		minInput3d.placeholder = "Min Value";
		minInput3d.step = "any";

		maxInput3d = document.createElement("input");
		maxInput3d.id = "maxValue3d";
		maxInput3d.type = "number";
		maxInput3d.placeholder = "Max Value";
		maxInput3d.step = "any";

		var inputContainer3d = document.createElement("div");
		inputContainer3d.style.marginBottom = "10px";
		inputContainer3d.appendChild(minInput3d);
		inputContainer3d.appendChild(maxInput3d);
		plotDiv.appendChild(inputContainer3d);
	}

	var select3d = document.getElementById("select3dScatter");
	if (result_names.length > 1 && !select3d) {
		if (!select3d) {
			select3d = document.createElement("select");
			select3d.id = "select3dScatter";
			select3d.style.marginBottom = "10px";
			select3d.innerHTML = result_names.map(name => `<option value="${name}">${name}</option>`).join("");

			select3d.addEventListener("change", updatePlots3d);

			plotDiv.appendChild(select3d);
		}
	}

	minInput3d.addEventListener("input", updatePlots3d);
	maxInput3d.addEventListener("input", updatePlots3d);

	updatePlots3d();

	async function updatePlots3d() {
		var selectedResult = select3d ? select3d.value : result_names[0];
		var minValue3d = parseFloat(minInput3d.value);
		var maxValue3d = parseFloat(maxInput3d.value);

		if (isNaN(minValue3d)) minValue3d = -Infinity;
		if (isNaN(maxValue3d)) maxValue3d = Infinity;

		while (plotDiv.children.length > 2) {
			plotDiv.removeChild(plotDiv.lastChild);
		}

		var resultIndex = tab_results_headers_json.findIndex(header =>
			header.toLowerCase() === selectedResult.toLowerCase()
		);
		var resultValues = tab_results_csv_json.map(row => row[resultIndex]);

		var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
		var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));

		if (minValue3d !== -Infinity) minResult = Math.max(minResult, minValue3d);
		if (maxValue3d !== Infinity) maxResult = Math.min(maxResult, maxValue3d);

		var invertColor = result_min_max[result_names.indexOf(selectedResult)] === "max";

		var numericColumns = tab_results_headers_json.filter(col =>
			!special_col_names.includes(col) && !result_names.includes(col) &&
			!col.startsWith("OO_Info") &&
			tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
		);

		if (numericColumns.length < 3) {
			console.error("Not enough columns for 3D scatter plots");
			return;
		}

		for (let i = 0; i < numericColumns.length; i++) {
			for (let j = i + 1; j < numericColumns.length; j++) {
				for (let k = j + 1; k < numericColumns.length; k++) {
					let xCol = numericColumns[i];
					let yCol = numericColumns[j];
					let zCol = numericColumns[k];

					let xIndex = tab_results_headers_json.indexOf(xCol);
					let yIndex = tab_results_headers_json.indexOf(yCol);
					let zIndex = tab_results_headers_json.indexOf(zCol);

					let data = tab_results_csv_json.map(row => ({
						x: parseFloat(row[xIndex]),
						y: parseFloat(row[yIndex]),
						z: parseFloat(row[zIndex]),
						result: row[resultIndex] !== "" ? parseFloat(row[resultIndex]) : null
					}));

					data = data.filter(d => d.result >= minResult && d.result <= maxResult);

					let layoutTitle = `${xCol} (x) vs ${yCol} (y) vs ${zCol} (z), result: ${selectedResult}`;
					let layout = {
						title: layoutTitle,
						scene: {
							xaxis: {
								title: get_axis_title_data(xCol)
							},
							yaxis: {
								title: get_axis_title_data(yCol)
							},
							zaxis: {
								title: get_axis_title_data(zCol)
							}
						},
						showlegend: false
					};

					let spinnerContainer = document.createElement("div");
					spinnerContainer.style.display = "flex";
					spinnerContainer.style.alignItems = "center";
					spinnerContainer.style.justifyContent = "center";
					spinnerContainer.style.width = layout.width + "px";
					spinnerContainer.style.height = layout.height + "px";
					spinnerContainer.style.position = "relative";

					let spinner = document.createElement("div");
					spinner.className = "spinner";
					spinner.style.width = "40px";
					spinner.style.height = "40px";

					let loadingText = document.createElement("span");
					loadingText.innerText = `Loading ${layoutTitle}`;
					loadingText.style.marginLeft = "10px";

					spinnerContainer.appendChild(spinner);
					spinnerContainer.appendChild(loadingText);

					plotDiv.appendChild(spinnerContainer);

					await new Promise(resolve => setTimeout(resolve, 50));

					let colors = data.map(d => {
						if (d.result === null) {
							return 'rgb(0, 0, 0)';
						} else {
							let norm = (d.result - minResult) / (maxResult - minResult);
							if (invertColor) {
								norm = 1 - norm;
							}
							return `rgb(${Math.round(255 * norm)}, ${Math.round(255 * (1 - norm))}, 0)`;
						}
					});

					let trace = {
						x: data.map(d => d.x),
						y: data.map(d => d.y),
						z: data.map(d => d.z),
						mode: 'markers',
						marker: {
							size: get_marker_size(),
							color: data.map(d => d.result !== null ? d.result : null),
							colorscale: invertColor ? [
								[0, 'red'],
								[1, 'green']
							] : [
								[0, 'green'],
								[1, 'red']
							],
							colorbar: {
								title: 'Result',
								tickvals: [minResult, maxResult],
								ticktext: [`${minResult}`, `${maxResult}`]
							},
						},
						text: data.map(d => d.result !== null ? `Result: ${d.result}` : 'No result'),
						type: 'scatter3d',
						showlegend: false
					};

					let subDiv = document.createElement("div");
					try {
						plotDiv.replaceChild(subDiv, spinnerContainer);
					} catch (err) {
						//
					}
					Plotly.newPlot(subDiv, [trace], add_default_layout_data(layout));
				}
			}
		}
	}

	$("#plotScatter3d").data("loaded", "true");
}

async function plot_worker_cpu_ram() {
	if($("#worker_cpu_ram_pre").data("loaded") == "true") {
		return;
	}

	const logData = $("#worker_cpu_ram_pre").text();
	const regex = /^Unix-Timestamp: (\d+), Hostname: ([\w-]+), CPU: ([\d.]+)%, RAM: ([\d.]+) MB \/ ([\d.]+) MB$/;

	const hostData = {};

	logData.split("\n").forEach(line => {
		line = line.trim();
		const match = line.match(regex);
		if (match) {
			const timestamp = new Date(parseInt(match[1]) * 1000);
			const hostname = match[2];
			const cpu = parseFloat(match[3]);
			const ram = parseFloat(match[4]);

			if (!hostData[hostname]) {
				hostData[hostname] = { timestamps: [], cpuUsage: [], ramUsage: [] };
			}

			hostData[hostname].timestamps.push(timestamp);
			hostData[hostname].cpuUsage.push(cpu);
			hostData[hostname].ramUsage.push(ram);
		}
	});

	if (!Object.keys(hostData).length) {
		console.log("No valid data found");
		return;
	}

	const container = document.getElementById("cpuRamWorkerChartContainer");
	container.innerHTML = "";

	var i = 1;

	Object.entries(hostData).forEach(([hostname, { timestamps, cpuUsage, ramUsage }], index) => {
		const chartId = `workerChart_${index}`;
		const chartDiv = document.createElement("div");
		chartDiv.id = chartId;
		chartDiv.style.marginBottom = "40px";
		container.appendChild(chartDiv);

		const cpuTrace = {
			x: timestamps,
			y: cpuUsage,
			mode: "lines+markers",
			name: "CPU Usage (%)",
			yaxis: "y1",
			line: {
				color: "red"
			}
		};

		const ramTrace = {
			x: timestamps,
			y: ramUsage,
			mode: "lines+markers",
			name: "RAM Usage (MB)",
			yaxis: "y2",
			line: {
				color: "blue"
			}
		};

		const layout = {
			title: `Worker CPU and RAM Usage - ${hostname}`,
			xaxis: {
				title: get_axis_title_data("Timestamp", "date")
			},
			yaxis: {
				title: get_axis_title_data("CPU Usage (%)"),
				side: "left",
				color: "red"
			},
			yaxis2: {
				title: get_axis_title_data("RAM Usage (MB)"),
				side: "right",
				overlaying: "y",
				color: "blue"
			},
			showlegend: true
		};

		Plotly.newPlot(chartId, [cpuTrace, ramTrace], add_default_layout_data(layout));
		i++;
	});

	$("#plot_worker_cpu_ram_button").remove();
	$("#worker_cpu_ram_pre").data("loaded", "true");
}

function load_log_file(log_nr, filename) {
	var pre_id = `single_run_${log_nr}_pre`;

	if (!$("#" + pre_id).data("loaded")) {
		const params = new URLSearchParams(window.location.search);

		const user_id = params.get('user_id');
		const experiment_name = params.get('experiment_name');
		const run_nr = params.get('run_nr');

		var url = `get_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}&filename=${filename}`;

		fetch(url)
			.then(response => response.json())
			.then(data => {
				if (data.data) {
					$("#" + pre_id).html(data.data);
					$("#" + pre_id).data("loaded", true);
				} else {
					log(`No 'data' key found in response.`);
				}

				$("#spinner_log_" + log_nr).remove();
			})
			.catch(error => {
				log(`Error loading log: ${error}`);
				$("#spinner_log_" + log_nr).remove();
			});
	}
}

function load_debug_log () {
	var pre_id = `here_debuglogs_go`;

	if (!$("#" + pre_id).data("loaded")) {
		const params = new URLSearchParams(window.location.search);

		const user_id = params.get('user_id');
		const experiment_name = params.get('experiment_name');
		const run_nr = params.get('run_nr');

		var url = `get_debug_log?user_id=${user_id}&experiment_name=${experiment_name}&run_nr=${run_nr}`;

		fetch(url)
			.then(response => response.json())
			.then(data => {
				$("#debug_log_spinner").remove();

				if (data.data) {
					try {
						$("#" + pre_id).html(data.data);
					} catch (err) {
						$("#" + pre_id).text(`Error loading data: ${err}`);
					}

					$("#" + pre_id).data("loaded", true);

					if (typeof apply_theme_based_on_system_preferences === 'function') {
						apply_theme_based_on_system_preferences();
					}
				} else {
					log(`No 'data' key found in response.`);
				}
			})
			.catch(error => {
				log(`Error loading log: ${error}`);
				$("#debug_log_spinner").remove();
			});
	}
}

function plotBoxplot() {
	if ($("#plotBoxplot").data("loaded") == "true") {
		return;
	}
	var numericColumns = tab_results_headers_json.filter(col =>
		!special_col_names.includes(col) && !result_names.includes(col) &&
		!col.startsWith("OO_Info") &&
		tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
	);

	if (numericColumns.length < 1) {
		console.error("Not enough numeric columns for Boxplot");
		return;
	}

	var resultIndex = tab_results_headers_json.findIndex(function(header) {
		return result_names.includes(header.toLowerCase());
	});
	var resultValues = tab_results_csv_json.map(row => row[resultIndex]);
	var minResult = Math.min(...resultValues.filter(value => value !== null && value !== ""));
	var maxResult = Math.max(...resultValues.filter(value => value !== null && value !== ""));

	var plotDiv = document.getElementById("plotBoxplot");
	plotDiv.innerHTML = "";

	let traces = numericColumns.map(col => {
		let index = tab_results_headers_json.indexOf(col);
		let data = tab_results_csv_json.map(row => parseFloat(row[index]));

		return {
			y: data,
			type: 'box',
			name: col,
			boxmean: 'sd',
			marker: {
				color: 'rgb(0, 255, 0)'
			},
		};
	});

	let layout = {
		title: 'Boxplot of Numerical Columns',
		xaxis: {
			title: get_axis_title_data("Columns")
		},
		yaxis: {
			title: get_axis_title_data("Value")
		},
		showlegend: false
	};

	Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
	$("#plotBoxplot").data("loaded", "true");
}

function plotHeatmap() {
	if ($("#plotHeatmap").data("loaded") === "true") {
		return;
	}

	var numericColumns = tab_results_headers_json.filter(col => {
		if (special_col_names.includes(col) || result_names.includes(col)) {
			return false;
		}
		if (!col.startsWith("OO_Info")) {
			return true;
		}
		let index = tab_results_headers_json.indexOf(col);
		return tab_results_csv_json.every(row => {
			let value = parseFloat(row[index]);
			return !isNaN(value) && isFinite(value);
		});
	});

	if (numericColumns.length < 2) {
		console.error("Not enough valid numeric columns for Heatmap");
		return;
	}

	var columnData = numericColumns.map(col => {
		let index = tab_results_headers_json.indexOf(col);
		return tab_results_csv_json.map(row => parseFloat(row[index]));
	});

	var dataMatrix = numericColumns.map((_, i) =>
		numericColumns.map((_, j) => {
			let values = columnData[i].map((val, index) => (val + columnData[j][index]) / 2);
			return values.reduce((a, b) => a + b, 0) / values.length;
		})
	);

	var trace = {
		z: dataMatrix,
		x: numericColumns,
		y: numericColumns,
		colorscale: 'Viridis',
		type: 'heatmap'
	};

	var layout = {
		xaxis: {
			title: get_axis_title_data("Columns")
		},
		yaxis: {
			title: get_axis_title_data("Columns")
		},
		showlegend: false
	};

	var plotDiv = document.getElementById("plotHeatmap");
	plotDiv.innerHTML = "";

	Plotly.newPlot(plotDiv, [trace], add_default_layout_data(layout));
	$("#plotHeatmap").data("loaded", "true");
}

function plotHistogram() {
	if ($("#plotHistogram").data("loaded") == "true") {
		return;
	}

	var numericColumns = tab_results_headers_json.filter(col =>
		!special_col_names.includes(col) && !result_names.includes(col) &&
		!col.startsWith("OO_Info") &&
		tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
	);

	if (numericColumns.length < 1) {
		console.error("Not enough columns for Histogram");
		return;
	}

	var plotDiv = document.getElementById("plotHistogram");
	plotDiv.innerHTML = "";

	const colorPalette = ['#ff9999', '#66b3ff', '#99ff99', '#ffcc99', '#c2c2f0', '#ffb3e6'];

	let traces = numericColumns.map((col, index) => {
		let data = tab_results_csv_json.map(row => parseFloat(row[tab_results_headers_json.indexOf(col)]));

		return {
			x: data,
			type: 'histogram',
			name: col,
			opacity: 0.7,
			marker: {
				color: colorPalette[index % colorPalette.length]
			},
			autobinx: true
		};
	});

	let layout = {
		title: 'Histogram of Numerical Columns',
		xaxis: {
			title: get_axis_title_data("Value")
		},
		yaxis: {
			title: get_axis_title_data("Frequency")
		},
		showlegend: true,
		barmode: 'overlay'
	};

	Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
	$("#plotHistogram").data("loaded", "true");
}

function plotViolin() {
	if ($("#plotViolin").data("loaded") == "true") {
		return;
	}
	var numericColumns = tab_results_headers_json.filter(col =>
		!special_col_names.includes(col) && !result_names.includes(col) &&
		!col.startsWith("OO_Info") &&
		tab_results_csv_json.every(row => !isNaN(parseFloat(row[tab_results_headers_json.indexOf(col)])))
	);

	if (numericColumns.length < 1) {
		console.error("Not enough columns for Violin Plot");
		return;
	}

	var plotDiv = document.getElementById("plotViolin");
	plotDiv.innerHTML = "";

	let traces = numericColumns.map(col => {
		let index = tab_results_headers_json.indexOf(col);
		let data = tab_results_csv_json.map(row => parseFloat(row[index]));

		return {
			y: data,
			type: 'violin',
			name: col,
			box: {
				visible: true
			},
			line: {
				color: 'rgb(0, 255, 0)'
			},
			marker: {
				color: 'rgb(0, 255, 0)'
			},
			meanline: {
				visible: true
			},
		};
	});

	let layout = {
		title: 'Violin Plot of Numerical Columns',
		yaxis: {
			title: get_axis_title_data("Value")
		},
		xaxis: {
			title: get_axis_title_data("Columns")
		},
		showlegend: false
	};

	Plotly.newPlot(plotDiv, traces, add_default_layout_data(layout));
	$("#plotViolin").data("loaded", "true");
}

function plotExitCodesPieChart() {
	if ($("#plotExitCodesPieChart").data("loaded") == "true") {
		return;
	}

	var exitCodes = tab_results_csv_json.map(row => row[tab_results_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("CANDIDATE") ? "lightblue" :
			el.textContent.includes("ABANDONED") ? "yellow" : "";
		if (color) el.style.backgroundColor = color;
		el.classList.add("invert_in_dark_mode");
	});
}

function _colorize_table_entries_by_queue_time() {
	let cells = [...document.querySelectorAll('[data-column-id="queue_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_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_queue_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();
	if (typeof apply_theme_based_on_system_preferences === 'function') {
		apply_theme_based_on_system_preferences();
	}
}

function plotTimelineFromGlobals() {
	if (
		typeof tab_results_headers_json === "undefined" ||
		typeof tab_results_csv_json === "undefined" ||
		!Array.isArray(tab_results_headers_json) ||
		!Array.isArray(tab_results_csv_json)
	) {
		console.warn("Global variables 'tab_results_headers_json' or 'tab_results_csv_json' missing or invalid.");
		return null;
	}

	const headers = tab_results_headers_json;
	const data = tab_results_csv_json;

	const col = name => headers.indexOf(name);
	const ix_trial_index = col("trial_index");
	const ix_start_time = col("start_time");
	const ix_end_time = col("end_time");
	const ix_status = col("trial_status");

	if ([ix_trial_index, ix_start_time, ix_end_time, ix_status].some(ix => ix === -1)) {
		console.warn("One or more needed columns missing");
		return null;
	}

	const traces = [];

	// Add dummy traces for legend
	traces.push({
		type: "scatter",
		mode: "lines",
		x: [null, null],
		y: [null, null],
		line: { color: "green", width: 4 },
		name: "COMPLETED",
		showlegend: true,
		hoverinfo: "none"
	});
	traces.push({
		type: "scatter",
		mode: "lines",
		x: [null, null],
		y: [null, null],
		line: { color: "yellow", width: 4 },
		name: "RUNNING",
		showlegend: true,
		hoverinfo: "none"
	});
	traces.push({
		type: "scatter",
		mode: "lines",
		x: [null, null],
		y: [null, null],
		line: { color: "red", width: 4 },
		name: "FAILED/OTHER",
		showlegend: true,
		hoverinfo: "none"
	});

	for (const row of data) {
		const trial_index = row[ix_trial_index];
		const start = row[ix_start_time];
		const end = row[ix_end_time];
		const status = row[ix_status];

		if (
			trial_index === "" || start === "" || end === "" ||
			isNaN(start) || isNaN(end)
		) continue;

		let color = "red"; // default
		if (status === "COMPLETED") color = "green";
		else if (status === "RUNNING") color = "yellow";

		traces.push({
			type: "scatter",
			mode: "lines",
			x: [new Date(start * 1000), new Date(end * 1000)],
			y: [trial_index, trial_index],
			line: { color: color, width: 4 },
			name: `Trial ${trial_index} (${status})`,
			showlegend: false,
			hoverinfo: "x+y+name"
		});
	}

	if (traces.length <= 3) { // only dummy traces added
		console.warn("No valid data for plotting found.");
		return null;
	}

	const layout = {
		title: "Trial Timeline",
		xaxis: {
			title: "Time",
			type: "date"
		},
		yaxis: {
			title: "Trial Index",
			autorange: "reversed"
		},
		margin: { t: 50 }
	};

	Plotly.newPlot('plot_timeline', traces, add_default_layout_data(layout));
	return true;
}

function createResultParameterCanvases(this_res_name) {
	if (
		typeof special_col_names === "undefined" ||
		typeof result_names === "undefined" ||
		typeof result_min_max === "undefined" ||
		typeof tab_results_headers_json === "undefined" ||
		typeof tab_results_csv_json === "undefined"
	) {
		console.error("Missing one or more required global variables.");
		return null;
	}

	if (
		!Array.isArray(special_col_names) ||
		!Array.isArray(result_names) ||
		!Array.isArray(result_min_max) ||
		!Array.isArray(tab_results_headers_json) ||
		!Array.isArray(tab_results_csv_json)
	) {
		console.error("All inputs must be arrays.");
		return null;
	}

	function getColumnIndexMap(headers) {
		var map = {};
		for (var i = 0; i < headers.length; i++) {
			map[headers[i]] = i;
		}
		return map;
	}

	function getColumnData(data, index) {
		var result = [];
		for (var i = 0; i < data.length; i++) {
			result.push(data[i][index]);
		}
		return result;
	}

	function normalize(value, min, max) {
		if (max === min) {
			return 0.5;
		}
		return (value - min) / (max - min);
	}

	function interpolateColor(ratio, reverse) {
		var r = reverse ? ratio : 1 - ratio;
		var g = reverse ? 1 - ratio : ratio;
		var b = 0;
		r = Math.floor(r * 255);
		g = Math.floor(g * 255);
		return "rgb(" + r + "," + g + "," + b + ")";
	}

	function createCanvas(width, height) {
		var canvas = document.createElement("canvas");
		canvas.width = width;
		canvas.height = height;
		return canvas;
	}

	function isNumericArray(arr) {
		for (var i = 0; i < arr.length; i++) {
			var val = arr[i];
			if (typeof val !== "number" || isNaN(val)) {
				return false;
			}
		}
		return true;
	}

	function findBestRowIndex() {
		var bestIndex = 0;

		for (var i = 1; i < tab_results_csv_json.length; i++) {
			var better = false;

			for (var r = 0; r < result_names.length; r++) {
				var col = result_names[r];
				var colIdx = header_map[col];
				var goal = result_min_max[r]; // "min" or "max"

				var valCurrent = tab_results_csv_json[i][colIdx];
				var valBest = tab_results_csv_json[bestIndex][colIdx];

				if (goal === "min" && valCurrent < valBest) {
					better = true;
					break;
				}

				if (goal === "max" && valCurrent > valBest) {
					better = true;
					break;
				}
			}

			if (better) {
				bestIndex = i;
			}
		}

		return bestIndex;
	}

	var canvas_width = 1000;
	var canvas_height = 100;

	var header_map = getColumnIndexMap(tab_results_headers_json);

	var parameter_columns = tab_results_headers_json.filter(function (name) {
		return (
			!special_col_names.includes(name) &&
			!result_names.includes(name) &&
			!name.startsWith("OO_Info_")
		);
	});

	var container = document.createElement("div");

	for (var r = 0; r < result_names.length; r++) {
		var result_name = result_names[r];
		if (this_res_name == result_name) {
			var result_index = header_map[result_name];
			var result_goal = result_min_max[r]; // "min" or "max"

			var result_values = getColumnData(tab_results_csv_json, result_index);
			var result_min = Math.min.apply(null, result_values);
			var result_max = Math.max.apply(null, result_values);

			var heading = document.createElement("h2");
			heading.textContent = "Interpretation for result: " + result_name + " (goal: " + result_goal + ")";
			heading.style.fontFamily = "sans-serif";
			heading.style.marginTop = "24px";
			heading.style.marginBottom = "12px";
			container.appendChild(heading);

			var table = document.createElement("table");
			table.style.borderCollapse = "collapse";
			table.style.marginBottom = "32px";

			var thead = document.createElement("thead");
			var headRow = document.createElement("tr");

			var th1 = document.createElement("th");
			th1.textContent = "Parameter";
			th1.style.textAlign = "left";
			th1.style.padding = "6px 12px";
			var th2 = document.createElement("th");
			th2.textContent = "Distribution of result";
			th2.style.textAlign = "left";
			th2.style.padding = "6px 12px";

			headRow.appendChild(th1);
			headRow.appendChild(th2);
			thead.appendChild(headRow);
			table.appendChild(thead);

			var tbody = document.createElement("tbody");

			for (var p = 0; p < parameter_columns.length; p++) {
				var param_name = parameter_columns[p];
				var param_index = header_map[param_name];
				var param_values = getColumnData(tab_results_csv_json, param_index);

				if (!isNumericArray(param_values)) {
					continue;
				}

				var param_min = Math.min.apply(null, param_values);
				var param_max = Math.max.apply(null, param_values);

				var canvas = createCanvas(canvas_width, canvas_height);

				canvas.classList.add("invert_in_dark_mode");

				var ctx = canvas.getContext("2d");

				ctx.fillStyle = "white";
				ctx.fillRect(0, 0, canvas.width, canvas.height);

				var x_groups = {};

				for (var i = 0; i < tab_results_csv_json.length; i++) {
					var raw_param = tab_results_csv_json[i][param_index];
					var raw_result = tab_results_csv_json[i][result_index];

					var x_ratio = normalize(raw_param, param_min, param_max);
					var x = Math.floor(x_ratio * (canvas_width - 1));

					if (!x_groups[x]) {
						x_groups[x] = [];
					}

					x_groups[x].push(raw_result);
				}

				for (var x in x_groups) {
					var values = x_groups[x];
					values.sort(function (a, b) {
						return a - b;
					});

					var stripe_height = canvas_height / values.length;
					for (var i = 0; i < values.length; i++) {
						var y_start = i * stripe_height;
						var y_end = (i + 1) * stripe_height;

						var value = values[i];
						var result_ratio = normalize(value, result_min, result_max);
						var color = interpolateColor(result_ratio, result_goal === "min");

						ctx.beginPath();
						ctx.strokeStyle = color;
						ctx.lineWidth = 1;
						ctx.moveTo(Number(x) + 0.5, y_start);
						ctx.lineTo(Number(x) + 0.5, y_end);
						ctx.stroke();
					}
				}

				var row = document.createElement("tr");

				var cell_param = document.createElement("td");
				cell_param.textContent = param_name;
				cell_param.style.padding = "4px 12px";
				cell_param.style.verticalAlign = "top";
				cell_param.style.fontFamily = "monospace";
				cell_param.style.whiteSpace = "nowrap";

				var cell_canvas = document.createElement("td");
				cell_canvas.appendChild(canvas);
				cell_canvas.style.padding = "4px 12px";

				row.appendChild(cell_param);
				row.appendChild(cell_canvas);
				tbody.appendChild(row);
			}

			table.appendChild(tbody);
			container.appendChild(table);
		}
	}

	// === Summary: Best result ===
	var bestIndex = findBestRowIndex();
	var bestRow = tab_results_csv_json[bestIndex];

	var ul = document.createElement("ul");
	ul.style.margin = "0";
	ul.style.paddingLeft = "24px";

	// Alle Result-Spalten
	for (var i = 0; i < result_names.length; i++) {
		var name = result_names[i];
		var val = bestRow[header_map[name]];
		var li = document.createElement("li");
		li.textContent = name + " = " + val;
		ul.appendChild(li);
	}

	// Alle Parameter-Spalten (außer special_col_names)
	for (var i = 0; i < tab_results_headers_json.length; i++) {
		var name = tab_results_headers_json[i];
		if (special_col_names.includes(name) || name.startsWith("OO_Info_") || result_names.includes(name)) {
			continue;
		}

		var val = bestRow[header_map[name]];
		var li = document.createElement("li");
		li.textContent = name + " = " + val;
		ul.appendChild(li);
	}

	return container;
}

function initializeResultParameterVisualizations() {
        try {
                var elements = $('.result_parameter_visualization');

                if (!elements || elements.length === 0) {
                        console.warn('No .result_parameter_visualization elements found.');
                        return;
                }

                elements.each(function () {
                        var element = $(this);

                        if (element.data('initialized')) {
                                return; // Already initialized, skip
                        }

                        var resname = element.attr('data-resname');

                        if (!resname) {
                                console.error('Missing data-resname attribute for element:', this);
                                return;
                        }

                        try {
                                var html = createResultParameterCanvases(resname);

                                element.html(html);
                                element.data('initialized', true);

                        } catch (err) {
                                console.error('Error while calling createResultParameterCanvases for resname:', resname, err);
                        }
                });
        } catch (outerErr) {
                console.error('Failed to initialize result parameter visualizations:', outerErr);
        }
}

function plotParameterDistributionsByStatus() {
	const container = document.getElementById('parameter_by_status_distribution');
	if (!container) {
		console.error("Kein Container mit id 'parameter_by_status_distribution' gefunden.");
		return null;
	}

	if ($(container).data("loaded") === "true") {
		return;
	}

	if (
		typeof special_col_names === "undefined" ||
		typeof result_names === "undefined" ||
		typeof result_min_max === "undefined" ||
		typeof tab_results_headers_json === "undefined" ||
		typeof tab_results_csv_json === "undefined"
	) {
		console.error("Missing one or more required global variables.");
		return null;
	}

	if (
		!Array.isArray(special_col_names) ||
		!Array.isArray(result_names) ||
		!Array.isArray(result_min_max) ||
		!Array.isArray(tab_results_headers_json) ||
		!Array.isArray(tab_results_csv_json)
	) {
		console.error("All inputs must be arrays.");
		return null;
	}

	container.innerHTML = "";

	const statusIndex = tab_results_headers_json.indexOf("trial_status");
	if (statusIndex < 0) {
		container.textContent = "Kein 'trial_status' in den Daten gefunden.";
		return null;
	}

	const trialStatuses = [...new Set(tab_results_csv_json.map(row => row[statusIndex]))].filter(s => s != null);
	const paramCols = tab_results_headers_json.filter(col =>
		!special_col_names.includes(col) &&
		!result_names.includes(col)
	);

	for (const param of paramCols) {
		const paramIndex = tab_results_headers_json.indexOf(param);
		if (paramIndex < 0) continue;

		const traces = [];

		trialStatuses.forEach((status) => {
			const filteredValues = tab_results_csv_json
				.filter(row => row[statusIndex] === status)
				.map(row => row[paramIndex])
				.filter(val => val !== "" && val != null && !isNaN(val))
				.map(Number);

			if (filteredValues.length > 1) {
				// Histogramm-Bins automatisch mit Plotly bestimmen lassen oder eigene
				// Hier: bins in 20 Stück
				const nbins = 20;
				traces.push({
					type: 'histogram',
					x: filteredValues,
					name: status,
					opacity: 0.6,
					xbingroup: 0,
					marker: {color: getColorForStatus(status)},
					nbinsx: nbins,
					// für Overlay-Stil:
					// histfunc: 'count', // default
					// autobinx: false,
					// xbins: {start: Math.min(...filteredValues), end: Math.max(...filteredValues), size: (Math.max(...filteredValues) - Math.min(...filteredValues)) / nbins}
				});
			}
		});

		if (traces.length > 0) {
			const h2 = document.createElement('h2');
			if(!param.startsWith("OO_Info_")) {
				h2.textContent = `Histogram: ${param}`;
				container.appendChild(h2);

				const plotDiv = document.createElement('div');
				plotDiv.style.marginBottom = '30px';
				container.appendChild(plotDiv);

				Plotly.newPlot(plotDiv, traces, {
					barmode: 'overlay',  // 'stack' oder 'overlay'
					xaxis: {
						title: { text: String(param) },  // Sicherstellen, dass es ein Textobjekt ist
						automargin: true,
						tickangle: -45,                  // Optional: bessere Lesbarkeit
						titlefont: { size: 16 }          // Optional: größerer Titel
					},
					yaxis: {
						title: { text: 'Count' },        // Titel explizit als Objekt angeben
						automargin: true,
						titlefont: { size: 16 }          // Optional: größerer Titel
					},
					margin: {
						l: 60,
						r: 30,
						t: 30,
						b: 80                            // genug Platz für x-Achsentitel
					},
					legend: {
						orientation: "h"
					}
				}, {
					responsive: true
				});

			}
		}
	}

	$(container).data("loaded", "true");

	// Color mapping (falls nicht global)
	function getColorForStatus(status) {
		const baseAlpha = 0.5;
		switch(status.toUpperCase()) {
			case 'FAILED':      return `rgba(214, 39, 40, ${baseAlpha})`;
			case 'COMPLETED':   return `rgba(44, 160, 44, ${baseAlpha})`;
			case 'ABANDONED':   return `rgba(255, 215, 0, ${baseAlpha})`;
			case 'RUNNING':     return `rgba(50, 50, 44, ${baseAlpha})`;
			default:
				const otherColors = [
					`rgba(31, 119, 180, ${baseAlpha})`,
					`rgba(255, 127, 14, ${baseAlpha})`,
					`rgba(148, 103, 189, ${baseAlpha})`,
					`rgba(140, 86, 75, ${baseAlpha})`,
					`rgba(227, 119, 194, ${baseAlpha})`,
					`rgba(127, 127, 127, ${baseAlpha})`,
					`rgba(188, 189, 34, ${baseAlpha})`,
					`rgba(23, 190, 207, ${baseAlpha})`
				];
				let hash = 0;
				for (let i = 0; i < status.length; i++) {
					hash = status.charCodeAt(i) + ((hash << 5) - hash);
				}
				const index = Math.abs(hash) % otherColors.length;
				return otherColors[index];
		}
	}

	resizePlotlyCharts();
}

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);

	if (typeof apply_theme_based_on_system_preferences === 'function') {
		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();;
plotParameterDistributionsByStatus();;
initializeResultParameterVisualizations();
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><img class='invert_icon' src='i/overview.svg' style='height: 1em' />&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>50444 </td></tr><tr><td> Max. nr. evaluations (from arguments)</td><td>50000 </td></tr><tr><td> Number random steps</td><td>20    </td></tr><tr><td> Nr. of workers (parameter)</td><td>50    </td></tr><tr><td> Main process memory (GB)</td><td>8     </td></tr><tr><td> Worker memory (GB)</td><td>32    </td></tr><tr><td> Nr. imported jobs</td><td>444   </td></tr></tbody></table><h2>Job Summary per Generation Node</h2>
<table border='1' cellpadding='5' cellspacing='0'>
<thead><tr><th>Generation Node</th><th>Total</th><th>COMPLETED</th><th>FAILED</th><th>RUNNING</th></tr></thead>
<tbody>
<tr><td>SOBOL</td><td>30</td><td>29</td><td>1</td><td>0</td></tr>
<tr><td>BOTORCH_MODULAR</td><td>651</td><td>448</td><td>197</td><td>6</td></tr>
</tbody></table>
<h2>Experiment parameters:                                                    </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Name</th><th>Type</th><th>Lower bound</th><th>Upper bound</th><th>Values</th><th>Type</th><th>Log Scale? </th></tr></thead><tbody><tr><td> recent_samples_size</td><td>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> n_samples</td><td>int</td><td>1</td><td>5000</td><td></td><td>int</td><td>No         </td></tr><tr><td> confidence</td><td>choice</td><td></td><td></td><td>0.25, 0.1, 0.05, 0.025, 0.01, 0.005, 0.001</td><td></td><td></td></tr><tr><td> feature_proportion</td><td>float</td><td>0.001</td><td>0.999</td><td></td><td>float</td><td>No         </td></tr><tr><td> n_clusters</td><td>int</td><td>1</td><td>50</td><td></td><td>int</td><td>No         </td></tr></tbody></table><h2>Number of evaluations</h2>
<table>
<tbody>
<tr>
<th>Failed</th>
<th>Succeeded</th>
<th>Running</th>
<th>Total</th>
</tr>
<tr>
<td>198</td>
<td>477</td>
<td>6</td>
<td>681</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><img class='invert_icon' src='i/csv.svg' style='height: 1em' />&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")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;results.csv&laquo; as file</button>
<pre id='tab_results_csv_table_pre'>trial_index,arm_name,trial_status,generation_method,generation_node,ACCURACY,RUNTIME,recent_samples_size,n_samples,feature_proportion,n_clusters,confidence
0,0_0,COMPLETED,Sobol,SOBOL,0.810000000000000053290705182008,220,933,3645,0.016406265849247574778457803291,12,0.100000000000000005551115123126
1,1_0,FAILED,Sobol,SOBOL,,,3269,1059,0.889731851389631622772924401943,49,0.005000000000000000104083408559
2,2_0,COMPLETED,Sobol,SOBOL,0.880000000000000004440892098501,242,4792,3930,0.736663017926737717644414260576,32,0.25
3,3_0,COMPLETED,Sobol,SOBOL,0.859999999999999986677323704498,367,2456,1360,0.362550650494173176685563930732,20,0.005000000000000000104083408559
4,4_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,302,1764,4952,0.808529176618903888673628443939,31,0.001000000000000000020816681712
5,5_0,COMPLETED,Sobol,SOBOL,0.900000000000000022204460492503,331,4114,2212,0.184947953529655928495145644774,18,0.050000000000000002775557561563
6,6_0,COMPLETED,Sobol,SOBOL,0.800000000000000044408920985006,202,2513,2779,0.439132494777441040323395782252,1,0.010000000000000000208166817117
7,7_0,COMPLETED,Sobol,SOBOL,0.930000000000000048849813083507,851,163,50,0.563987804446369422883833522064,38,0.100000000000000005551115123126
8,8_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,477,362,4154,0.30147460699453948462789298901,41,0.001000000000000000020816681712
9,9_0,COMPLETED,Sobol,SOBOL,0.890000000000000013322676295502,289,3016,1721,0.675799627423286475291774877405,4,0.25
10,10_0,COMPLETED,Sobol,SOBOL,0.900000000000000022204460492503,283,3915,3264,0.945730223692953564373908648122,15,0.010000000000000000208166817117
11,11_0,COMPLETED,Sobol,SOBOL,0.890000000000000013322676295502,5302,1261,853,0.072618361886590723774936861901,27,0.005000000000000000104083408559
12,12_0,COMPLETED,Sobol,SOBOL,0.619999999999999995559107901499,175,2021,2886,0.506892937110737018535644438089,23,0.25
13,13_0,COMPLETED,Sobol,SOBOL,0.920000000000000039968028886506,1619,4681,606,0.382311327366158359986059167568,36,0.005000000000000000104083408559
14,14_0,COMPLETED,Sobol,SOBOL,0.849999999999999977795539507497,299,3704,4376,0.244683968624100078859129325792,46,0.025000000000000001387778780781
15,15_0,COMPLETED,Sobol,SOBOL,0.880000000000000004440892098501,277,1044,2124,0.868539724433794568803079982899,9,0.050000000000000002775557561563
16,16_0,COMPLETED,Sobol,SOBOL,0.83000000000000007105427357601,205,1221,4545,0.126570844171568747116296549393,7,0.25
17,17_0,COMPLETED,Sobol,SOBOL,0.900000000000000022204460492503,323,3567,1955,0.750458536224439698436583512375,45,0.100000000000000005551115123126
18,18_0,COMPLETED,Sobol,SOBOL,0.880000000000000004440892098501,303,4465,3029,0.62260761624015870108195258581,37,0.25
19,19_0,COMPLETED,Sobol,SOBOL,0.849999999999999977795539507497,540,2119,463,0.497933142295107267205622747497,25,0.005000000000000000104083408559
20,20_0,COMPLETED,Sobol,SOBOL,0.849999999999999977795539507497,253,1476,3433,0.924474668532609955562406867102,26,0.001000000000000000020816681712
21,21_0,COMPLETED,Sobol,SOBOL,0.930000000000000048849813083507,518,3817,684,0.051329918716102838904813410181,13,0.25
22,22_0,COMPLETED,Sobol,SOBOL,0.790000000000000035527136788005,209,2840,4298,0.327077826227992751739748200634,5,0.050000000000000002775557561563
23,23_0,COMPLETED,Sobol,SOBOL,0.849999999999999977795539507497,255,500,1577,0.701496662624180311595978309924,43,0.010000000000000000208166817117
24,24_0,COMPLETED,Sobol,SOBOL,0.650000000000000022204460492503,181,64,2629,0.433072397448122481389276572372,40,0.025000000000000001387778780781
25,25_0,COMPLETED,Sobol,SOBOL,0.920000000000000039968028886506,843,2728,199,0.557960476156324158836241622339,3,0.005000000000000000104083408559
26,26_0,COMPLETED,Sobol,SOBOL,0.839999999999999968913755310496,279,4252,4789,0.818023256603628401428807137563,17,0.005000000000000000104083408559
27,27_0,COMPLETED,Sobol,SOBOL,0.880000000000000004440892098501,1293,1588,2375,0.194348336517810832413388766327,29,0.001000000000000000020816681712
28,28_0,COMPLETED,Sobol,SOBOL,0.739999999999999991118215802999,244,2319,3780,0.632591794868931134310230390838,21,0.100000000000000005551115123126
29,29_0,COMPLETED,Sobol,SOBOL,0.920000000000000039968028886506,521,4968,1509,0.258447610164061203352758866458,34,0.010000000000000000208166817117
30,30_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.479999999999999982236431605997,171,1,1177,0.401716089285815092235765177975,1,0.005000000000000000104083408559
31,31_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.780000000000000026645352591004,197,744,4018,0.402247029487527496538490368039,1,0.25
32,32_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,660,3412,507,0.836446303532113355494459483452,2,0.010000000000000000208166817117
33,33_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,211,3036,4823,0.776709133921094752039948616584,27,0.025000000000000001387778780781
34,34_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,479,3402,723,0.405149014173144528250247731194,1,0.25
35,35_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3254,4,0.837076194802877204814706146863,17,0.25
36,36_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,545,3207,2492,0.449683885895869495108456703747,50,0.001000000000000000020816681712
37,37_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.780000000000000026645352591004,203,798,4802,0.757673651136403836225952090899,1,0.25
38,38_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1045,1,0.840009102875358348860856949614,19,0.010000000000000000208166817117
39,39_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.350000000000000033306690738755,179,1,4496,0.402404643975039333358978410615,1,0.25
40,40_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,600,2945,2840,0.47901129085467519796992519332,44,0.001000000000000000020816681712
41,41_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,306,3394,4392,0.447005571413483182574566399126,50,0.25
42,42_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,238,3063,4733,0.792181858450079379174724181212,1,0.010000000000000000208166817117
43,43_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,233,957,5000,0.404621943590119548250783054755,1,0.050000000000000002775557561563
44,44_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,806,1715,2388,0.49394537454229964223983984084,38,0.001000000000000000020816681712
45,45_0,FAILED,BoTorch,BOTORCH_MODULAR,,,481,1,0.397295053113226215302233867988,1,0.100000000000000005551115123126
46,46_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,350,3476,2162,0.813787342029485771810470851051,1,0.010000000000000000208166817117
47,47_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,367,727,1028,0.397404305498810894725636444491,1,0.005000000000000000104083408559
48,48_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,321,2980,1382,0.40785076679966381085762350267,6,0.001000000000000000020816681712
49,49_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,227,4846,5000,0.06843707090514136726078220363,1,0.100000000000000005551115123126
50,50_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1788,369,0.855080426755115752257552230731,14,0.001000000000000000020816681712
51,51_0,FAILED,BoTorch,BOTORCH_MODULAR,,,583,1,0.830643200356299793440939538414,13,0.100000000000000005551115123126
52,52_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,212,3410,4540,0.477523049219214845706460437214,1,0.010000000000000000208166817117
53,53_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,262,5000,5000,0.017891190585536825147228157107,1,0.010000000000000000208166817117
54,54_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,4638,459,0.496152388883231543204033187067,36,0.001000000000000000020816681712
55,55_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,775,4422,442,0.86245766784778732372274134832,1,0.010000000000000000208166817117
56,56_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,181,590,5000,0.399458194579713210536908718495,1,0.25
57,57_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1,1,0.253399716761304349965655546839,50,0.100000000000000005551115123126
58,58_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,527,2713,713,0.420460602402282723755178039937,1,0.001000000000000000020816681712
59,59_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4925,653,0.890088525592851009804462592001,50,0.005000000000000000104083408559
60,60_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.700000000000000066613381477509,220,203,4182,0.410774195419250809369060561949,50,0.100000000000000005551115123126
61,61_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.670000000000000039968028886506,201,203,4655,0.894417858805075849382149044686,50,0.100000000000000005551115123126
62,62_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3195,256,0.843433272889609120248621820792,1,0.005000000000000000104083408559
63,63_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,343,4842,3515,0.428147763186417951164486339621,13,0.005000000000000000104083408559
64,64_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,396,3958,1909,0.419075276876676339199434551119,13,0.010000000000000000208166817117
65,65_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3576,539,0.895032778609820112158956817439,30,0.010000000000000000208166817117
66,66_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,243,3657,4767,0.400169023866103312769837430096,16,0.010000000000000000208166817117
67,67_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,259,555,4556,0.389851652245955915265795965752,30,0.025000000000000001387778780781
68,68_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,414,716,1136,0.408763180330456499245173063173,14,0.005000000000000000104083408559
69,69_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4895,22,0.901411548469879253531189533533,46,0.010000000000000000208166817117
70,70_0,FAILED,BoTorch,BOTORCH_MODULAR,,,494,170,0.875639450795588136777780619013,36,0.100000000000000005551115123126
71,71_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,283,1570,3003,0.321577352334178612203174907336,19,0.005000000000000000104083408559
72,72_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,308,4011,2261,0.507221172284818333508837895351,1,0.25
73,73_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,6086,3287,1765,0.298177350279924258114050417134,1,0.005000000000000000104083408559
74,74_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,259,1521,4154,0.410317445386874202206684003613,6,0.005000000000000000104083408559
75,75_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,371,4120,4414,0.892034796612900748868923983537,50,0.100000000000000005551115123126
76,76_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,277,1724,4072,0.850855144712747035740108003665,50,0.025000000000000001387778780781
77,77_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,533,3939,1024,0.828351334279278539440838358132,21,0.050000000000000002775557561563
78,78_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3330,431,0.831035425087151558010134522192,23,0.005000000000000000104083408559
79,79_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3848,1186,0.656323426444592294970448165259,36,0.005000000000000000104083408559
80,80_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,326,3528,2410,0.446997728597091192881407550885,1,0.005000000000000000104083408559
81,81_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3819,109,0.559858395723889734618694546953,16,0.25
82,82_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,531,1682,3429,0.289481007314808636010639020242,26,0.005000000000000000104083408559
83,83_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,524,2317,1521,0.415204695669736834062746311247,50,0.005000000000000000104083408559
84,84_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1877,1,0.38662794248162835053506114491,50,0.005000000000000000104083408559
85,85_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4865,316,0.522801574519677125785221960541,46,0.010000000000000000208166817117
86,86_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3452,13,0.906116307198888137897085925943,16,0.050000000000000002775557561563
87,87_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,440,3839,1826,0.148255061360728607189329864013,22,0.050000000000000002775557561563
88,88_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,332,3867,1738,0.527837961961195034632510214578,1,0.050000000000000002775557561563
89,89_0,FAILED,BoTorch,BOTORCH_MODULAR,,,349,61,0.9989999999999999991118215803,50,0.100000000000000005551115123126
90,90_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,621,3785,920,0.710654819171848028958038412384,1,0.005000000000000000104083408559
91,91_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,517,1622,1922,0.497378129202429297706089528219,50,0.005000000000000000104083408559
92,92_0,FAILED,BoTorch,BOTORCH_MODULAR,,,385,1,0.001000000000000000020816681712,50,0.100000000000000005551115123126
93,93_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,260,1590,2960,0.478068945925519406259240895452,50,0.005000000000000000104083408559
94,94_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,653,3664,694,0.324642623035016897325988338707,18,0.050000000000000002775557561563
95,95_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3765,172,0.559398691698044903120035087341,16,0.050000000000000002775557561563
96,96_0,FAILED,BoTorch,BOTORCH_MODULAR,,,370,1,0.831150805716577956161472684471,50,0.100000000000000005551115123126
97,97_0,FAILED,BoTorch,BOTORCH_MODULAR,,,362,1,0.289727790574765553532898820777,50,0.100000000000000005551115123126
98,98_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,454,3599,1752,0.558839685745653902415597258369,17,0.050000000000000002775557561563
99,99_0,FAILED,BoTorch,BOTORCH_MODULAR,,,361,114,0.545419810414490280336963223817,20,0.100000000000000005551115123126
100,100_0,FAILED,BoTorch,BOTORCH_MODULAR,,,883,21,0.260842293749805054225987532845,50,0.005000000000000000104083408559
101,101_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,2244,4089,419,0.491116435985835875221994228923,48,0.005000000000000000104083408559
102,102_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,793,893,1516,0.259269573744980164065054850653,50,0.005000000000000000104083408559
103,103_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1592,119,0.69922313740421371264233130205,50,0.050000000000000002775557561563
104,104_0,FAILED,BoTorch,BOTORCH_MODULAR,,,428,1,0.081088519768732741921368756266,50,0.100000000000000005551115123126
105,105_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,502,1532,968,0.70108345809889471844655872701,50,0.050000000000000002775557561563
106,106_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,6480,1587,2087,0.073561990200969637476724471981,50,0.010000000000000000208166817117
107,107_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,345,652,1460,0.972368899156179966603019693139,50,0.050000000000000002775557561563
108,108_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,290,636,1774,0.085283135440549495687179160086,1,0.050000000000000002775557561563
109,109_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,2498,4842,52,0.045897220402122629323571345594,7,0.010000000000000000208166817117
110,110_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,562,1787,1178,0.362077188613498746061480915159,1,0.050000000000000002775557561563
111,111_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,703,4891,839,0.959315108461900600822502838128,50,0.25
112,112_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.739999999999999991118215802999,304,562,4284,0.439553041900662411212152846929,50,0.005000000000000000104083408559
113,113_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.780000000000000026645352591004,209,612,4483,0.462986754601204641978995368845,12,0.010000000000000000208166817117
114,114_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,697,1680,1221,0.702220421204335254472539418202,31,0.050000000000000002775557561563
115,115_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,582,385,264,0.475530252069373826628861934296,12,0.100000000000000005551115123126
116,116_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,316,397,1135,0.760034447562991655189534867532,15,0.100000000000000005551115123126
117,117_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,419,1627,1957,0.463741616817853974374941117276,1,0.005000000000000000104083408559
118,118_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,391,566,835,0.984700996914394388603852803499,13,0.010000000000000000208166817117
119,119_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,887,1671,1079,0.373071380463568524898931855205,29,0.005000000000000000104083408559
120,120_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,325,3767,3618,0.21642407836937158083223664562,50,0.025000000000000001387778780781
121,121_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,767,4795,2022,0.22375723746486822496315483022,50,0.025000000000000001387778780781
122,122_0,FAILED,BoTorch,BOTORCH_MODULAR,,,692,622,0.88482709044083474037023506753,50,0.001000000000000000020816681712
123,123_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,616,3795,789,0.762095912146215415106098589604,50,0.25
124,124_0,FAILED,BoTorch,BOTORCH_MODULAR,,,690,724,0.905076494331021885741961341409,50,0.001000000000000000020816681712
125,125_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,361,4915,2874,0.04042848296696410076433991776,5,0.25
126,126_0,FAILED,BoTorch,BOTORCH_MODULAR,,,237,1,0.001000000000000000020816681712,50,0.100000000000000005551115123126
127,127_0,FAILED,BoTorch,BOTORCH_MODULAR,,,749,249,0.910145400356307310296699597529,50,0.001000000000000000020816681712
128,128_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,370,1817,3400,0.350416876965735646365374122979,23,0.005000000000000000104083408559
129,129_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,737,801,239,0.225770205544726654256493247885,34,0.050000000000000002775557561563
130,130_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,266,785,2801,0.559511227148913659057427594234,50,0.001000000000000000020816681712
131,131_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3508,37,0.589880947402471211837848841242,1,0.25
132,132_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4828,86,0.68334254732516974684131128015,50,0.25
133,133_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,253,1225,2816,0.001000000000000000020816681712,11,0.25
134,134_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,604,4744,907,0.682518862606819487481857322564,26,0.25
135,135_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4935,1707,0.993316608983916604636021929764,50,0.010000000000000000208166817117
136,136_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,627,1738,960,0.730300892406150703450862238242,1,0.005000000000000000104083408559
137,137_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,327,929,2394,0.635951743848487516252987461485,50,0.010000000000000000208166817117
138,138_0,FAILED,BoTorch,BOTORCH_MODULAR,,,864,1478,0.870620464180522968256070726056,50,0.010000000000000000208166817117
139,139_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,376,3309,811,0.479233464794179719881128676207,1,0.050000000000000002775557561563
140,140_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,241,1149,5000,0.001000000000000000020816681712,11,0.100000000000000005551115123126
141,141_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,526,3666,885,0.554631917454611267359609882988,19,0.25
142,142_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4893,512,0.994721057836606248336863700388,50,0.010000000000000000208166817117
143,143_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,654,3731,939,0.967527898084584059290591540048,28,0.100000000000000005551115123126
144,144_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,286,3629,4112,0.723203072727519935547491058969,14,0.100000000000000005551115123126
145,145_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,327,4394,2749,0.522089970823158000534647271706,15,0.010000000000000000208166817117
146,146_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4931,614,0.813414770175450607681000292359,29,0.025000000000000001387778780781
147,147_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,492,1737,1819,0.644380411854861390175130964053,34,0.005000000000000000104083408559
148,148_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,452,4036,2032,0.792507279916961571153422028146,13,0.25
149,149_0,FAILED,BoTorch,BOTORCH_MODULAR,,,823,757,0.835408760471992972718169312429,29,0.010000000000000000208166817117
150,150_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3488,215,0.995834787550731959093752720946,1,0.001000000000000000020816681712
151,151_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1615,1011,0.813967254073040824557949690643,30,0.005000000000000000104083408559
152,152_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,269,4220,4624,0.694046202018260283139738930913,42,0.010000000000000000208166817117
153,153_0,FAILED,BoTorch,BOTORCH_MODULAR,,,612,377,0.814550773126271665525166554289,32,0.010000000000000000208166817117
154,154_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,221,3189,4055,0.534653129309606733876591988519,50,0.25
155,155_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,241,5000,4927,0.53795102531716487703761231387,1,0.010000000000000000208166817117
156,156_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,250,1188,3231,0.066160240318490520783356600987,9,0.25
157,157_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,286,4719,4950,0.461798552379177329463288970146,10,0.25
158,158_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,390,3975,2545,0.806912100382841446233328497328,8,0.050000000000000002775557561563
159,159_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,287,4294,3850,0.586194506773836443436209719948,1,0.010000000000000000208166817117
160,160_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1611,1141,0.868090015827760130839862995344,19,0.005000000000000000104083408559
161,161_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,417,4070,1976,0.764242949809882499145885503822,30,0.010000000000000000208166817117
162,162_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.410000000000000031086244689504,5348,707,27,0.302196059017490192832866569006,25,0.010000000000000000208166817117
163,163_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1661,534,0.899275684498777150288617576734,46,0.005000000000000000104083408559
164,164_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3700,438,0.944413901631698582406215791707,32,0.050000000000000002775557561563
165,165_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,368,3689,2791,0.68888161376051815221188689975,47,0.25
166,166_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,261,4663,4758,0.649796132650023672283623454859,14,0.25
167,167_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,324,1763,2905,0.397941550333508808900973008349,11,0.050000000000000002775557561563
168,168_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3802,577,0.897070428775234574025887468451,47,0.050000000000000002775557561563
169,169_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,310,651,1493,0.870808097890499288595833604631,17,0.001000000000000000020816681712
170,170_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,926,1130,1019,0.333443920990381781344069622719,20,0.001000000000000000020816681712
171,171_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4615,229,0.802948432723596505766749942268,39,0.025000000000000001387778780781
172,172_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,387,1763,1157,0.188306586863676711507409322621,2,0.050000000000000002775557561563
173,173_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,1389,1006,241,0.275701564558041400943011467461,50,0.025000000000000001387778780781
174,174_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,348,1234,1756,0.502568742342697660774319956545,41,0.25
175,175_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1090,1740,0.906286889002529627568094383605,35,0.005000000000000000104083408559
176,176_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.660000000000000031086244689504,181,76,3229,0.386214008118464569019323562316,15,0.025000000000000001387778780781
177,177_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3748,1455,0.9989999999999999991118215803,50,0.001000000000000000020816681712
178,178_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,388,4808,2135,0.120768550021714687892071538045,4,0.25
179,179_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,635,3749,518,0.129650066496429100526555089345,6,0.050000000000000002775557561563
180,180_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,235,2997,3546,0.421956824727809376440745836589,1,0.005000000000000000104083408559
181,181_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,250,1078,4104,0.896890747668984800178293426143,50,0.010000000000000000208166817117
182,182_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,226,972,3890,0.9989999999999999991118215803,50,0.010000000000000000208166817117
183,183_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,279,4654,5000,0.419742615484247405532869379385,1,0.010000000000000000208166817117
184,184_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,377,2825,1134,0.449127147554825412179013710556,1,0.005000000000000000104083408559
185,185_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,234,1397,4457,0.521669615589749668949082206382,1,0.010000000000000000208166817117
186,186_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,251,1595,5000,0.526388184674304593357874182402,12,0.005000000000000000104083408559
187,187_0,FAILED,BoTorch,BOTORCH_MODULAR,,,814,490,0.624116100703496212709353585524,50,0.001000000000000000020816681712
188,188_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,515,3022,437,0.223389295314400299075074940447,1,0.050000000000000002775557561563
189,189_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,444,786,736,0.669221494678618022966531952989,50,0.050000000000000002775557561563
190,190_0,FAILED,BoTorch,BOTORCH_MODULAR,,,894,467,0.61375724977635104373518970533,48,0.005000000000000000104083408559
191,191_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,250,750,2825,0.796121150705675351133550066152,50,0.010000000000000000208166817117
192,192_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,362,5000,1560,0.822621704483540550079112563253,40,0.25
193,193_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,242,317,1657,0.868015819578583758264755942946,41,0.010000000000000000208166817117
194,194_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3773,146,0.792347608843669837241918685322,50,0.025000000000000001387778780781
195,195_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,461,1117,1425,0.838514771065928199433869849599,37,0.100000000000000005551115123126
196,196_0,FAILED,BoTorch,BOTORCH_MODULAR,,,251,1,0.340588130743317285542559602618,1,0.100000000000000005551115123126
197,197_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,409,2592,608,0.058559046278854047506978730553,1,0.100000000000000005551115123126
198,198_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,288,1668,2704,0.708915151796441267428861010558,1,0.100000000000000005551115123126
199,199_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,879,3268,421,0.793172580992936748778276978555,5,0.025000000000000001387778780781
200,200_0,FAILED,BoTorch,BOTORCH_MODULAR,,,756,252,0.624032337859948937897058840463,50,0.001000000000000000020816681712
201,201_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,7065,4007,88,0.089108960880626641998247805532,39,0.100000000000000005551115123126
202,202_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4138,624,0.9989999999999999991118215803,41,0.010000000000000000208166817117
203,203_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3227,352,0.957754261034429399401801674685,4,0.001000000000000000020816681712
204,204_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,305,4564,3347,0.9989999999999999991118215803,1,0.010000000000000000208166817117
205,205_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,260,3933,4941,0.001000000000000000020816681712,1,0.100000000000000005551115123126
206,206_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,504,3213,605,0.675853807594583355644601851964,1,0.100000000000000005551115123126
207,207_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,321,689,737,0.764512339956638586890846909228,50,0.050000000000000002775557561563
208,208_0,FAILED,BoTorch,BOTORCH_MODULAR,,,875,709,0.624690990204782470307520725328,50,0.001000000000000000020816681712
209,209_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3071,386,0.99312366421242637137822839577,22,0.001000000000000000020816681712
210,210_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1480,1305,0.847810980071561970383697826037,15,0.005000000000000000104083408559
211,211_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3620,2511,0.997679673299284086596117049339,25,0.001000000000000000020816681712
212,212_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,517,3045,581,0.793759147956846211613424202369,1,0.001000000000000000020816681712
213,213_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,245,3116,3220,0.998139437710909516177082423383,19,0.010000000000000000208166817117
214,214_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4552,3493,0.945686916197176818954517329985,50,0.005000000000000000104083408559
215,215_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3831,31,0.16218040346674375551394575723,45,0.25
216,216_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,218,2295,2541,0.004321089852263826532052792828,1,0.25
217,217_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,257,1676,3394,0.775784802539482787331337476644,1,0.025000000000000001387778780781
218,218_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,529,2602,502,0.971358875266893240230103856447,1,0.005000000000000000104083408559
219,219_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,284,3211,3786,0.427735762428598009776692379091,23,0.025000000000000001387778780781
220,220_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,319,3849,3475,0.253257528922915309266272743116,39,0.010000000000000000208166817117
221,221_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4855,1105,0.604361952963004656069756492798,20,0.005000000000000000104083408559
222,222_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,261,3965,4552,0.81343027571827497546053109545,1,0.001000000000000000020816681712
223,223_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,434,1437,1886,0.870441783894983167613190744305,48,0.050000000000000002775557561563
224,224_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,418,1026,1279,0.959467138214798564987972895324,43,0.010000000000000000208166817117
225,225_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4444,642,0.776358491145872187111365292367,40,0.010000000000000000208166817117
226,226_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,367,3943,3359,0.724282484097924617039154782105,22,0.005000000000000000104083408559
227,227_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,236,673,4815,0.513310251664911731950269313529,48,0.25
228,228_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,274,4713,5000,0.316805305491798583350515627899,13,0.001000000000000000020816681712
229,229_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,635,4478,999,0.286365052209477721767427738087,36,0.025000000000000001387778780781
230,230_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,244,3216,4775,0.48177013084364461725783712609,19,0.010000000000000000208166817117
231,231_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,1506,732,361,0.30754051568689050322191747,11,0.001000000000000000020816681712
232,232_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,705,1628,845,0.593842842477294574621282663429,19,0.005000000000000000104083408559
233,233_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,277,1619,4951,0.545484811193007290697210009967,50,0.005000000000000000104083408559
234,234_0,FAILED,BoTorch,BOTORCH_MODULAR,,,912,160,0.628485188632738167591185174388,9,0.005000000000000000104083408559
235,235_0,FAILED,BoTorch,BOTORCH_MODULAR,,,957,294,0.760180401835949814959292325511,18,0.005000000000000000104083408559
236,236_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,366,4032,3806,0.351815510380234508502894641424,17,0.001000000000000000020816681712
237,237_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4292,509,0.755115880480870971247497891454,36,0.005000000000000000104083408559
238,238_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,358,4720,3288,0.969362927289964204646821599454,11,0.25
239,239_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,321,1409,4465,0.814992272731260292140120782278,14,0.050000000000000002775557561563
240,240_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,266,704,1670,0.477712757800049181433621470205,50,0.100000000000000005551115123126
241,241_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,330,4777,3145,0.130343806612493867680413472954,16,0.100000000000000005551115123126
242,242_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,297,1683,4328,0.779758860138101361769713548711,40,0.025000000000000001387778780781
243,243_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4694,186,0.760197715681833807721545781533,35,0.005000000000000000104083408559
244,244_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,280,3990,3546,0.186182562545603530468341091364,1,0.25
245,245_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4255,651,0.758492895729702465423827106861,35,0.005000000000000000104083408559
246,246_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,267,1549,4727,0.92428834640225165930615958132,13,0.050000000000000002775557561563
247,247_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3943,644,0.761028865391914499660686033167,35,0.005000000000000000104083408559
248,248_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,534,3873,1405,0.598963917185907579465720118606,47,0.025000000000000001387778780781
249,249_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.729999999999999982236431605997,196,461,4982,0.230590637040369084154178835888,50,0.100000000000000005551115123126
250,250_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,294,3730,3527,0.772087045754427769850281038089,30,0.005000000000000000104083408559
251,251_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,368,1000,1147,0.691769376564340343627179663599,10,0.001000000000000000020816681712
252,252_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,332,4402,3082,0.437084338101387359643013041932,9,0.025000000000000001387778780781
253,253_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,898,4253,458,0.602636352898106686382107000099,7,0.050000000000000002775557561563
254,254_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,547,4759,1467,0.7781437066480645370347701828,24,0.005000000000000000104083408559
255,255_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,383,4755,2307,0.72264145491717735048098347761,36,0.005000000000000000104083408559
256,256_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1441,930,0.77397766377005328131133410352,42,0.010000000000000000208166817117
257,257_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,382,3488,4531,0.001000000000000000020816681712,1,0.010000000000000000208166817117
258,258_0,FAILED,BoTorch,BOTORCH_MODULAR,,,854,704,0.900828363675549304012690754462,25,0.010000000000000000208166817117
259,259_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,286,4467,4967,0.523873916922660609607476089877,18,0.25
260,260_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,296,4453,4235,0.181114021965484928156087107709,12,0.100000000000000005551115123126
261,261_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,316,4924,4335,0.239567378616296594584511581161,20,0.025000000000000001387778780781
262,262_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,268,3411,4661,0.157754137865472016111212383294,1,0.100000000000000005551115123126
263,263_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,412,3964,3377,0.778616771309360466979399006959,37,0.010000000000000000208166817117
264,264_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,526,4026,1655,0.924311694195173005894616835576,12,0.050000000000000002775557561563
265,265_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,328,1771,4670,0.523207092363837888981947799039,19,0.25
266,266_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1054,604,0.925541207360469297960037238227,12,0.001000000000000000020816681712
267,267_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,347,3633,2920,0.997461900802080414507599925855,10,0.010000000000000000208166817117
268,268_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,335,3828,2759,0.696846012479054421895341420168,33,0.010000000000000000208166817117
269,269_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,251,249,867,0.445325262138219879481937368837,23,0.25
270,270_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.770000000000000017763568394003,221,676,3992,0.675981616981616961759016248834,43,0.100000000000000005551115123126
271,271_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,285,1325,3939,0.818401457126171960609894995287,4,0.25
272,272_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,327,4220,2891,0.166345719363937022405863785934,8,0.001000000000000000020816681712
273,273_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,294,4324,5000,0.228836800085950448080396313344,50,0.025000000000000001387778780781
274,274_0,FAILED,BoTorch,BOTORCH_MODULAR,,,467,250,0.764657604121955825071665913129,42,0.100000000000000005551115123126
275,275_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,352,735,1223,0.047937748780182178054420916169,1,0.25
276,276_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,499,4800,1943,0.325487799282633549768917191614,33,0.025000000000000001387778780781
277,277_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,469,459,354,0.907266806667281544562797535036,9,0.100000000000000005551115123126
278,278_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,251,3204,3872,0.435449501150438844643275615454,9,0.010000000000000000208166817117
279,279_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,220,346,963,0.510089371569839356013176256965,19,0.010000000000000000208166817117
280,280_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,303,1593,4085,0.78952460485781339460942263031,12,0.001000000000000000020816681712
281,281_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,287,3396,4977,0.885134484699801937779284344288,19,0.025000000000000001387778780781
282,282_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,650,3909,2170,0.397173915009322753277842821262,25,0.001000000000000000020816681712
283,283_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,363,4734,2159,0.731163223899292002982974736369,1,0.001000000000000000020816681712
284,284_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,473,4668,2096,0.9989999999999999991118215803,1,0.001000000000000000020816681712
285,285_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,281,4281,4298,0.361104739054762868821768506677,35,0.025000000000000001387778780781
286,286_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,402,4348,1458,0.500090534000078079657214402687,18,0.050000000000000002775557561563
287,287_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,452,4611,2761,0.276988549212962509304958302891,35,0.025000000000000001387778780781
288,288_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,306,1707,3932,0.9179561109319455125543640861,23,0.010000000000000000208166817117
289,289_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,1246,920,204,0.425450792589821435996100262855,1,0.005000000000000000104083408559
290,290_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4941,265,0.502664496151725259664999612141,17,0.010000000000000000208166817117
291,291_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,336,4424,4281,0.037430412828066826624873186802,1,0.001000000000000000020816681712
292,292_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,314,4944,4737,0.676123206113592889465735424892,34,0.100000000000000005551115123126
293,293_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,746,3501,1173,0.088501762358657143359152996709,8,0.100000000000000005551115123126
294,294_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,3810,3395,1142,0.096165314747458693900306059277,8,0.001000000000000000020816681712
295,295_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,657,3713,1265,0.074609217052758025623404591897,9,0.100000000000000005551115123126
296,296_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,408,4254,2674,0.132379658427638685624927461504,12,0.25
297,297_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,264,224,1368,0.353742404106911989547512575882,13,0.005000000000000000104083408559
298,298_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,591,4162,977,0.370785447967687753489940405416,16,0.050000000000000002775557561563
299,299_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,369,3264,1442,0.252114843441091973641476897683,40,0.050000000000000002775557561563
300,300_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,480,4468,1523,0.063552048744071013008927195642,1,0.100000000000000005551115123126
301,301_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,296,4227,4340,0.171952718640027230057043539091,3,0.001000000000000000020816681712
302,302_0,FAILED,BoTorch,BOTORCH_MODULAR,,,477,177,0.91009346335913765546621334579,42,0.010000000000000000208166817117
303,303_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,2314,918,578,0.010503856927295789416842985986,7,0.001000000000000000020816681712
304,304_0,FAILED,BoTorch,BOTORCH_MODULAR,,,695,5,0.9989999999999999991118215803,46,0.005000000000000000104083408559
305,305_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,638,4557,976,0.597982231012806786374369494297,39,0.001000000000000000020816681712
306,306_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,231,4390,4982,0.333315763490679206615396878988,15,0.025000000000000001387778780781
307,307_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1847,63,0.896443571865113364438570897619,33,0.025000000000000001387778780781
308,308_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,339,1343,1981,0.384224687426643285448335518595,10,0.25
309,309_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,279,3947,4553,0.967804225034262666227391491702,34,0.25
310,310_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,369,4871,2837,0.9989999999999999991118215803,37,0.25
311,311_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,780,4633,887,0.001000000000000000020816681712,50,0.100000000000000005551115123126
312,312_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,625,4677,1419,0.83492571366357881679221009108,42,0.001000000000000000020816681712
313,313_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1070,385,0.741233796002824130155772763828,42,0.005000000000000000104083408559
314,314_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,644,4390,1514,0.461977297010310261615728677498,1,0.010000000000000000208166817117
315,315_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,183,563,4754,0.979883093408462024775928966847,33,0.010000000000000000208166817117
316,316_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.690000000000000057731597280508,215,2151,4450,0.300639717036525144777669993346,33,0.050000000000000002775557561563
317,317_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.770000000000000017763568394003,243,535,4865,0.302117640110901974903612199341,28,0.005000000000000000104083408559
318,318_0,FAILED,BoTorch,BOTORCH_MODULAR,,,499,216,0.895105876160731783741653089237,26,0.010000000000000000208166817117
319,319_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1074,1695,0.892090824886298316975796751649,32,0.005000000000000000104083408559
320,320_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,281,244,804,0.894131814478284936420493522746,27,0.100000000000000005551115123126
321,321_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3737,526,0.915057234540519126575475183927,5,0.001000000000000000020816681712
322,322_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,793,4801,753,0.226886772548892640122275565773,27,0.010000000000000000208166817117
323,323_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,415,4917,2124,0.887433629084299235856292398239,27,0.25
324,324_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,381,4205,2150,0.199034940780344254962486161276,1,0.001000000000000000020816681712
325,325_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1030,387,0.802858037390168810532031784533,50,0.050000000000000002775557561563
326,326_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.780000000000000026645352591004,206,777,4616,0.965340481092234470317237082782,16,0.010000000000000000208166817117
327,327_0,FAILED,BoTorch,BOTORCH_MODULAR,,,511,606,0.897069112406862601005741453264,28,0.010000000000000000208166817117
328,328_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,558,197,649,0.172885012696957940381281559894,50,0.025000000000000001387778780781
329,329_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,383,1466,2517,0.458487412956616047221558574165,33,0.100000000000000005551115123126
330,330_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,467,4848,2254,0.559181088731763531463059280213,50,0.010000000000000000208166817117
331,331_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,435,4825,1762,0.001000000000000000020816681712,1,0.100000000000000005551115123126
332,332_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,312,2853,1662,0.024523367627895517606440023428,1,0.100000000000000005551115123126
333,333_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,258,3566,4656,0.339346692133996319373778760564,6,0.050000000000000002775557561563
334,334_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,289,4350,4061,0.375029010246999694455638518775,50,0.100000000000000005551115123126
335,335_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4769,100,0.899392982498551263326191929082,28,0.001000000000000000020816681712
336,336_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,616,4551,771,0.958979903615146733741880780144,6,0.010000000000000000208166817117
337,337_0,FAILED,BoTorch,BOTORCH_MODULAR,,,600,208,0.749734316899749342333336699085,33,0.100000000000000005551115123126
338,338_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,371,4607,2020,0.396591166150835561232668169396,1,0.010000000000000000208166817117
339,339_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,1195,520,93,0.749018601711895715133948669973,32,0.050000000000000002775557561563
340,340_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,504,4571,1500,0.828320932680246202473028915847,14,0.001000000000000000020816681712
341,341_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,1084,3929,866,0.001000000000000000020816681712,24,0.050000000000000002775557561563
342,342_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,433,3153,4756,0.298376322607331989633649982352,22,0.001000000000000000020816681712
343,343_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,415,4401,3948,0.118437771413171938350572531817,8,0.100000000000000005551115123126
344,344_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,560,3163,795,0.524940330324802806316597525438,19,0.050000000000000002775557561563
345,345_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,242,3471,4482,0.582401762363778052744578417332,34,0.25
346,346_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,247,4180,4909,0.931525617969499397652555217064,38,0.100000000000000005551115123126
347,347_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,270,3851,5000,0.352503946258493905396846912481,46,0.025000000000000001387778780781
348,348_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1450,2540,0.739278947434575672836842841207,50,0.005000000000000000104083408559
349,349_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3520,132,0.9989999999999999991118215803,47,0.050000000000000002775557561563
350,350_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,449,1763,2638,0.02354731687570041712143087409,7,0.025000000000000001387778780781
351,351_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,238,4325,4627,0.153636909900829177200165531758,22,0.050000000000000002775557561563
352,352_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1040,326,0.90036944708323884967171579774,28,0.025000000000000001387778780781
353,353_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,317,1568,4967,0.874936303349702182430291941273,34,0.100000000000000005551115123126
354,354_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,235,2592,2122,0.793346030417139580492857930949,50,0.050000000000000002775557561563
355,355_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,399,1136,2201,0.68452803979294141178968402528,3,0.010000000000000000208166817117
356,356_0,FAILED,BoTorch,BOTORCH_MODULAR,,,424,196,0.9989999999999999991118215803,45,0.050000000000000002775557561563
357,357_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,2462,4922,260,0.9989999999999999991118215803,1,0.25
358,358_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,496,3430,1054,0.9989999999999999991118215803,50,0.100000000000000005551115123126
359,359_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1000,179,0.898154560273931701352978507202,23,0.005000000000000000104083408559
360,360_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,457,3840,2637,0.731879208688724136600001202169,50,0.010000000000000000208166817117
361,361_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,315,1715,2638,0.962734799075106062460349676257,2,0.005000000000000000104083408559
362,362_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,350,981,2831,0.772299668514224602056117419124,50,0.025000000000000001387778780781
363,363_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,401,4474,3351,0.761411842359113077982613049244,12,0.100000000000000005551115123126
364,364_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,2188,740,0.763879294209316106467611007247,10,0.010000000000000000208166817117
365,365_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,257,4523,4215,0.695321496590289855888045167376,6,0.100000000000000005551115123126
366,366_0,FAILED,BoTorch,BOTORCH_MODULAR,,,635,487,0.558153185234274484827210471849,28,0.001000000000000000020816681712
367,367_0,FAILED,BoTorch,BOTORCH_MODULAR,,,978,220,0.956876451711107356423724468186,8,0.005000000000000000104083408559
368,368_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3191,2448,0.001000000000000000020816681712,50,0.001000000000000000020816681712
369,369_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,279,4349,4802,0.724561318199509418747084055212,39,0.100000000000000005551115123126
370,370_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,1269,1692,328,0.437546033858756344692153561482,50,0.25
371,371_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,476,1073,593,0.956686572358681486250020498119,4,0.005000000000000000104083408559
372,372_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,802,1644,456,0.94895262144973491214017258244,1,0.005000000000000000104083408559
373,373_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,620,2917,377,0.748457007021387177303495263914,11,0.100000000000000005551115123126
374,374_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,258,3674,3138,0.334462597696392915924690214524,17,0.25
375,375_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,224,2887,3889,0.755808519889688779080927361065,9,0.010000000000000000208166817117
376,376_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,257,4487,4904,0.830856537378403703364426746703,39,0.010000000000000000208166817117
377,377_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,306,4705,4662,0.234090654717339891055516432061,33,0.25
378,378_0,FAILED,BoTorch,BOTORCH_MODULAR,,,481,491,0.898958465487556201978236458672,30,0.010000000000000000208166817117
379,379_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,530,4046,948,0.171376541760119210922042043421,1,0.005000000000000000104083408559
380,380_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,188,2203,3379,0.336608693987204998787632348467,15,0.010000000000000000208166817117
381,381_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,249,879,3704,0.487520688200630047948180845196,50,0.100000000000000005551115123126
382,382_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,252,1642,4068,0.605805974372041977638048138033,24,0.010000000000000000208166817117
383,383_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,323,3806,4130,0.321968956596112798607123295369,21,0.050000000000000002775557561563
384,384_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,323,1158,1927,0.070142033109485246722414331089,2,0.100000000000000005551115123126
385,385_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,675,4944,658,0.291763254327745746863342901634,44,0.050000000000000002775557561563
386,386_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,538,848,575,0.877506148782741135505602869671,19,0.25
387,387_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,401,1730,2381,0.567180607832030725390382031037,34,0.25
388,388_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,509,1741,1147,0.535092556604968350164597268304,50,0.005000000000000000104083408559
389,389_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,342,3498,2160,0.441220994754018658312588740955,2,0.25
390,390_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,247,1708,4885,0.866170282934193846990922338591,18,0.001000000000000000020816681712
391,391_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4876,1605,0.94213676799566403730068486766,17,0.001000000000000000020816681712
392,392_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,370,3279,1754,0.331780464782229722597861609756,23,0.050000000000000002775557561563
393,393_0,FAILED,BoTorch,BOTORCH_MODULAR,,,217,1,0.89764349780437002745969721218,22,0.100000000000000005551115123126
394,394_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4539,287,0.906987608098459130445689879707,39,0.100000000000000005551115123126
395,395_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,327,4336,3778,0.344940864581544548439495656567,6,0.010000000000000000208166817117
396,396_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3058,1030,0.909516993997259048931880442979,33,0.005000000000000000104083408559
397,397_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,240,422,1037,0.517895072705149339675756436918,32,0.005000000000000000104083408559
398,398_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,363,477,719,0.508393728081375062544111642637,14,0.005000000000000000104083408559
399,399_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,474,4922,1361,0.909429617015160562942810429377,31,0.25
400,400_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,605,4822,1733,0.288368736434590544615019780395,47,0.025000000000000001387778780781
401,401_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,254,4786,4988,0.398449654523289953367282123509,42,0.025000000000000001387778780781
402,402_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,350,494,680,0.661190820201880469220157010568,7,0.010000000000000000208166817117
403,403_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,349,4076,3884,0.962728171811089827869523105619,29,0.050000000000000002775557561563
404,404_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4904,551,0.970251312128735166062654116104,7,0.001000000000000000020816681712
405,405_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,334,1680,1967,0.59882363012410733116297478773,1,0.005000000000000000104083408559
406,406_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,376,4029,1983,0.601261130469281535049219655775,1,0.005000000000000000104083408559
407,407_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,370,3719,2030,0.24361102873536424895384300271,38,0.100000000000000005551115123126
408,408_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,311,4912,3685,0.312953721035338749967280591591,29,0.005000000000000000104083408559
409,409_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,238,3401,4453,0.987564498365419041192581062205,3,0.010000000000000000208166817117
410,410_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,733,4931,873,0.339454336965219816146799303169,19,0.005000000000000000104083408559
411,411_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.19000000000000000222044604925,468,255,1,0.007647243306679590325869444456,1,0.100000000000000005551115123126
412,412_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1655,2131,0.802864034291173034318944701226,38,0.005000000000000000104083408559
413,413_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3406,183,0.968958733915738057440592001512,6,0.001000000000000000020816681712
414,414_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,367,4507,3372,0.668236454942390811773123004969,47,0.025000000000000001387778780781
415,415_0,FAILED,BoTorch,BOTORCH_MODULAR,,,836,347,0.802659094592802935252962015511,44,0.050000000000000002775557561563
416,416_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4475,1002,0.971155792048661203885728809837,11,0.001000000000000000020816681712
417,417_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,307,4020,4696,0.365734769841610074525561913106,28,0.010000000000000000208166817117
418,418_0,FAILED,BoTorch,BOTORCH_MODULAR,,,830,77,0.802085712817528384555032516801,47,0.050000000000000002775557561563
419,419_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,3376,45,0.665043971380007037375037270976,1,0.001000000000000000020816681712
420,420_0,FAILED,BoTorch,BOTORCH_MODULAR,,,438,177,0.678949277474951373712030999741,49,0.100000000000000005551115123126
421,421_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,280,3608,3374,0.588187115597288201485071112984,50,0.025000000000000001387778780781
422,422_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4580,292,0.964561881672513221630538282625,9,0.001000000000000000020816681712
423,423_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,4188,4028,2916,0.001000000000000000020816681712,50,0.010000000000000000208166817117
424,424_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,198,809,4345,0.988530543806968475806229434966,42,0.025000000000000001387778780781
425,425_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,261,1019,2524,0.529873488129248504385770957015,34,0.005000000000000000104083408559
426,426_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,596,2985,1149,0.226124668226217045985393383489,44,0.010000000000000000208166817117
427,427_0,FAILED,BoTorch,BOTORCH_MODULAR,,,460,49,0.810681695475671149075935772998,50,0.050000000000000002775557561563
428,428_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3293,553,0.906954681078079083533793891547,24,0.001000000000000000020816681712
429,429_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,796,4386,749,0.667201039830953690490389362822,48,0.100000000000000005551115123126
430,430_0,FAILED,BoTorch,BOTORCH_MODULAR,,,572,4,0.912492561678998614915769849176,25,0.050000000000000002775557561563
431,431_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2862,260,0.915151847185172839793665389152,22,0.001000000000000000020816681712
432,432_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,2060,3099,162,0.203777431789001955975138002941,1,0.25
433,433_0,FAILED,BoTorch,BOTORCH_MODULAR,,,472,1,0.81005122616227109855202570543,50,0.050000000000000002775557561563
434,434_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3405,313,0.745663780366687456435670355859,9,0.001000000000000000020816681712
435,435_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,228,901,3575,0.562634808155798582518514194817,1,0.025000000000000001387778780781
436,436_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,364,1620,1746,0.974827660654167926779223307676,14,0.005000000000000000104083408559
437,437_0,FAILED,BoTorch,BOTORCH_MODULAR,,,594,1,0.921281615658567476501161763736,23,0.001000000000000000020816681712
438,438_0,FAILED,BoTorch,BOTORCH_MODULAR,,,589,1,0.918527293366203090307919865154,22,0.010000000000000000208166817117
439,439_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4407,1763,0.949357395406286164174503028335,9,0.001000000000000000020816681712
440,440_0,FAILED,BoTorch,BOTORCH_MODULAR,,,632,110,0.935774270129960172859284739388,16,0.001000000000000000020816681712
441,441_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4570,49,0.007986148518911368940353945334,10,0.25
442,442_0,FAILED,BoTorch,BOTORCH_MODULAR,,,546,109,0.942676172736665929363653049222,14,0.001000000000000000020816681712
443,443_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3281,297,0.892015406983544423269449907821,24,0.001000000000000000020816681712
444,444_0,FAILED,BoTorch,BOTORCH_MODULAR,,,492,1,0.737649422358029105417642767861,18,0.010000000000000000208166817117
445,445_0,FAILED,BoTorch,BOTORCH_MODULAR,,,442,73,0.814312297591118228190509853448,50,0.010000000000000000208166817117
446,446_0,FAILED,BoTorch,BOTORCH_MODULAR,,,597,17,0.922688777641588075972833848937,21,0.001000000000000000020816681712
447,447_0,FAILED,BoTorch,BOTORCH_MODULAR,,,512,1,0.81865882334623663041384133976,50,0.010000000000000000208166817117
448,448_0,FAILED,BoTorch,BOTORCH_MODULAR,,,674,41,0.950218240827422899741350192926,12,0.001000000000000000020816681712
449,449_0,FAILED,BoTorch,BOTORCH_MODULAR,,,512,1,0.905274461501300309329565152439,23,0.010000000000000000208166817117
450,450_0,FAILED,BoTorch,BOTORCH_MODULAR,,,671,320,0.949323095188323917703598908702,12,0.001000000000000000020816681712
451,451_0,FAILED,BoTorch,BOTORCH_MODULAR,,,736,186,0.918469214165192338050758280588,23,0.100000000000000005551115123126
452,452_0,FAILED,BoTorch,BOTORCH_MODULAR,,,395,48,0.806440711772054008577015338233,50,0.010000000000000000208166817117
453,453_0,FAILED,BoTorch,BOTORCH_MODULAR,,,555,97,0.91641755514871625631911911114,21,0.010000000000000000208166817117
454,454_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3960,1116,0.895612626169261072384131239232,28,0.001000000000000000020816681712
455,455_0,FAILED,BoTorch,BOTORCH_MODULAR,,,784,591,0.943211628187388573252292189864,15,0.001000000000000000020816681712
456,456_0,FAILED,BoTorch,BOTORCH_MODULAR,,,671,343,0.925975697743831260844160624401,20,0.100000000000000005551115123126
457,457_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,476,4338,1385,0.820338466079878148029536077956,50,0.100000000000000005551115123126
458,458_0,FAILED,BoTorch,BOTORCH_MODULAR,,,947,835,0.955027337830586575684321815061,8,0.001000000000000000020816681712
459,459_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2795,455,0.923595871931560674639172248135,21,0.005000000000000000104083408559
460,460_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3344,117,0.913008173216965923657539860869,19,0.100000000000000005551115123126
461,461_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,441,4387,1415,0.645615478110278195877924645174,7,0.025000000000000001387778780781
462,462_0,FAILED,BoTorch,BOTORCH_MODULAR,,,508,62,0.914616806389118908171553812281,21,0.100000000000000005551115123126
463,463_0,FAILED,BoTorch,BOTORCH_MODULAR,,,293,123,0.579131831441583644348725101736,50,0.005000000000000000104083408559
464,464_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.790000000000000035527136788005,238,298,1689,0.474233702069369489340289192114,20,0.025000000000000001387778780781
465,465_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,725,3850,513,0.001000000000000000020816681712,11,0.25
466,466_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3175,554,0.936754445843089089684951886738,14,0.005000000000000000104083408559
467,467_0,FAILED,BoTorch,BOTORCH_MODULAR,,,608,16,0.938590871955955363681312064728,14,0.001000000000000000020816681712
468,468_0,FAILED,BoTorch,BOTORCH_MODULAR,,,545,220,0.908924853614719863159621127124,18,0.010000000000000000208166817117
469,469_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4605,166,0.61195842347973816721662387863,50,0.050000000000000002775557561563
470,470_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,511,641,427,0.918733326446982911939187488315,25,0.100000000000000005551115123126
471,471_0,FAILED,BoTorch,BOTORCH_MODULAR,,,543,1,0.917487002849765254097746947082,21,0.010000000000000000208166817117
472,472_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2339,103,0.943956775957401794663326199952,9,0.001000000000000000020816681712
473,473_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3358,162,0.732065318738640780082960191066,20,0.100000000000000005551115123126
474,474_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,334,4750,3932,0.228758765073748371321471495321,30,0.010000000000000000208166817117
475,475_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4473,62,0.218973951513074360786248462318,38,0.050000000000000002775557561563
476,476_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,514,4689,979,0.734673201590154922868691755866,19,0.001000000000000000020816681712
477,477_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,2120,4487,606,0.222166208421157668206902258135,37,0.005000000000000000104083408559
478,478_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,445,921,731,0.956283059730483220306496150442,9,0.001000000000000000020816681712
479,479_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.930000000000000048849813083507,594,1849,867,0.95040765697494244967913346045,12,0.025000000000000001387778780781
480,480_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,301,3171,2826,0.400572545743998975620314695334,1,0.005000000000000000104083408559
481,481_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,333,1833,2281,0.167403880723124759422049123714,1,0.050000000000000002775557561563
482,482_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,306,4281,3225,0.001000000000000000020816681712,1,0.050000000000000002775557561563
483,483_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,316,4653,3041,0.170393189673534478645322565171,45,0.050000000000000002775557561563
484,484_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,285,4320,3957,0.971935474200423366042400630249,8,0.001000000000000000020816681712
485,485_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,288,1639,3234,0.833027266163514856778249395575,32,0.010000000000000000208166817117
486,486_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,246,4298,3878,0.607207695715000550507056686911,44,0.050000000000000002775557561563
487,487_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,343,4881,3761,0.173946697851250497990349686006,1,0.005000000000000000104083408559
488,488_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,312,4994,4175,0.594675615998505602277646175935,9,0.25
489,489_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.700000000000000066613381477509,207,2192,3911,0.205520897916500244750892534285,1,0.050000000000000002775557561563
490,490_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,901,4836,4797,0.367776190299359928559397303616,46,0.001000000000000000020816681712
491,491_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,391,1358,2387,0.908400683820741350338323627511,10,0.100000000000000005551115123126
492,492_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,382,1887,3484,0.336181699300889424986138465101,20,0.100000000000000005551115123126
493,493_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,317,1243,2611,0.670503582898604344464388304914,45,0.050000000000000002775557561563
494,494_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2579,181,0.663960961565906115922075514391,46,0.010000000000000000208166817117
495,495_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,327,3025,3460,0.971078718919881067606070246256,44,0.100000000000000005551115123126
496,496_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4463,266,0.668163216375846968908547296451,23,0.005000000000000000104083408559
497,497_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,273,4597,4089,0.987701161753788303698797790275,1,0.005000000000000000104083408559
498,498_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,624,1815,972,0.65606443147297888174307445297,8,0.005000000000000000104083408559
499,499_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,377,1012,1283,0.165235824959120203292428641362,1,0.050000000000000002775557561563
500,500_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,296,4370,4943,0.274068100358152100248787519376,50,0.050000000000000002775557561563
501,501_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,270,4365,4261,0.607042889805541885372974775237,42,0.001000000000000000020816681712
502,502_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,204,2706,3385,0.24869234009028237664118421435,26,0.050000000000000002775557561563
503,503_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,327,4332,4651,0.5709113478276283126788825939,1,0.005000000000000000104083408559
504,504_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,410,3970,1458,0.890656003975181853604681236902,32,0.050000000000000002775557561563
505,505_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4535,4279,0.979187407261952857950859652192,35,0.001000000000000000020816681712
506,506_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4372,2234,0.890637281353753973434095314587,32,0.001000000000000000020816681712
507,507_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,253,1454,4803,0.164006709612800949393829341716,38,0.25
508,508_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,395,4343,2791,0.586964433108885019763079071708,50,0.005000000000000000104083408559
509,509_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.690000000000000057731597280508,184,2182,4187,0.990127317417882513161941915314,1,0.025000000000000001387778780781
510,510_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4362,1055,0.896560331678095345786516645603,23,0.001000000000000000020816681712
511,511_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2809,793,0.889469695894870793217990012636,46,0.005000000000000000104083408559
512,512_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,436,3179,1286,0.443310356308329600594220210041,13,0.050000000000000002775557561563
513,513_0,FAILED,BoTorch,BOTORCH_MODULAR,,,527,1,0.897102498987694230159206654207,24,0.001000000000000000020816681712
514,514_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,289,3825,4266,0.155180649470799569833445730183,18,0.25
515,515_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,509,4958,1698,0.896933894616124494092446184368,30,0.001000000000000000020816681712
516,516_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,404,4225,3009,0.419278693528491341879771425738,2,0.001000000000000000020816681712
517,517_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,284,4056,4853,0.623844614583360379533871764579,40,0.100000000000000005551115123126
518,518_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,462,4338,2158,0.6458789766279570132567755536,18,0.010000000000000000208166817117
519,519_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,311,4492,2591,0.683230482739730637931074852531,20,0.001000000000000000020816681712
520,520_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,311,4478,4398,0.19379227751252842137930088029,50,0.050000000000000002775557561563
521,521_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,267,1254,4019,0.633103792908047191545506393595,9,0.025000000000000001387778780781
522,522_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,239,4537,4791,0.969125774714110654883825191064,40,0.001000000000000000020816681712
523,523_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,349,4429,2595,0.605935644782938265251459597494,5,0.001000000000000000020816681712
524,524_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.770000000000000017763568394003,226,2807,4768,0.9989999999999999991118215803,1,0.050000000000000002775557561563
525,525_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.780000000000000026645352591004,221,1005,4880,0.572688115088818339160070536309,48,0.010000000000000000208166817117
526,526_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,258,4964,4370,0.967222418555400587081294361269,45,0.050000000000000002775557561563
527,527_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.810000000000000053290705182008,227,2905,4509,0.826349245020313372123155204463,38,0.100000000000000005551115123126
528,528_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,228,416,1113,0.752912314121918280207523821446,2,0.010000000000000000208166817117
529,529_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,505,3842,946,0.867350491310135085498700391327,1,0.001000000000000000020816681712
530,530_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,383,4268,2324,0.770017035267024474443076087482,2,0.010000000000000000208166817117
531,531_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,249,1551,4873,0.020596722386069209187464679189,1,0.25
532,532_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,299,1712,2587,0.733203106422843475797890278045,15,0.25
533,533_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,232,1271,3568,0.843404618650703596927087346558,7,0.100000000000000005551115123126
534,534_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,397,4707,2407,0.573094229446160507990271071321,5,0.25
535,535_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,269,1914,4918,0.310428395741759455273012235921,15,0.25
536,536_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,517,1722,1067,0.731008127879759439515794383624,9,0.010000000000000000208166817117
537,537_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,254,4742,4767,0.9989999999999999991118215803,1,0.025000000000000001387778780781
538,538_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.849999999999999977795539507497,333,3564,3668,0.847203253225263686054802292347,6,0.050000000000000002775557561563
539,539_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.770000000000000017763568394003,210,798,4889,0.432178662596826024255847187305,5,0.25
540,540_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,339,1363,4220,0.838159919835667621690333817241,46,0.010000000000000000208166817117
541,541_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3890,1929,0.976482019144778057295752660139,15,0.001000000000000000020816681712
542,542_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,248,1262,3062,0.430457193922167136168610568348,50,0.25
543,543_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.780000000000000026645352591004,228,443,2726,0.527699792950350410336568529601,50,0.100000000000000005551115123126
544,544_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,3333,2665,69,0.746377516344377212043070812797,1,0.001000000000000000020816681712
545,545_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,344,4967,2505,0.726168359107945304842246514454,20,0.001000000000000000020816681712
546,546_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,436,4600,2177,0.742451659599124735855468770751,43,0.001000000000000000020816681712
547,547_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,270,4292,2958,0.223839870920728545300448786293,19,0.050000000000000002775557561563
548,548_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3286,712,0.711434143063113810789843682869,34,0.001000000000000000020816681712
549,549_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1741,223,0.9989999999999999991118215803,48,0.025000000000000001387778780781
550,550_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,339,1682,2474,0.133532570600974731522825322827,1,0.100000000000000005551115123126
551,551_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,1280,1555,252,0.492870322897542678663995729949,10,0.25
552,552_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,374,1576,1608,0.407035607524040388138786283889,32,0.025000000000000001387778780781
553,553_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,366,3729,2430,0.524562131740790915657157711394,13,0.100000000000000005551115123126
554,554_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,372,3601,1817,0.516613942216307631127847344032,22,0.005000000000000000104083408559
555,555_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,238,1548,4386,0.745814547470307176446624453092,1,0.001000000000000000020816681712
556,556_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,318,1430,2288,0.793312586713614487088364057854,1,0.001000000000000000020816681712
557,557_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,354,4102,2698,0.488951327917372835507592299109,50,0.010000000000000000208166817117
558,558_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3393,789,0.706035146513146250057957331592,34,0.001000000000000000020816681712
559,559_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4916,3329,0.890671911203969268733260378212,10,0.001000000000000000020816681712
560,560_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,290,3197,2381,0.683177583422662215717480194144,1,0.001000000000000000020816681712
561,561_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,282,1266,1889,0.409391164215885727806210070412,1,0.025000000000000001387778780781
562,562_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,336,3019,1214,0.9989999999999999991118215803,1,0.005000000000000000104083408559
563,563_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,428,1439,2224,0.236669678581056031063667433045,31,0.010000000000000000208166817117
564,564_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1657,1043,0.695265149334150178717095514003,31,0.001000000000000000020816681712
565,565_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,274,4668,4212,0.835247493218237546663829107274,16,0.010000000000000000208166817117
566,566_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3400,931,0.696552442038869901175246468483,31,0.001000000000000000020816681712
567,567_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,473,4113,1393,0.533013059446484582792891160352,28,0.010000000000000000208166817117
568,568_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1142,664,0.696731010910612291731069944944,33,0.001000000000000000020816681712
569,569_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.709999999999999964472863211995,185,2221,3257,0.190362277289385595224757707911,31,0.050000000000000002775557561563
570,570_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,536,2999,653,0.195022245216122130928582123488,15,0.050000000000000002775557561563
571,571_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3289,1026,0.696537759142953016855415171449,30,0.001000000000000000020816681712
572,572_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,419,926,1204,0.797129251674883576583852118347,1,0.001000000000000000020816681712
573,573_0,FAILED,BoTorch,BOTORCH_MODULAR,,,938,558,0.842169147437020759738857123011,14,0.001000000000000000020816681712
574,574_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2985,1004,0.694989510526247800115129393816,30,0.001000000000000000020816681712
575,575_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1150,1,0.826467331689693329721535519639,1,0.001000000000000000020816681712
576,576_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4039,1024,0.77503145699697173487408008441,36,0.001000000000000000020816681712
577,577_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1664,821,0.693961506830739427442722444539,31,0.001000000000000000020816681712
578,578_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,256,986,2312,0.659480763556816063086785106861,16,0.25
579,579_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3238,859,0.696542438999053326043053857575,31,0.001000000000000000020816681712
580,580_0,FAILED,BoTorch,BOTORCH_MODULAR,,,815,348,0.64232774861265962140777219247,16,0.001000000000000000020816681712
581,581_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,274,4755,4629,0.568638064501646001147605602455,49,0.001000000000000000020816681712
582,582_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,330,4699,2371,0.993308333038379287494024083571,1,0.005000000000000000104083408559
583,583_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,469,4323,2248,0.879739289411639702187528655486,7,0.005000000000000000104083408559
584,584_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4052,487,0.694819837747188140397724964714,32,0.001000000000000000020816681712
585,585_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1383,270,0.829310394570764386479311269795,1,0.001000000000000000020816681712
586,586_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,229,4815,4468,0.760419123679591302256142171245,1,0.001000000000000000020816681712
587,587_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1780,1131,0.672518083926690657392555294791,27,0.001000000000000000020816681712
588,588_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,392,1583,2234,0.41200144859207005199053241995,3,0.005000000000000000104083408559
589,589_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4789,10,0.694818320644815523579040927871,35,0.001000000000000000020816681712
590,590_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,334,2871,1751,0.189145248168950730338622179261,10,0.050000000000000002775557561563
591,591_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,431,361,573,0.764407456676524654781701428874,26,0.100000000000000005551115123126
592,592_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1919,997,0.698030413297600960120803392783,32,0.001000000000000000020816681712
593,593_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,332,4791,2938,0.852771145258178320247566261969,7,0.001000000000000000020816681712
594,594_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1189,210,0.853908395905289108185343138757,18,0.001000000000000000020816681712
595,595_0,FAILED,BoTorch,BOTORCH_MODULAR,,,223,394,0.692401865636422364502777782036,32,0.001000000000000000020816681712
596,596_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3248,813,0.774494529842276180353621839458,35,0.001000000000000000020816681712
597,597_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3170,1056,0.698592977492513034221133239043,31,0.001000000000000000020816681712
598,598_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2793,62,0.772741812327616406363972600957,39,0.001000000000000000020816681712
599,599_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4155,406,0.696496499964953885708496272855,33,0.001000000000000000020816681712
600,600_0,FAILED,BoTorch,BOTORCH_MODULAR,,,845,1302,0.777872410352760779161940263293,34,0.001000000000000000020816681712
601,601_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,503,1503,1234,0.69861181622321788520224572494,32,0.001000000000000000020816681712
602,602_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4868,334,0.82248901869892288019059378712,1,0.001000000000000000020816681712
603,603_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,369,1605,3551,0.546226527933411420967502181156,35,0.100000000000000005551115123126
604,604_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2832,585,0.838576138534613879649270984373,15,0.001000000000000000020816681712
605,605_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,345,3916,3073,0.001000000000000000020816681712,1,0.005000000000000000104083408559
606,606_0,FAILED,BoTorch,BOTORCH_MODULAR,,,651,1276,0.776512371127587863739449858258,35,0.001000000000000000020816681712
607,607_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,292,1500,3686,0.001000000000000000020816681712,3,0.100000000000000005551115123126
608,608_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,428,4052,2522,0.976895880621036827307079875027,25,0.010000000000000000208166817117
609,609_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,331,4882,3305,0.501003014636318355634614363225,1,0.050000000000000002775557561563
610,610_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3874,1207,0.774634395928514463136593803938,33,0.001000000000000000020816681712
611,611_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,382,3392,1227,0.780844310780660189053037356643,38,0.001000000000000000020816681712
612,612_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4891,1,0.822817725871724858777156441647,1,0.001000000000000000020816681712
613,613_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,385,3964,1615,0.897240367803719740535939308756,17,0.010000000000000000208166817117
614,614_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,1326,4950,748,0.449806168749131041195710167813,22,0.001000000000000000020816681712
615,615_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,464,4298,1361,0.524592639285676454186102546373,18,0.005000000000000000104083408559
616,616_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,286,4381,3562,0.61766279217015918057143153419,19,0.005000000000000000104083408559
617,617_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1691,51,0.649972495533467031769703226018,12,0.001000000000000000020816681712
618,618_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,289,3375,2435,0.443509774439760584563430256821,50,0.050000000000000002775557561563
619,619_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,237,1789,4195,0.993131152163835739798969370895,25,0.025000000000000001387778780781
620,620_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,362,4431,2939,0.726036607254487931228936758998,1,0.25
621,621_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,306,4000,3065,0.728936554147291415617360144097,1,0.001000000000000000020816681712
622,622_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,297,1402,2606,0.496211229622156302365709734659,25,0.050000000000000002775557561563
623,623_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,524,4408,1189,0.658543198585732958427740868501,15,0.001000000000000000020816681712
624,624_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,390,1118,764,0.797320609819106129734223031846,19,0.010000000000000000208166817117
625,625_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,350,4183,2243,0.42667508488351107986957799767,50,0.010000000000000000208166817117
626,626_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,289,4695,2680,0.995642265480040533631722610153,45,0.050000000000000002775557561563
627,627_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,501,4369,2389,0.791903837057734372173456449673,36,0.25
628,628_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.820000000000000062172489379009,301,1387,4485,0.585146845735496357043814441568,25,0.001000000000000000020816681712
629,629_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,542,3931,2970,0.592818748369108527995763324725,47,0.001000000000000000020816681712
630,630_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,378,1806,4645,0.026811407910844377994186160663,8,0.050000000000000002775557561563
631,631_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.83000000000000007105427357601,226,1638,4949,0.772678602935065961254679223202,10,0.005000000000000000104083408559
632,632_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,301,1415,2838,0.411595007797121548165364401939,32,0.25
633,633_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,1756,4701,0.497058361556228789357447794828,11,0.050000000000000002775557561563
634,634_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,370,4144,2308,0.981736160521978984405677692848,23,0.001000000000000000020816681712
635,635_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.760000000000000008881784197001,268,427,3390,0.876455919636598190791687557066,18,0.100000000000000005551115123126
636,636_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,336,1603,3022,0.424785278108559150034295726073,50,0.005000000000000000104083408559
637,637_0,FAILED,BoTorch,BOTORCH_MODULAR,,,3130,1232,0.873340757162251901668525988498,28,0.005000000000000000104083408559
638,638_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,361,1722,1773,0.560237427015988664891210646601,1,0.001000000000000000020816681712
639,639_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.719999999999999973354647408996,228,2258,3234,0.6731489460805294422485189898,48,0.010000000000000000208166817117
640,640_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,294,4921,3626,0.001000000000000000020816681712,5,0.25
641,641_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,326,4637,2968,0.89867585091859769619304643129,11,0.001000000000000000020816681712
642,642_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1050,1104,0.753954824344437724015222102025,34,0.001000000000000000020816681712
643,643_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,368,2812,1413,0.674522599903293995637909574725,50,0.010000000000000000208166817117
644,644_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,2247,1774,177,0.59014840214186237155047365377,1,0.001000000000000000020816681712
645,645_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,435,1842,1812,0.548739327742971405577065979742,50,0.050000000000000002775557561563
646,646_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4832,158,0.98549498892548548223402349322,16,0.005000000000000000104083408559
647,647_0,FAILED,BoTorch,BOTORCH_MODULAR,,,954,32,0.812712291703685862920281124389,46,0.050000000000000002775557561563
648,648_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,265,4646,4271,0.561981816013789381436538405978,1,0.001000000000000000020816681712
649,649_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.859999999999999986677323704498,267,4136,4194,0.962543159094027767075374413253,4,0.025000000000000001387778780781
650,650_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2660,347,0.812026818421411222814754182764,45,0.050000000000000002775557561563
651,651_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,498,4421,742,0.820438513030537164283373385842,1,0.001000000000000000020816681712
652,652_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,222,1564,4849,0.9989999999999999991118215803,26,0.050000000000000002775557561563
653,653_0,FAILED,BoTorch,BOTORCH_MODULAR,,,690,266,0.813803489137209123960303713829,47,0.25
654,654_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,277,4403,2973,0.551012453343881936085324468877,1,0.001000000000000000020816681712
655,655_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.869999999999999995559107901499,257,1865,3535,0.854557625472993742654637117084,22,0.100000000000000005551115123126
656,656_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,524,1248,453,0.223565077666824235658182828956,50,0.050000000000000002775557561563
657,657_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1267,1014,0.782953308137021797286081437051,21,0.001000000000000000020816681712
658,658_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.790000000000000035527136788005,212,731,3370,0.588079385335890325592345106998,1,0.001000000000000000020816681712
659,659_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,350,3800,1916,0.771813969869681093527447046654,17,0.001000000000000000020816681712
660,660_0,FAILED,BoTorch,BOTORCH_MODULAR,,,527,303,0.982542167937289545598389395309,15,0.005000000000000000104083408559
661,661_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,377,3154,1003,0.268217873984074817172995608416,1,0.005000000000000000104083408559
662,662_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,343,1316,2496,0.397745593401200359107150461568,25,0.005000000000000000104083408559
663,663_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.920000000000000039968028886506,389,1031,668,0.238612707288378356196290042135,1,0.050000000000000002775557561563
664,664_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,255,337,605,0.511289375514729527161250643985,9,0.100000000000000005551115123126
665,665_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4516,996,0.9989999999999999991118215803,5,0.005000000000000000104083408559
666,666_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.829999999999999960031971113494,239,2704,2894,0.901626442827991425588152196724,50,0.025000000000000001387778780781
667,667_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.890000000000000013322676295502,427,2584,907,0.9989999999999999991118215803,1,0.005000000000000000104083408559
668,668_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,377,3140,1103,0.9989999999999999991118215803,1,0.001000000000000000020816681712
669,669_0,FAILED,BoTorch,BOTORCH_MODULAR,,,1655,617,0.9989999999999999991118215803,33,0.005000000000000000104083408559
670,670_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,269,1734,2864,0.001000000000000000020816681712,1,0.25
671,671_0,FAILED,BoTorch,BOTORCH_MODULAR,,,2685,510,0.9989999999999999991118215803,29,0.005000000000000000104083408559
672,672_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.839999999999999968913755310496,5961,4153,4711,0.447404393767833641337716699127,30,0.005000000000000000104083408559
673,673_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.880000000000000004440892098501,292,1359,2230,0.476160303343340085557855445586,11,0.005000000000000000104083408559
674,674_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.800000000000000044408920985006,4634,2438,2301,0.307709169158330020366065582493,50,0.100000000000000005551115123126
675,675_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.900000000000000022204460492503,330,3142,1406,0.756089856711035790404196177406,1,0.100000000000000005551115123126
676,676_0,FAILED,BoTorch,BOTORCH_MODULAR,,,4861,692,0.998516113833091134566188884492,31,0.005000000000000000104083408559
677,677_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.910000000000000031086244689504,339,4630,1569,0.248702980451874944289869517888,1,0.005000000000000000104083408559
678,678_0,COMPLETED,BoTorch,BOTORCH_MODULAR,0.680000000000000048849813083507,178,2023,876,0.250429141937037413878641700649,1,0.005000000000000000104083408559
679,679_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,4682,1779,0.471684763443508681124427539544,24,0.100000000000000005551115123126
680,680_0,RUNNING,BoTorch,BOTORCH_MODULAR,,,423,1,0.680923494380599070296966601745,21,0.005000000000000000104083408559</pre>
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<button onclick='download_as_file("tab_results_csv_table_pre", "results.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;results.csv&laquo; as file</button>
<script>
	createTable(tab_results_csv_json, tab_results_headers_json, 'tab_results_csv_table');</script>

<h1><img class='invert_icon' src='i/terminal.svg' style='height: 1em' />&nbsp;Errors</h1>
<button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<pre id='simple_pre_tab_tab_errors'><span style="background-color: black; color: white;">
/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023504/5023504_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023556/5023556_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023606/5023606_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023622/5023622_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023656/5023656_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023672/5023672_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5023691/5023691_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5024273/5024273_0_log.err not found


⚠ Job 5024297 (task: 0) with path /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5024297/5024297_0_result.pkl
has not produced any output (state: TIMEOUT)
No error stream produced. Look at stdout: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5024297/5024297_0_log.out
----------------------------------------
submitit INFO (2025-05-11 18:04:04,410) - Starting with JobEnvironment(job_id=5024297, hostname=i7176, local_rank=0(1), node=0(1), global_rank=0(1))
submitit INFO (2025-05-11 18:04:04,423) - Loading pickle: /data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5024297/5024297_submitted.pkl
slurmstepd: error: *** JOB 5024297 ON i7176 CANCELLED AT 2025-05-11T20:03:51 DUE TO TIME LIMIT ***



/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5024297/5024297_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5025093/5025093_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5025102/5025102_0_log.err not found


/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/5/single_runs/5025123/5025123_0_log.err not found

</span></pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("simple_pre_tab_tab_errors")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("simple_pre_tab_tab_errors", "oo_errors.txt")'><img src='i/download.svg' style='height: 1em'> Download &raquo;oo_errors.txt&laquo; as file</button>

<h1><img class='invert_icon' src='i/table.svg' style='height: 1em' />&nbsp;Args Overview</h1>
<h2>Arguments Overview:                                                                              </h2><table cellspacing="0" cellpadding="5"><thead><tr><th> Key</th><th>Value                                                                                                                          </th></tr></thead><tbody><tr><td> config_yaml</td><td>None                                                                                                                           </td></tr><tr><td> config_toml</td><td>None                                                                                                                           </td></tr><tr><td> config_json</td><td>None                                                                                                                           </td></tr><tr><td> num_random_steps</td><td>20                                                                                                                             </td></tr><tr><td> max_eval</td><td>50000                                                                                                                          </td></tr><tr><td> run_program</td><td>None                                                                                                                           </td></tr><tr><td> experiment_name</td><td>None                                                                                                                           </td></tr><tr><td> mem_gb</td><td>32                                                                                                                             </td></tr><tr><td> parameter</td><td>None                                                                                                                           </td></tr><tr><td> continue_previous_job</td><td>/data/horse/ws/s4122485-compPerfDD/benchmark/dfki/benchmarkdd/runs/CSDDM_PokerHand_HoeffdingTreeClassifier_ACCURACY-RUNTIME/4/ </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>50                                                                                                                             </td></tr><tr><td> worker_timeout</td><td>120                                                                                                                            </td></tr><tr><td> slurm_use_srun</td><td>False                                                                                                                          </td></tr><tr><td> time</td><td></td></tr><tr><td> partition</td><td></td></tr><tr><td> reservation</td><td>None                                                                                                                           </td></tr><tr><td> force_local_execution</td><td>False                                                                                                                          </td></tr><tr><td> slurm_signal_delay_s</td><td>0                                                                                                                              </td></tr><tr><td> nodes_per_job</td><td>1                                                                                                                              </td></tr><tr><td> cpus_per_task</td><td>32                                                                                                                             </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><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&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")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_worker_usage", "worker_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;worker_usage.csv&laquo; as file</button>
<pre id="pre_tab_worker_usage">1746862358.2331367,50,0,0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_worker_usage")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<h1><img class='invert_icon' src='i/cpu.svg' style='height: 1em' />&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")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
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<pre id="pre_tab_main_worker_cpu_ram">timestamp,ram_usage_mb,cpu_usage_percent
1746862358,646.03125,4.6
1746862358,640.390625,3.9
1746862358,640.390625,4.7
1746862358,640.390625,6.0
1746862358,640.390625,3.0
1746862358,640.390625,5.6
1746862358,640.390625,4.0
</pre><button class='copy_clipboard_button' onclick='copy_to_clipboard_from_id("pre_tab_main_worker_cpu_ram")'><img src='i/clipboard.svg' style='height: 1em'> Copy raw data to clipboard</button>
<button onclick='download_as_file("pre_tab_main_worker_cpu_ram", "cpu_ram_usage.csv")'><img src='i/download.svg' style='height: 1em'> Download &raquo;cpu_ram_usage.csv&laquo; as file</button>

<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Param-Distrib by Status</h1>
<div class='invert_in_dark_mode' id='parameter_by_status_distribution'></div>
<h1><img class='invert_icon' src='i/insights.svg' style='height: 1em' />&nbsp;Insights</h1>
<h2>Visualization for result: <code>ACCURACY</code> (goal: <b>maximize</b>)</h2><p>Best value: <b>0.93</b><br />
Achieved at:<br />
- <code>RUNTIME</code> = 851<br />
- <code>recent_samples_size</code> = 163<br />
- <code>n_samples</code> = 50<br />
- <code>feature_proportion</code> = 0.56398780444637<br />
- <code>n_clusters</code> = 38<br />
- <code>confidence</code> = 0.1</p><div class="result_parameter_visualization" data-resname="ACCURACY"></div><h2>Visualization for result: <code>RUNTIME</code> (goal: <b>minimize</b>)</h2><p>Best value: <b>171</b><br />
Achieved at:<br />
- <code>ACCURACY</code> = 0.48<br />
- <code>recent_samples_size</code> = 1<br />
- <code>n_samples</code> = 1177<br />
- <code>feature_proportion</code> = 0.40171608928582<br />
- <code>n_clusters</code> = 1<br />
- <code>confidence</code> = 0.005</p><div class="result_parameter_visualization" data-resname="RUNTIME"></div><h2>Parameter statistics</h2><table border='1' cellpadding='5' cellspacing='0'><thead><tr><th>Parameter</th><th>Min</th><th>Max</th><th>Mean</th><th>Std Dev</th><th>Count</th></tr></thead><tbody><tr><td>generation_method</td><td colspan='5' style='text-align:center;'>No numerical statistics available</td></tr><tr><td>ACCURACY</td><td>0.19</td><td>0.93</td><td>0.8658</td><td>0.0698</td><td>477</td></tr><tr><td>RUNTIME</td><td>171</td><td>7065</td><td>521.1048</td><td>769.4002</td><td>477</td></tr><tr><td>recent_samples_size</td><td>1</td><td>5000</td><td>2678.7812</td><td>1576.675</td><td>681</td></tr><tr><td>n_samples</td><td>1</td><td>5000</td><td>1997.9736</td><td>1604.5651</td><td>681</td></tr><tr><td>feature_proportion</td><td>0.001</td><td>0.999</td><td>0.6116</td><td>0.2857</td><td>681</td></tr><tr><td>n_clusters</td><td>1</td><td>50</td><td>23.558</td><td>17.2457</td><td>681</td></tr><tr><td>confidence</td><td>0.001</td><td>0.25</td><td>0.0522</td><td>0.0773</td><td>681</td></tr></tbody></table>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Parallel Plot</h1>
<input type="checkbox" id="enable_slurm_id_if_exists" onchange="createParallelPlot(tab_results_csv_json, tab_results_headers_json, result_names, special_col_names, true)" /> Show SLURM-Job-ID (if it exists)<br><div class="invert_in_dark_mode" id="parallel-plot"></div>
<h1><img class='invert_icon' src='i/scatter.svg' style='height: 1em' />&nbsp;Scatter-2D</h1>
<div class='invert_in_dark_mode' id='plotScatter2d'></div>
<h1><img class='invert_icon' src='i/scatter.svg' style='height: 1em' />&nbsp;Scatter-3D</h1>
<div class='invert_in_dark_mode' id='plotScatter3d'></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Job Status Distribution</h1>
<div class="invert_in_dark_mode" id="plotJobStatusDistribution"></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Boxplots</h1>
<div class="invert_in_dark_mode" id="plotBoxplot"></div>
<h1><img class='invert_icon' src='i/violin.svg' style='height: 1em' />&nbsp;Violin</h1>
<div class="invert_in_dark_mode" id="plotViolin"></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&nbsp;Histogram</h1>
<div class="invert_in_dark_mode" id="plotHistogram"></div>
<h1><img class='invert_icon' src='i/plot.svg' style='height: 1em' />&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><img class='invert_icon' src='i/scatter.svg' style='height: 1em' />&nbsp;Result-Pairs</h1>
<div class="invert_in_dark_mode" id="plotResultPairs"></div>
<h1><img class='invert_icon' src='i/evolution.svg' style='height: 1em' />&nbsp;Evolution</h1>
<div class="invert_in_dark_mode" id="plotResultEvolution"></div>
	</body>
</html>
Experiment overview:

Job Summary per Generation Node

Experiment parameters:

Number of evaluations

Result names and types

Git-Version

Arguments Overview:

Visualization for result: `ACCURACY` (goal: maximize)

Visualization for result: `RUNTIME` (goal: minimize)

Parameter statistics

Correlation Heatmap Explanation

How It Works

Color Scale: Yellow to Purple (Viridis)

What the Heatmap Shows

Experiment overview:

Job Summary per Generation Node

Experiment parameters:

Number of evaluations

Result names and types

Git-Version

Arguments Overview:

Visualization for result: ACCURACY (goal: maximize)

Visualization for result: RUNTIME (goal: minimize)

Parameter statistics

Correlation Heatmap Explanation

How It Works

Color Scale: Yellow to Purple (Viridis)

What the Heatmap Shows

Visualization for result: `ACCURACY` (goal: maximize)

Visualization for result: `RUNTIME` (goal: minimize)
