refactor: Archive experimental LLM features for MVP stability (Phase 1.1)
Moved experimental LLM integration code to optimization_engine/future/: - llm_optimization_runner.py - Runtime LLM API runner - llm_workflow_analyzer.py - Workflow analysis - inline_code_generator.py - Auto-generate calculations - hook_generator.py - Auto-generate hooks - report_generator.py - LLM report generation - extractor_orchestrator.py - Extractor orchestration Added comprehensive optimization_engine/future/README.md explaining: - MVP LLM strategy (Claude Code skills, not runtime LLM) - Why files were archived - When to revisit post-MVP - Production architecture reference Production runner confirmed: optimization_engine/runner.py is sole active runner. This establishes clear separation between: - Production code (stable, no runtime LLM dependencies) - Experimental code (archived for post-MVP exploration) Part of Phase 1: Core Stabilization & Organization for MVP Generated with Claude Code Co-Authored-By: Claude <noreply@anthropic.com>
This commit is contained in:
@@ -3,33 +3,53 @@ import {
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LineChart, Line, ScatterChart, Scatter,
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XAxis, YAxis, CartesianGrid, Tooltip, Legend, ResponsiveContainer, Cell
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} from 'recharts';
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import { useWebSocket } from '../hooks/useWebSocket';
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import { Card } from '../components/Card';
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import { MetricCard } from '../components/MetricCard';
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import { StudyCard } from '../components/StudyCard';
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import { useOptimizationWebSocket } from '../hooks/useWebSocket';
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import { apiClient } from '../api/client';
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import { Card } from '../components/common/Card';
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import { MetricCard } from '../components/dashboard/MetricCard';
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import { StudyCard } from '../components/dashboard/StudyCard';
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import { OptimizerPanel } from '../components/OptimizerPanel';
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import { ParetoPlot } from '../components/ParetoPlot';
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import { ParallelCoordinatesPlot } from '../components/ParallelCoordinatesPlot';
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import type { Study, Trial, ConvergenceDataPoint, ParameterSpaceDataPoint } from '../types';
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interface DashboardProps {
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studies: Study[];
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selectedStudyId: string | null;
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onStudySelect: (studyId: string) => void;
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}
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export default function Dashboard({ studies, selectedStudyId, onStudySelect }: DashboardProps) {
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const [trials, setTrials] = useState<Trial[]>([]);
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export default function Dashboard() {
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const [studies, setStudies] = useState<Study[]>([]);
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const [selectedStudyId, setSelectedStudyId] = useState<string | null>(null);
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const [allTrials, setAllTrials] = useState<Trial[]>([]);
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const [displayedTrials, setDisplayedTrials] = useState<Trial[]>([]);
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const [bestValue, setBestValue] = useState<number>(Infinity);
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const [prunedCount, setPrunedCount] = useState<number>(0);
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const [alerts, setAlerts] = useState<Array<{ id: number; type: 'success' | 'warning'; message: string }>>([]);
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const [alertIdCounter, setAlertIdCounter] = useState(0);
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const [expandedTrials, setExpandedTrials] = useState<Set<number>>(new Set());
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const [sortBy, setSortBy] = useState<'performance' | 'chronological'>('performance');
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// Protocol 13: New state for metadata and Pareto front
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const [studyMetadata, setStudyMetadata] = useState<any>(null);
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const [paretoFront, setParetoFront] = useState<any[]>([]);
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// Load studies on mount
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useEffect(() => {
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apiClient.getStudies()
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.then(data => {
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setStudies(data.studies);
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if (data.studies.length > 0) {
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// Check LocalStorage for last selected study
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const savedStudyId = localStorage.getItem('lastSelectedStudyId');
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const studyExists = data.studies.find(s => s.id === savedStudyId);
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if (savedStudyId && studyExists) {
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setSelectedStudyId(savedStudyId);
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} else {
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const running = data.studies.find(s => s.status === 'running');
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setSelectedStudyId(running?.id || data.studies[0].id);
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}
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}
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})
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.catch(console.error);
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}, []);
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const showAlert = (type: 'success' | 'warning', message: string) => {
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const id = alertIdCounter;
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setAlertIdCounter(prev => prev + 1);
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@@ -40,54 +60,50 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
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};
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// WebSocket connection
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const { isConnected } = useWebSocket({
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const { connectionStatus } = useOptimizationWebSocket({
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studyId: selectedStudyId,
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onTrialCompleted: (trial) => {
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setTrials(prev => [trial, ...prev].slice(0, 20));
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setAllTrials(prev => [...prev, trial]);
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if (trial.objective < bestValue) {
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setBestValue(trial.objective);
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showAlert('success', `New best: ${trial.objective.toFixed(4)} (Trial #${trial.trial_number})`);
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onMessage: (msg) => {
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if (msg.type === 'trial_completed') {
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const trial = msg.data as Trial;
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setAllTrials(prev => [...prev, trial]);
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if (trial.objective !== null && trial.objective !== undefined && trial.objective < bestValue) {
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setBestValue(trial.objective);
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showAlert('success', `New best: ${trial.objective.toFixed(4)} (Trial #${trial.trial_number})`);
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}
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} else if (msg.type === 'trial_pruned') {
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setPrunedCount(prev => prev + 1);
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showAlert('warning', `Trial pruned: ${msg.data.pruning_cause}`);
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}
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},
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onNewBest: (trial) => {
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console.log('New best trial:', trial);
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},
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onTrialPruned: (pruned) => {
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setPrunedCount(prev => prev + 1);
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showAlert('warning', `Trial #${pruned.trial_number} pruned: ${pruned.pruning_cause}`);
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},
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}
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});
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// Load initial trial history when study changes
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useEffect(() => {
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if (selectedStudyId) {
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setTrials([]);
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setAllTrials([]);
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setBestValue(Infinity);
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setPrunedCount(0);
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setExpandedTrials(new Set());
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// Fetch full history
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fetch(`/api/optimization/studies/${selectedStudyId}/history`)
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.then(res => res.json())
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// Save to LocalStorage
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localStorage.setItem('lastSelectedStudyId', selectedStudyId);
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apiClient.getStudyHistory(selectedStudyId)
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.then(data => {
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const sortedTrials = data.trials.sort((a: Trial, b: Trial) => a.trial_number - b.trial_number);
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setAllTrials(sortedTrials);
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setTrials(sortedTrials.slice(-20).reverse());
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if (sortedTrials.length > 0) {
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const minObj = Math.min(...sortedTrials.map((t: Trial) => t.objective));
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const validTrials = data.trials.filter(t => t.objective !== null && t.objective !== undefined);
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setAllTrials(validTrials);
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if (validTrials.length > 0) {
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const minObj = Math.min(...validTrials.map(t => t.objective));
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setBestValue(minObj);
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}
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})
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.catch(err => console.error('Failed to load history:', err));
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.catch(console.error);
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// Fetch pruning count
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fetch(`/api/optimization/studies/${selectedStudyId}/pruning`)
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.then(res => res.json())
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apiClient.getStudyPruning(selectedStudyId)
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.then(data => {
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setPrunedCount(data.pruned_trials?.length || 0);
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})
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.catch(err => console.error('Failed to load pruning data:', err));
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.catch(console.error);
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// Protocol 13: Fetch metadata
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fetch(`/api/optimization/studies/${selectedStudyId}/metadata`)
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@@ -97,12 +113,12 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
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})
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.catch(err => console.error('Failed to load metadata:', err));
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// Protocol 13: Fetch Pareto front
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// Protocol 13: Fetch Pareto front (raw format for Protocol 13 components)
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fetch(`/api/optimization/studies/${selectedStudyId}/pareto-front`)
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.then(res => res.json())
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.then(data => {
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if (data.is_multi_objective) {
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setParetoFront(data.pareto_front);
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.then(paretoData => {
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if (paretoData.is_multi_objective && paretoData.pareto_front) {
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setParetoFront(paretoData.pareto_front);
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} else {
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setParetoFront([]);
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}
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@@ -111,42 +127,92 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
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}
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}, [selectedStudyId]);
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// Prepare chart data
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const convergenceData: ConvergenceDataPoint[] = allTrials.map((trial, idx) => ({
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trial_number: trial.trial_number,
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objective: trial.objective,
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best_so_far: Math.min(...allTrials.slice(0, idx + 1).map(t => t.objective)),
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}));
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// Sort trials based on selected sort order
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useEffect(() => {
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let sorted = [...allTrials];
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if (sortBy === 'performance') {
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// Sort by objective (best first)
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sorted.sort((a, b) => {
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const aObj = a.objective ?? Infinity;
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const bObj = b.objective ?? Infinity;
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return aObj - bObj;
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});
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} else {
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// Chronological (newest first)
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sorted.sort((a, b) => b.trial_number - a.trial_number);
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}
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setDisplayedTrials(sorted);
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}, [allTrials, sortBy]);
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const parameterSpaceData: ParameterSpaceDataPoint[] = allTrials.map(trial => {
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const params = Object.values(trial.design_variables);
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return {
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trial_number: trial.trial_number,
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x: params[0] || 0,
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y: params[1] || 0,
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objective: trial.objective,
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isBest: trial.objective === bestValue,
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};
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});
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// Auto-refresh polling (every 3 seconds) for trial history
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useEffect(() => {
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if (!selectedStudyId) return;
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const refreshInterval = setInterval(() => {
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apiClient.getStudyHistory(selectedStudyId)
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.then(data => {
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const validTrials = data.trials.filter(t => t.objective !== null && t.objective !== undefined);
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setAllTrials(validTrials);
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if (validTrials.length > 0) {
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const minObj = Math.min(...validTrials.map(t => t.objective));
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setBestValue(minObj);
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}
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})
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.catch(err => console.error('Auto-refresh failed:', err));
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}, 3000); // Poll every 3 seconds
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return () => clearInterval(refreshInterval);
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}, [selectedStudyId]);
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// Prepare chart data with proper null/undefined handling
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const convergenceData: ConvergenceDataPoint[] = allTrials
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.filter(t => t.objective !== null && t.objective !== undefined)
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.sort((a, b) => a.trial_number - b.trial_number)
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.map((trial, idx, arr) => {
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const previousTrials = arr.slice(0, idx + 1);
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const validObjectives = previousTrials.map(t => t.objective).filter(o => o !== null && o !== undefined);
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return {
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trial_number: trial.trial_number,
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objective: trial.objective,
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best_so_far: validObjectives.length > 0 ? Math.min(...validObjectives) : trial.objective,
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};
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});
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const parameterSpaceData: ParameterSpaceDataPoint[] = allTrials
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.filter(t => t.objective !== null && t.objective !== undefined && t.design_variables)
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.map(trial => {
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const params = Object.values(trial.design_variables);
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return {
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trial_number: trial.trial_number,
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x: params[0] || 0,
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y: params[1] || 0,
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objective: trial.objective,
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isBest: trial.objective === bestValue,
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};
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});
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// Calculate average objective
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const avgObjective = allTrials.length > 0
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? allTrials.reduce((sum, t) => sum + t.objective, 0) / allTrials.length
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const validObjectives = allTrials.filter(t => t.objective !== null && t.objective !== undefined).map(t => t.objective);
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const avgObjective = validObjectives.length > 0
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? validObjectives.reduce((sum, obj) => sum + obj, 0) / validObjectives.length
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: 0;
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// Get parameter names
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const paramNames = allTrials.length > 0 ? Object.keys(allTrials[0].design_variables) : [];
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const paramNames = allTrials.length > 0 && allTrials[0].design_variables
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? Object.keys(allTrials[0].design_variables)
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: [];
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// Helper: Format parameter label with unit from metadata
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const getParamLabel = (paramName: string, index: number): string => {
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if (!studyMetadata?.design_variables) {
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return paramName || `Parameter ${index + 1}`;
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}
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const dv = studyMetadata.design_variables.find((v: any) => v.name === paramName);
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if (dv && dv.unit) {
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return `${paramName} (${dv.unit})`;
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}
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return paramName || `Parameter ${index + 1}`;
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// Toggle trial expansion
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const toggleTrialExpansion = (trialNumber: number) => {
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setExpandedTrials(prev => {
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const newSet = new Set(prev);
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if (newSet.has(trialNumber)) {
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newSet.delete(trialNumber);
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} else {
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newSet.add(trialNumber);
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}
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return newSet;
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});
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};
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// Export functions
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@@ -169,7 +235,7 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
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const rows = allTrials.map(t => [
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t.trial_number,
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t.objective,
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...paramNames.map(k => t.design_variables[k])
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...paramNames.map(k => t.design_variables?.[k] ?? '')
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].join(','));
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const csv = [headers, ...rows].join('\n');
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const blob = new Blob([csv], { type: 'text/csv' });
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@@ -183,7 +249,7 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
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};
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return (
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<div className="container mx-auto p-6">
|
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<div className="container mx-auto">
|
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{/* Alerts */}
|
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<div className="fixed top-4 right-4 z-50 space-y-2">
|
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{alerts.map(alert => (
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@@ -201,12 +267,24 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
|
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</div>
|
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|
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{/* Header */}
|
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<header className="mb-8 flex items-center justify-between border-b border-dark-500 pb-4">
|
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<header className="mb-8 flex items-center justify-between border-b border-dark-600 pb-4">
|
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<div>
|
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<h1 className="text-3xl font-bold text-primary-400">Atomizer Dashboard</h1>
|
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<p className="text-dark-200 mt-2">Real-time optimization monitoring</p>
|
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<h1 className="text-3xl font-bold text-primary-400">Live Dashboard</h1>
|
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<p className="text-dark-300 mt-1">Real-time optimization monitoring</p>
|
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</div>
|
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<div className="flex gap-2">
|
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<button
|
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onClick={() => {
|
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if (selectedStudyId) {
|
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window.open(`http://localhost:8080?study=${selectedStudyId}`, '_blank');
|
||||
}
|
||||
}}
|
||||
className="btn-secondary"
|
||||
disabled={!selectedStudyId}
|
||||
title="Open Optuna Dashboard (make sure it's running on port 8080)"
|
||||
>
|
||||
Optuna Dashboard
|
||||
</button>
|
||||
<button onClick={exportJSON} className="btn-secondary" disabled={allTrials.length === 0}>
|
||||
Export JSON
|
||||
</button>
|
||||
@@ -226,7 +304,7 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
|
||||
key={study.id}
|
||||
study={study}
|
||||
isActive={study.id === selectedStudyId}
|
||||
onClick={() => onStudySelect(study.id)}
|
||||
onClick={() => setSelectedStudyId(study.id)}
|
||||
/>
|
||||
))}
|
||||
</div>
|
||||
@@ -248,14 +326,6 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
|
||||
value={avgObjective > 0 ? avgObjective.toFixed(4) : '-'}
|
||||
valueColor="text-blue-400"
|
||||
/>
|
||||
<MetricCard
|
||||
label="Connection"
|
||||
value={isConnected ? 'Connected' : 'Disconnected'}
|
||||
valueColor={isConnected ? 'text-green-400' : 'text-red-400'}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="grid grid-cols-4 gap-4 mb-6">
|
||||
<MetricCard
|
||||
label="Pruned"
|
||||
value={prunedCount}
|
||||
@@ -264,25 +334,38 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
|
||||
</div>
|
||||
|
||||
{/* Protocol 13: Intelligent Optimizer & Pareto Front */}
|
||||
{selectedStudyId && (
|
||||
{selectedStudyId && paretoFront.length > 0 && studyMetadata && studyMetadata.objectives && (
|
||||
<div className="grid grid-cols-2 gap-6 mb-6">
|
||||
<OptimizerPanel studyId={selectedStudyId} />
|
||||
{paretoFront.length > 0 && studyMetadata && (
|
||||
<ParetoPlot
|
||||
paretoData={paretoFront}
|
||||
objectives={studyMetadata.objectives || []}
|
||||
/>
|
||||
)}
|
||||
<Card title="Optimizer Strategy">
|
||||
<div className="space-y-2">
|
||||
<div className="text-sm text-dark-300">
|
||||
<span className="font-semibold text-dark-100">Algorithm:</span> {studyMetadata.sampler || 'NSGA-II'}
|
||||
</div>
|
||||
<div className="text-sm text-dark-300">
|
||||
<span className="font-semibold text-dark-100">Type:</span> Multi-objective
|
||||
</div>
|
||||
<div className="text-sm text-dark-300">
|
||||
<span className="font-semibold text-dark-100">Objectives:</span> {studyMetadata.objectives?.length || 2}
|
||||
</div>
|
||||
<div className="text-sm text-dark-300">
|
||||
<span className="font-semibold text-dark-100">Design Variables:</span> {studyMetadata.design_variables?.length || 0}
|
||||
</div>
|
||||
</div>
|
||||
</Card>
|
||||
<ParetoPlot
|
||||
paretoData={paretoFront}
|
||||
objectives={studyMetadata.objectives}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Parallel Coordinates (full width for multi-objective) */}
|
||||
{paretoFront.length > 0 && studyMetadata && (
|
||||
{paretoFront.length > 0 && studyMetadata && studyMetadata.objectives && studyMetadata.design_variables && (
|
||||
<div className="mb-6">
|
||||
<ParallelCoordinatesPlot
|
||||
paretoData={paretoFront}
|
||||
objectives={studyMetadata.objectives || []}
|
||||
designVariables={studyMetadata.design_variables || []}
|
||||
objectives={studyMetadata.objectives}
|
||||
designVariables={studyMetadata.design_variables}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
@@ -344,14 +427,14 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
|
||||
dataKey="x"
|
||||
stroke="#94a3b8"
|
||||
name={paramNames[0] || 'X'}
|
||||
label={{ value: getParamLabel(paramNames[0], 0), position: 'insideBottom', offset: -5, fill: '#94a3b8' }}
|
||||
label={{ value: paramNames[0] || 'Parameter 1', position: 'insideBottom', offset: -5, fill: '#94a3b8' }}
|
||||
/>
|
||||
<YAxis
|
||||
type="number"
|
||||
dataKey="y"
|
||||
stroke="#94a3b8"
|
||||
name={paramNames[1] || 'Y'}
|
||||
label={{ value: getParamLabel(paramNames[1], 1), angle: -90, position: 'insideLeft', fill: '#94a3b8' }}
|
||||
label={{ value: paramNames[1] || 'Parameter 2', angle: -90, position: 'insideLeft', fill: '#94a3b8' }}
|
||||
/>
|
||||
<Tooltip
|
||||
cursor={{ strokeDasharray: '3 3' }}
|
||||
@@ -381,38 +464,149 @@ export default function Dashboard({ studies, selectedStudyId, onStudySelect }: D
|
||||
</Card>
|
||||
</div>
|
||||
|
||||
{/* Trial Feed */}
|
||||
<Card title="Recent Trials">
|
||||
<div className="space-y-2 max-h-96 overflow-y-auto">
|
||||
{trials.length > 0 ? (
|
||||
trials.map(trial => (
|
||||
<div
|
||||
key={trial.trial_number}
|
||||
className={`p-3 rounded-lg transition-all duration-200 ${
|
||||
trial.objective === bestValue
|
||||
? 'bg-green-900 border-l-4 border-green-400'
|
||||
: 'bg-dark-500 hover:bg-dark-400'
|
||||
{/* Trial History with Sort Controls */}
|
||||
<Card
|
||||
title={
|
||||
<div className="flex items-center justify-between w-full">
|
||||
<span>Trial History ({displayedTrials.length} trials)</span>
|
||||
<div className="flex gap-2">
|
||||
<button
|
||||
onClick={() => setSortBy('performance')}
|
||||
className={`px-3 py-1 rounded text-sm ${
|
||||
sortBy === 'performance'
|
||||
? 'bg-primary-500 text-white'
|
||||
: 'bg-dark-500 text-dark-200 hover:bg-dark-400'
|
||||
}`}
|
||||
>
|
||||
<div className="flex justify-between items-center mb-1">
|
||||
<span className="font-semibold text-primary-400">
|
||||
Trial #{trial.trial_number}
|
||||
</span>
|
||||
<span className={`font-mono text-lg ${
|
||||
trial.objective === bestValue ? 'text-green-400 font-bold' : 'text-dark-100'
|
||||
}`}>
|
||||
{trial.objective.toFixed(4)}
|
||||
</span>
|
||||
Best First
|
||||
</button>
|
||||
<button
|
||||
onClick={() => setSortBy('chronological')}
|
||||
className={`px-3 py-1 rounded text-sm ${
|
||||
sortBy === 'chronological'
|
||||
? 'bg-primary-500 text-white'
|
||||
: 'bg-dark-500 text-dark-200 hover:bg-dark-400'
|
||||
}`}
|
||||
>
|
||||
Newest First
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
}
|
||||
>
|
||||
<div className="space-y-2 max-h-[600px] overflow-y-auto">
|
||||
{displayedTrials.length > 0 ? (
|
||||
displayedTrials.map(trial => {
|
||||
const isExpanded = expandedTrials.has(trial.trial_number);
|
||||
const isBest = trial.objective === bestValue;
|
||||
|
||||
return (
|
||||
<div
|
||||
key={trial.trial_number}
|
||||
className={`rounded-lg transition-all duration-200 cursor-pointer ${
|
||||
isBest
|
||||
? 'bg-green-900 border-l-4 border-green-400'
|
||||
: 'bg-dark-500 hover:bg-dark-400'
|
||||
}`}
|
||||
onClick={() => toggleTrialExpansion(trial.trial_number)}
|
||||
>
|
||||
{/* Collapsed View */}
|
||||
<div className="p-3">
|
||||
<div className="flex justify-between items-center">
|
||||
<span className="font-semibold text-primary-400">
|
||||
Trial #{trial.trial_number}
|
||||
{isBest && <span className="ml-2 text-xs bg-green-700 text-green-100 px-2 py-1 rounded">BEST</span>}
|
||||
</span>
|
||||
<div className="flex items-center gap-3">
|
||||
<span className={`font-mono text-lg ${
|
||||
isBest ? 'text-green-400 font-bold' : 'text-dark-100'
|
||||
}`}>
|
||||
{trial.objective !== null && trial.objective !== undefined
|
||||
? trial.objective.toFixed(4)
|
||||
: 'N/A'}
|
||||
</span>
|
||||
<span className="text-dark-400 text-sm">
|
||||
{isExpanded ? '▼' : '▶'}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Quick Preview */}
|
||||
{!isExpanded && trial.results && Object.keys(trial.results).length > 0 && (
|
||||
<div className="text-xs text-primary-300 flex flex-wrap gap-3 mt-2">
|
||||
{trial.results.mass && (
|
||||
<span>Mass: {trial.results.mass.toFixed(2)}g</span>
|
||||
)}
|
||||
{trial.results.frequency && (
|
||||
<span>Freq: {trial.results.frequency.toFixed(2)}Hz</span>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{/* Expanded View */}
|
||||
{isExpanded && (
|
||||
<div className="px-3 pb-3 space-y-3">
|
||||
{/* Design Variables */}
|
||||
{trial.design_variables && Object.keys(trial.design_variables).length > 0 && (
|
||||
<div className="border-t border-dark-400 pt-3">
|
||||
<h4 className="text-sm font-semibold text-dark-200 mb-2">Design Variables</h4>
|
||||
<div className="grid grid-cols-2 gap-2 text-xs">
|
||||
{Object.entries(trial.design_variables).map(([key, val]) => (
|
||||
<div key={key} className="flex justify-between bg-dark-600 px-2 py-1 rounded">
|
||||
<span className="text-dark-300">{key}:</span>
|
||||
<span className="text-dark-100 font-mono">{val.toFixed(4)}</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Results */}
|
||||
{trial.results && Object.keys(trial.results).length > 0 && (
|
||||
<div className="border-t border-dark-400 pt-3">
|
||||
<h4 className="text-sm font-semibold text-dark-200 mb-2">Extracted Results</h4>
|
||||
<div className="grid grid-cols-2 gap-2 text-xs">
|
||||
{Object.entries(trial.results).map(([key, val]) => (
|
||||
<div key={key} className="flex justify-between bg-dark-600 px-2 py-1 rounded">
|
||||
<span className="text-dark-300">{key}:</span>
|
||||
<span className="text-primary-300 font-mono">
|
||||
{typeof val === 'number' ? val.toFixed(4) : String(val)}
|
||||
</span>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* All User Attributes */}
|
||||
{trial.user_attrs && Object.keys(trial.user_attrs).length > 0 && (
|
||||
<div className="border-t border-dark-400 pt-3">
|
||||
<h4 className="text-sm font-semibold text-dark-200 mb-2">All Attributes</h4>
|
||||
<div className="max-h-48 overflow-y-auto">
|
||||
<pre className="text-xs text-dark-300 bg-dark-700 p-2 rounded">
|
||||
{JSON.stringify(trial.user_attrs, null, 2)}
|
||||
</pre>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Timestamps */}
|
||||
{trial.start_time && trial.end_time && (
|
||||
<div className="border-t border-dark-400 pt-3 text-xs text-dark-400">
|
||||
<div className="flex justify-between">
|
||||
<span>Duration:</span>
|
||||
<span>
|
||||
{((new Date(trial.end_time).getTime() - new Date(trial.start_time).getTime()) / 1000).toFixed(1)}s
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
<div className="text-xs text-dark-200 flex flex-wrap gap-3">
|
||||
{Object.entries(trial.design_variables).map(([key, val]) => (
|
||||
<span key={key}>
|
||||
<span className="text-dark-400">{key}:</span> {val.toFixed(3)}
|
||||
</span>
|
||||
))}
|
||||
</div>
|
||||
</div>
|
||||
))
|
||||
);
|
||||
})
|
||||
) : (
|
||||
<div className="text-center py-8 text-dark-300">
|
||||
No trials yet. Waiting for optimization to start...
|
||||
|
||||
Reference in New Issue
Block a user