14863929a0
- Translate all Chinese comments and strings in webui/app.py - Translate all Chinese comments and strings in webui/run.py - Translate all Chinese comments and strings in webui/start.sh - Translate all Chinese content in webui/README.md - Translate all Chinese content in webui/templates/index.html - Add prediction results directory for analysis - Complete internationalization of webui module
1239 lines
45 KiB
HTML
1239 lines
45 KiB
HTML
<!DOCTYPE html>
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<html lang="zh-CN">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Kronos Financial Prediction Web UI</title>
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<script src="https://cdn.plot.ly/plotly-latest.min.js"></script>
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<script src="https://cdn.jsdelivr.net/npm/axios/dist/axios.min.js"></script>
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<style>
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* {
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margin: 0;
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padding: 0;
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box-sizing: border-box;
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}
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body {
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font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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min-height: 100vh;
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color: #333;
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}
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.container {
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max-width: 1400px;
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margin: 0 auto;
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padding: 20px;
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}
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.header {
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text-align: center;
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margin-bottom: 30px;
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color: white;
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}
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.header h1 {
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font-size: 2.5rem;
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margin-bottom: 10px;
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text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
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}
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.header p {
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font-size: 1.1rem;
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opacity: 0.9;
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}
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.main-content {
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display: grid;
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grid-template-columns: 1fr 2fr;
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gap: 30px;
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margin-bottom: 30px;
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}
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.control-panel {
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background: white;
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border-radius: 15px;
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padding: 25px;
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box-shadow: 0 10px 30px rgba(0,0,0,0.2);
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height: fit-content;
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}
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.control-panel h2 {
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color: #4a5568;
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margin-bottom: 20px;
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font-size: 1.5rem;
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border-bottom: 2px solid #e2e8f0;
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padding-bottom: 10px;
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}
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.form-group {
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margin-bottom: 20px;
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}
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.form-group label {
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display: block;
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margin-bottom: 8px;
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font-weight: 600;
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color: #4a5568;
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}
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.form-group select,
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.form-group input {
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width: 100%;
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padding: 12px;
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border: 2px solid #e2e8f0;
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border-radius: 8px;
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font-size: 14px;
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transition: border-color 0.3s ease;
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}
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.form-group select:focus,
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.form-group input:focus {
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outline: none;
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border-color: #667eea;
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}
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/* Prediction quality parameter styles */
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.form-group input[type="range"] {
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width: 70%;
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margin-right: 10px;
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}
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.form-group input[type="number"] {
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width: 100%;
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}
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.form-group span {
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display: inline-block;
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min-width: 40px;
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font-weight: 600;
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color: #667eea;
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}
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.form-text {
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font-size: 12px;
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color: #718096;
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margin-top: 5px;
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}
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.btn {
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background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
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color: white;
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border: none;
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padding: 12px 24px;
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border-radius: 8px;
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font-size: 16px;
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font-weight: 600;
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cursor: pointer;
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transition: transform 0.2s ease, box-shadow 0.2s ease;
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width: 100%;
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margin-bottom: 10px;
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}
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.btn:hover {
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transform: translateY(-2px);
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box-shadow: 0 5px 15px rgba(0,0,0,0.2);
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}
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.btn:disabled {
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opacity: 0.6;
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cursor: not-allowed;
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transform: none;
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}
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.btn-secondary {
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background: linear-gradient(135deg, #718096 0%, #4a5568 100%);
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}
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.btn-success {
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background: linear-gradient(135deg, #48bb78 0%, #38a169 100%);
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}
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.btn-warning {
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background: linear-gradient(135deg, #ed8936 0%, #dd6b20 100%);
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}
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.status {
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padding: 15px;
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border-radius: 8px;
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margin-bottom: 20px;
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font-weight: 500;
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}
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.status.success {
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background: #c6f6d5;
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color: #22543d;
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border: 1px solid #9ae6b4;
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}
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.status.error {
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background: #fed7d7;
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color: #742a2a;
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border: 1px solid #feb2b2;
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}
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.status.info {
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background: #bee3f8;
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color: #2a4365;
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border: 1px solid #90cdf4;
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}
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.status.warning {
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background: #fef5e7;
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color: #744210;
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border: 1px solid #fbd38d;
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}
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.chart-container {
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background: white;
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border-radius: 15px;
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padding: 25px;
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box-shadow: 0 10px 30px rgba(0,0,0,0.2);
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}
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.chart-container h2 {
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color: #4a5568;
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margin-bottom: 20px;
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font-size: 1.5rem;
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border-bottom: 2px solid #e2e8f0;
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padding-bottom: 10px;
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}
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#chart {
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width: 100%;
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height: 600px;
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}
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.data-info {
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background: #f7fafc;
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border: 1px solid #e2e8f0;
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border-radius: 8px;
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padding: 15px;
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margin-bottom: 20px;
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}
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.data-info h3 {
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color: #4a5568;
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margin-bottom: 10px;
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font-size: 1.1rem;
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}
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.data-info p {
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margin-bottom: 5px;
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color: #4a5568;
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}
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.data-info strong {
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color: #2d3748;
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}
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/* Time window selector styles */
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.time-window-container {
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background: #f7fafc;
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border: 1px solid #e2e8f0;
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border-radius: 8px;
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padding: 20px;
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margin-bottom: 20px;
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}
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.time-window-container h3 {
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color: #4a5568;
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margin-bottom: 15px;
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font-size: 1.1rem;
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}
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.time-window-info {
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display: flex;
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justify-content: space-between;
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margin-bottom: 15px;
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font-size: 12px;
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color: #666;
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}
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.time-window-slider {
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position: relative;
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margin-bottom: 10px;
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}
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.slider-track {
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position: relative;
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height: 6px;
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background: #e2e8f0;
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border-radius: 3px;
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cursor: pointer;
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}
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.slider-handle {
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position: absolute;
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top: -7px;
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width: 20px;
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height: 20px;
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background: #667eea;
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border-radius: 50%;
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cursor: grab;
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border: 2px solid white;
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box-shadow: 0 2px 4px rgba(0,0,0,0.2);
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z-index: 10;
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}
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.slider-handle:hover {
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background: #5a67d8;
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transform: scale(1.1);
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}
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.slider-handle:active {
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cursor: grabbing;
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}
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.slider-selection {
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position: absolute;
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height: 6px;
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background: #48bb78;
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border-radius: 3px;
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top: 0;
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}
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.slider-labels {
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display: flex;
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justify-content: space-between;
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font-size: 11px;
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color: #999;
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margin-top: 5px;
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}
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/* Comparison analysis styles */
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.comparison-section {
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background: #f7fafc;
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border: 1px solid #e2e8f0;
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border-radius: 8px;
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padding: 20px;
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margin-top: 20px;
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}
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.comparison-section h3 {
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color: #4a5568;
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margin-bottom: 15px;
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font-size: 1.1rem;
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}
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.comparison-info {
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background: white;
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border: 1px solid #e2e8f0;
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border-radius: 6px;
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padding: 15px;
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margin-bottom: 15px;
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}
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.comparison-table {
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width: 100%;
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border-collapse: collapse;
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margin-top: 15px;
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}
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.comparison-table th,
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.comparison-table td {
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border: 1px solid #e2e8f0;
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padding: 8px;
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text-align: center;
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font-size: 12px;
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}
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.comparison-table th {
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background: #f7fafc;
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font-weight: 600;
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}
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.error-stats {
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display: grid;
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grid-template-columns: repeat(auto-fit, minmax(150px, 1fr));
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gap: 15px;
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margin-top: 15px;
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}
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.error-stat {
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background: white;
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border: 1px solid #e2e8f0;
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border-radius: 6px;
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padding: 15px;
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text-align: center;
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}
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.error-stat h4 {
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color: #4a5568;
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margin-bottom: 5px;
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font-size: 0.9rem;
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}
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.error-stat .value {
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font-size: 1.5rem;
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font-weight: 600;
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color: #667eea;
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}
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.error-stat .unit {
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font-size: 0.8rem;
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color: #718096;
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}
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.loading {
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display: none;
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text-align: center;
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padding: 20px;
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}
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.loading.show {
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display: block;
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}
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.spinner {
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border: 4px solid #f3f3f3;
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border-top: 4px solid #667eea;
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border-radius: 50%;
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width: 40px;
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height: 40px;
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animation: spin 1s linear infinite;
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margin: 0 auto 10px;
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}
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@keyframes spin {
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0% { transform: rotate(0deg); }
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100% { transform: rotate(360deg); }
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}
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.model-info {
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background: #e6fffa;
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border: 1px solid #81e6d9;
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border-radius: 8px;
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padding: 15px;
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margin-bottom: 20px;
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}
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.model-info h3 {
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color: #234e52;
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margin-bottom: 10px;
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font-size: 1.1rem;
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}
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.model-info p {
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margin-bottom: 5px;
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color: #234e52;
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}
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.model-info strong {
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color: #0f2027;
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}
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@media (max-width: 768px) {
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.main-content {
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grid-template-columns: 1fr;
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}
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.container {
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padding: 10px;
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}
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.header h1 {
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font-size: 2rem;
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}
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}
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</style>
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</head>
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<body>
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<div class="container">
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<div class="header">
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<h1>🚀 Kronos Financial Prediction Web UI</h1>
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<p>AI-based financial K-line data prediction analysis platform</p>
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</div>
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<div class="main-content">
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<div class="control-panel">
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<h2>🎯 Control Panel</h2>
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<!-- Model Selection -->
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<div class="form-group">
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<label for="model-select">Select Model:</label>
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<select id="model-select">
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<option value="">Please load available models first</option>
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</select>
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<small class="form-text">Select the Kronos model to use</small>
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</div>
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<!-- Device Selection -->
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<div class="form-group">
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<label for="device-select">Select Device:</label>
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<select id="device-select">
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<option value="cpu">CPU</option>
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<option value="cuda">CUDA (NVIDIA GPU)</option>
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<option value="mps">MPS (Apple Silicon)</option>
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</select>
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<small class="form-text">Select the device to run the model on</small>
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</div>
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<!-- Model Status -->
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<div id="model-status" class="status info" style="display: none;">
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Model status information
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</div>
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<!-- Load Model Button -->
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<button id="load-model-btn" class="btn btn-secondary">
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🔄 Load Model
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</button>
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<hr style="margin: 20px 0; border: 1px solid #e2e8f0;">
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<!-- Data File Selection -->
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<div class="form-group">
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<label for="data-file-select">Select Data File:</label>
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<select id="data-file-select">
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<option value="">Please load data file list first</option>
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</select>
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<small class="form-text">Select K-line data file from data directory</small>
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</div>
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<button id="load-data-btn" class="btn btn-secondary">
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📁 Load Data
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</button>
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<!-- Data Information Display -->
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<div id="data-info" class="data-info" style="display: none;">
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<h3>📊 Data Information</h3>
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<p><strong>Rows:</strong> <span id="data-rows">-</span></p>
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<p><strong>Columns:</strong> <span id="data-cols">-</span></p>
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<p><strong>Time Range:</strong> <span id="data-time-range">-</span></p>
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<p><strong>Price Range:</strong> <span id="data-price-range">-</span></p>
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<p><strong>Time Frequency:</strong> <span id="data-timeframe">-</span></p>
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<p><strong>Prediction Columns:</strong> <span id="data-prediction-cols">-</span></p>
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</div>
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<hr style="margin: 20px 0; border: 1px solid #e2e8f0;">
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<!-- Time Window Selector -->
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<div class="time-window-container">
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<h3>⏰ Time Window Selection</h3>
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<div class="time-window-info">
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<span id="window-start">Start: --</span>
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<span id="window-end">End: --</span>
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<span id="window-size">Window Size: 400+120=520 data points</span>
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</div>
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<div class="time-window-slider">
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<div class="slider-track">
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<div class="slider-handle start-handle" id="start-handle"></div>
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<div class="slider-selection" id="slider-selection"></div>
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<div class="slider-handle end-handle" id="end-handle"></div>
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</div>
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<div class="slider-labels">
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<span id="min-label">Earliest</span>
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<span id="max-label">Latest</span>
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</div>
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</div>
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<small class="form-text">Drag slider to select time window position for 520 data points, green area represents fixed 400+120 data point range</small>
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</div>
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<!-- Prediction Parameters -->
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<div class="form-group">
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<label for="lookback">Lookback Window Size:</label>
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<input type="number" id="lookback" value="400" readonly>
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<small class="form-text">Fixed at 400 data points</small>
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</div>
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<div class="form-group">
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<label for="pred-len">Prediction Length:</label>
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<input type="number" id="pred-len" value="120" readonly>
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<small class="form-text">Fixed at 120 data points</small>
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</div>
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<!-- Prediction Quality Parameters -->
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<div class="form-group">
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<label for="temperature">Prediction Temperature (T):</label>
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<input type="range" id="temperature" value="1.0" min="0.1" max="2.0" step="0.1">
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<span id="temperature-value">1.0</span>
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<small class="form-text">Controls prediction randomness, higher values make predictions more diverse, lower values make predictions more conservative</small>
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</div>
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<div class="form-group">
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<label for="top-p">Nucleus Sampling Parameter (top_p):</label>
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<input type="range" id="top-p" value="0.9" min="0.1" max="1.0" step="0.1">
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<span id="top-p-value">0.9</span>
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<small class="form-text">Controls prediction diversity, higher values consider broader probability distributions</small>
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</div>
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<div class="form-group">
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<label for="sample-count">Sample Count:</label>
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<input type="number" id="sample-count" value="1" min="1" max="5" step="1">
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<small class="form-text">Generate multiple prediction samples to improve quality (recommended 1-3)</small>
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</div>
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<button id="predict-btn" class="btn btn-success" disabled>
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🔮 Start Prediction
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</button>
|
|
|
|
<!-- Loading Status -->
|
|
<div id="loading" class="loading">
|
|
<div class="spinner"></div>
|
|
<p>Processing, please wait...</p>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="chart-container">
|
|
<h2>📈 Prediction Results Chart</h2>
|
|
<div id="chart"></div>
|
|
|
|
<!-- Comparison Analysis -->
|
|
<div id="comparison-section" class="comparison-section" style="display: none;">
|
|
<h3>📊 Prediction vs Actual Data Comparison</h3>
|
|
<div id="comparison-info" class="comparison-info">
|
|
<p><strong>Prediction Type:</strong> <span id="prediction-type">-</span></p>
|
|
<p><strong>Comparison Data:</strong> <span id="comparison-data">-</span></p>
|
|
</div>
|
|
|
|
<div class="error-stats">
|
|
<div class="error-stat">
|
|
<h4>Mean Absolute Error</h4>
|
|
<div class="value" id="mae">-</div>
|
|
<div class="unit">Price Units</div>
|
|
</div>
|
|
<div class="error-stat">
|
|
<h4>Root Mean Square Error</h4>
|
|
<div class="value" id="rmse">-</div>
|
|
<div class="unit">Price Units</div>
|
|
</div>
|
|
<div class="error-stat">
|
|
<h4>Mean Absolute Percentage Error</h4>
|
|
<div class="value" id="mape">-</div>
|
|
<div class="unit">%</div>
|
|
</div>
|
|
</div>
|
|
|
|
<div class="error-details">
|
|
<h4>Detailed Comparison Data:</h4>
|
|
<div style="max-height: 300px; overflow-y: auto;">
|
|
<table class="comparison-table">
|
|
<thead>
|
|
<tr>
|
|
<th>Time</th>
|
|
<th>Actual Open</th>
|
|
<th>Predicted Open</th>
|
|
<th>Actual High</th>
|
|
<th>Predicted High</th>
|
|
<th>Actual Low</th>
|
|
<th>Predicted Low</th>
|
|
<th>Actual Close</th>
|
|
<th>Predicted Close</th>
|
|
</tr>
|
|
</thead>
|
|
<tbody id="comparison-tbody">
|
|
</tbody>
|
|
</table>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
</div>
|
|
|
|
<script>
|
|
// Global variables
|
|
let currentDataFile = null;
|
|
let currentDataInfo = null;
|
|
let availableModels = [];
|
|
let modelLoaded = false;
|
|
|
|
// Initialize after page loads
|
|
document.addEventListener('DOMContentLoaded', function() {
|
|
initializeApp();
|
|
});
|
|
|
|
// Initialize application
|
|
async function initializeApp() {
|
|
console.log('🚀 Initializing Kronos Web UI...');
|
|
|
|
// Load available models
|
|
await loadAvailableModels();
|
|
|
|
// Load data file list
|
|
await loadDataFiles();
|
|
|
|
// Set up event listeners
|
|
setupEventListeners();
|
|
|
|
// Initialize time slider
|
|
initializeTimeSlider();
|
|
|
|
console.log('✅ Application initialization completed');
|
|
}
|
|
|
|
// Load available models
|
|
async function loadAvailableModels() {
|
|
try {
|
|
const response = await axios.get('/api/available-models');
|
|
if (response.data.model_available) {
|
|
availableModels = response.data.models;
|
|
populateModelSelect();
|
|
console.log('✅ Available models loaded successfully:', availableModels);
|
|
} else {
|
|
console.warn('⚠️ Kronos model library not available');
|
|
showStatus('warning', 'Kronos model library not available, will use simulated prediction');
|
|
}
|
|
} catch (error) {
|
|
console.error('❌ Failed to load available models:', error);
|
|
showStatus('error', 'Failed to load available models');
|
|
}
|
|
}
|
|
|
|
// Populate model selection dropdown
|
|
function populateModelSelect() {
|
|
const modelSelect = document.getElementById('model-select');
|
|
modelSelect.innerHTML = '<option value="">Please select model</option>';
|
|
|
|
Object.entries(availableModels).forEach(([key, model]) => {
|
|
const option = document.createElement('option');
|
|
option.value = key;
|
|
option.textContent = `${model.name} (${model.params}) - ${model.description}`;
|
|
modelSelect.appendChild(option);
|
|
});
|
|
}
|
|
|
|
// Load model
|
|
async function loadModel() {
|
|
const modelKey = document.getElementById('model-select').value;
|
|
const device = document.getElementById('device-select').value;
|
|
|
|
if (!modelKey) {
|
|
showStatus('error', 'Please select a model to load');
|
|
return;
|
|
}
|
|
|
|
try {
|
|
showLoading(true);
|
|
document.getElementById('load-model-btn').disabled = true;
|
|
|
|
const response = await axios.post('/api/load-model', {
|
|
model_key: modelKey,
|
|
device: device
|
|
});
|
|
|
|
if (response.data.success) {
|
|
modelLoaded = true;
|
|
showStatus('success', response.data.message);
|
|
updateModelStatus();
|
|
document.getElementById('predict-btn').disabled = false;
|
|
console.log('✅ Model loaded successfully:', response.data.model_info);
|
|
} else {
|
|
showStatus('error', response.data.error);
|
|
}
|
|
} catch (error) {
|
|
console.error('❌ Model loading failed:', error);
|
|
showStatus('error', `Model loading failed: ${error.response?.data?.error || error.message}`);
|
|
} finally {
|
|
showLoading(false);
|
|
document.getElementById('load-model-btn').disabled = false;
|
|
}
|
|
}
|
|
|
|
// Update model status
|
|
async function updateModelStatus() {
|
|
try {
|
|
const response = await axios.get('/api/model-status');
|
|
const status = response.data;
|
|
|
|
if (status.loaded) {
|
|
showStatus('success', `Model loaded: ${status.current_model.name} on ${status.current_model.device}`);
|
|
} else if (status.available) {
|
|
showStatus('info', 'Model available but not loaded');
|
|
} else {
|
|
showStatus('warning', 'Model library not available');
|
|
}
|
|
} catch (error) {
|
|
console.error('❌ Failed to get model status:', error);
|
|
}
|
|
}
|
|
|
|
// Load data file list
|
|
async function loadDataFiles() {
|
|
try {
|
|
const response = await axios.get('/api/data-files');
|
|
const dataFiles = response.data;
|
|
|
|
const dataFileSelect = document.getElementById('data-file-select');
|
|
dataFileSelect.innerHTML = '<option value="">Please select data file</option>';
|
|
|
|
dataFiles.forEach(file => {
|
|
const option = document.createElement('option');
|
|
option.value = file.path;
|
|
option.textContent = `${file.name} (${file.size})`;
|
|
dataFileSelect.appendChild(option);
|
|
});
|
|
|
|
console.log('✅ Data file list loaded successfully:', dataFiles);
|
|
} catch (error) {
|
|
console.error('❌ Failed to load data file list:', error);
|
|
showStatus('error', 'Failed to load data file list');
|
|
}
|
|
}
|
|
|
|
// Load data file
|
|
async function loadData() {
|
|
const filePath = document.getElementById('data-file-select').value;
|
|
|
|
if (!filePath) {
|
|
showStatus('error', 'Please select a data file to load');
|
|
return;
|
|
}
|
|
|
|
try {
|
|
showLoading(true);
|
|
document.getElementById('load-data-btn').disabled = true;
|
|
|
|
const response = await axios.post('/api/load-data', {
|
|
file_path: filePath
|
|
});
|
|
|
|
if (response.data.success) {
|
|
currentDataFile = filePath;
|
|
currentDataInfo = response.data.data_info;
|
|
showDataInfo(response.data.data_info);
|
|
showStatus('success', response.data.message);
|
|
|
|
// Update prediction button status
|
|
if (modelLoaded) {
|
|
document.getElementById('predict-btn').disabled = false;
|
|
}
|
|
|
|
console.log('✅ Data loaded successfully:', response.data.data_info);
|
|
} else {
|
|
showStatus('error', response.data.error);
|
|
}
|
|
} catch (error) {
|
|
console.error('❌ Data loading failed:', error);
|
|
showStatus('error', `Data loading failed: ${error.response?.data?.error || error.message}`);
|
|
} finally {
|
|
showLoading(false);
|
|
document.getElementById('load-data-btn').disabled = false;
|
|
}
|
|
}
|
|
|
|
// Display data information
|
|
function showDataInfo(dataInfo) {
|
|
document.getElementById('data-info').style.display = 'block';
|
|
document.getElementById('data-rows').textContent = dataInfo.rows;
|
|
document.getElementById('data-cols').textContent = dataInfo.columns.length;
|
|
document.getElementById('data-time-range').textContent = `${dataInfo.start_date} to ${dataInfo.end_date}`;
|
|
document.getElementById('data-price-range').textContent = `${dataInfo.price_range.min.toFixed(4)} - ${dataInfo.price_range.max.toFixed(4)}`;
|
|
document.getElementById('data-timeframe').textContent = dataInfo.timeframe;
|
|
document.getElementById('data-prediction-cols').textContent = dataInfo.prediction_columns.join(', ');
|
|
|
|
// Initialize time window slider
|
|
initializeTimeWindowSlider(dataInfo);
|
|
}
|
|
|
|
// Time window slider related variables
|
|
let sliderData = null;
|
|
let isDragging = false;
|
|
let currentHandle = null;
|
|
|
|
// Initialize time window slider
|
|
function initializeTimeSlider() {
|
|
// Set up slider event listeners
|
|
setupSliderEventListeners();
|
|
}
|
|
|
|
// Set up slider event listeners
|
|
function setupSliderEventListeners() {
|
|
const startHandle = document.getElementById('start-handle');
|
|
const endHandle = document.getElementById('end-handle');
|
|
const track = document.querySelector('.slider-track');
|
|
|
|
// Start dragging
|
|
startHandle.addEventListener('mousedown', (e) => {
|
|
isDragging = true;
|
|
currentHandle = 'start';
|
|
e.preventDefault();
|
|
});
|
|
|
|
endHandle.addEventListener('mousedown', (e) => {
|
|
isDragging = true;
|
|
currentHandle = 'end';
|
|
e.preventDefault();
|
|
});
|
|
|
|
// Dragging
|
|
document.addEventListener('mousemove', (e) => {
|
|
if (!isDragging) return;
|
|
|
|
const rect = track.getBoundingClientRect();
|
|
const x = e.clientX - rect.left;
|
|
const percentage = Math.max(0, Math.min(1, x / rect.width));
|
|
|
|
if (currentHandle === 'start') {
|
|
updateStartHandle(percentage);
|
|
} else if (currentHandle === 'end') {
|
|
updateEndHandle(percentage);
|
|
}
|
|
|
|
updateSliderFromHandles();
|
|
});
|
|
|
|
// End dragging
|
|
document.addEventListener('mouseup', () => {
|
|
isDragging = false;
|
|
currentHandle = null;
|
|
});
|
|
|
|
// Click track to set position directly
|
|
track.addEventListener('click', (e) => {
|
|
const rect = track.getBoundingClientRect();
|
|
const x = e.clientX - rect.left;
|
|
const percentage = Math.max(0, Math.min(1, x / rect.width));
|
|
|
|
// Determine which handle is closer to the click position
|
|
const startHandle = document.getElementById('start-handle');
|
|
const endHandle = document.getElementById('end-handle');
|
|
const startRect = startHandle.getBoundingClientRect();
|
|
const endRect = endHandle.getBoundingClientRect();
|
|
|
|
if (Math.abs(x - (startRect.left - rect.left)) < Math.abs(x - (endRect.left - rect.left))) {
|
|
updateStartHandle(percentage);
|
|
} else {
|
|
updateEndHandle(percentage);
|
|
}
|
|
|
|
updateSliderFromHandles();
|
|
});
|
|
}
|
|
|
|
// Update start handle position
|
|
function updateStartHandle(percentage) {
|
|
const startHandle = document.getElementById('start-handle');
|
|
const selection = document.getElementById('slider-selection');
|
|
|
|
// Fixed window size of 520 data points
|
|
const windowSize = 520;
|
|
const totalRows = sliderData ? sliderData.totalRows : 1000;
|
|
const windowPercentage = windowSize / totalRows;
|
|
|
|
// Ensure start handle doesn't cause window to exceed data range
|
|
if (percentage + windowPercentage > 1) {
|
|
percentage = 1 - windowPercentage;
|
|
}
|
|
|
|
startHandle.style.left = (percentage * 100) + '%';
|
|
selection.style.left = (percentage * 100) + '%';
|
|
selection.style.width = (windowPercentage * 100) + '%';
|
|
|
|
// Automatically adjust end handle position to maintain fixed window size
|
|
const endHandle = document.getElementById('end-handle');
|
|
endHandle.style.left = ((percentage + windowPercentage) * 100) + '%';
|
|
}
|
|
|
|
// Update end handle position
|
|
function updateEndHandle(percentage) {
|
|
const endHandle = document.getElementById('end-handle');
|
|
const selection = document.getElementById('slider-selection');
|
|
|
|
// Fixed window size of 520 data points
|
|
const windowSize = 520;
|
|
const totalRows = sliderData ? sliderData.totalRows : 1000;
|
|
const windowPercentage = windowSize / totalRows;
|
|
|
|
// Ensure end handle doesn't cause window to exceed data range
|
|
if (percentage - windowPercentage < 0) {
|
|
percentage = windowPercentage;
|
|
}
|
|
|
|
endHandle.style.left = (percentage * 100) + '%';
|
|
selection.style.left = ((percentage - windowPercentage) * 100) + '%';
|
|
selection.style.width = (windowPercentage * 100) + '%';
|
|
|
|
// Automatically adjust start handle position to maintain fixed window size
|
|
const startHandle = document.getElementById('start-handle');
|
|
startHandle.style.left = ((percentage - windowPercentage) * 100) + '%';
|
|
}
|
|
|
|
// Update slider display based on handle positions
|
|
function updateSliderFromHandles() {
|
|
const startHandle = document.getElementById('start-handle');
|
|
const endHandle = document.getElementById('end-handle');
|
|
|
|
const startPercentage = parseFloat(startHandle.style.left) / 100;
|
|
const endPercentage = parseFloat(endHandle.style.left) / 100;
|
|
|
|
if (!sliderData) return;
|
|
|
|
// Calculate selected time range
|
|
const totalTime = sliderData.endDate.getTime() - sliderData.startDate.getTime();
|
|
const startTime = sliderData.startDate.getTime() + (totalTime * startPercentage);
|
|
const endTime = sliderData.startDate.getTime() + (totalTime * endPercentage);
|
|
|
|
const startDate = new Date(startTime);
|
|
const endDate = new Date(endTime);
|
|
|
|
// Update display information
|
|
document.getElementById('window-start').textContent = `Start: ${startDate.toLocaleDateString()}`;
|
|
document.getElementById('window-end').textContent = `End: ${endDate.toLocaleDateString()}`;
|
|
|
|
// Display fixed window size
|
|
document.getElementById('window-size').textContent = `Window Size: 400 + 120 = 520 data points (fixed)`;
|
|
|
|
// Input field values remain fixed
|
|
document.getElementById('lookback').value = 400;
|
|
document.getElementById('pred-len').value = 120;
|
|
}
|
|
|
|
// Update slider based on input fields
|
|
function updateSliderFromInputs() {
|
|
if (!sliderData) return;
|
|
|
|
// Fixed window size: 400 + 120 = 520 data points
|
|
const lookback = 400;
|
|
const predLen = 120;
|
|
const windowSize = lookback + predLen; // Fixed at 520
|
|
|
|
// Calculate slider position
|
|
const totalRows = sliderData.totalRows;
|
|
|
|
if (windowSize > totalRows) {
|
|
// If window size exceeds total data amount, show error
|
|
showStatus('error', `Insufficient data, need at least ${windowSize} data points, currently only ${totalRows} available`);
|
|
return;
|
|
}
|
|
|
|
// Calculate slider position (default select first half of data)
|
|
const startPercentage = 0.1; // Start from 10%
|
|
const endPercentage = startPercentage + (windowSize / totalRows);
|
|
|
|
// Update handle positions
|
|
updateStartHandle(startPercentage);
|
|
updateEndHandle(endPercentage);
|
|
|
|
// Update display information
|
|
updateSliderFromHandles();
|
|
}
|
|
|
|
// Initialize time window slider
|
|
function initializeTimeWindowSlider(dataInfo) {
|
|
sliderData = {
|
|
startDate: new Date(dataInfo.start_date),
|
|
endDate: new Date(dataInfo.end_date),
|
|
totalRows: dataInfo.rows,
|
|
timeframe: dataInfo.timeframe
|
|
};
|
|
|
|
// Set slider labels
|
|
document.getElementById('min-label').textContent = dataInfo.start_date.split('T')[0];
|
|
document.getElementById('max-label').textContent = dataInfo.end_date.split('T')[0];
|
|
|
|
// Initialize slider position
|
|
updateSliderFromInputs();
|
|
}
|
|
|
|
// Start prediction
|
|
async function startPrediction() {
|
|
if (!currentDataFile) {
|
|
showStatus('error', 'Please load data file first');
|
|
return;
|
|
}
|
|
|
|
if (!modelLoaded) {
|
|
showStatus('error', 'Please load model first');
|
|
return;
|
|
}
|
|
|
|
try {
|
|
showLoading(true);
|
|
document.getElementById('predict-btn').disabled = true;
|
|
|
|
const lookback = parseInt(document.getElementById('lookback').value);
|
|
const predLen = parseInt(document.getElementById('pred-len').value);
|
|
|
|
// Get selected time range from time window slider
|
|
const startHandle = document.getElementById('start-handle');
|
|
const startPercentage = parseFloat(startHandle.style.left) / 100;
|
|
|
|
if (!sliderData) {
|
|
showStatus('error', 'Time window slider not initialized');
|
|
return;
|
|
}
|
|
|
|
// Calculate selected time range
|
|
const totalTime = sliderData.endDate.getTime() - sliderData.startDate.getTime();
|
|
const startTime = sliderData.startDate.getTime() + (totalTime * startPercentage);
|
|
const startDate = new Date(startTime);
|
|
|
|
// Get prediction quality parameters
|
|
const temperature = parseFloat(document.getElementById('temperature').value);
|
|
const topP = parseFloat(document.getElementById('top-p').value);
|
|
const sampleCount = parseInt(document.getElementById('sample-count').value);
|
|
|
|
let predictionParams = {
|
|
file_path: currentDataFile,
|
|
lookback: lookback,
|
|
pred_len: predLen,
|
|
start_date: startDate.toISOString().slice(0, 16), // Format as YYYY-MM-DDTHH:MM
|
|
temperature: temperature,
|
|
top_p: topP,
|
|
sample_count: sampleCount
|
|
};
|
|
|
|
console.log('🚀 Starting prediction, parameters:', predictionParams);
|
|
|
|
const response = await axios.post('/api/predict', predictionParams);
|
|
|
|
if (response.data.success) {
|
|
// Display prediction results
|
|
displayPredictionResult(response.data);
|
|
showStatus('success', response.data.message);
|
|
} else {
|
|
showStatus('error', response.data.error);
|
|
}
|
|
} catch (error) {
|
|
console.error('❌ Prediction failed:', error);
|
|
showStatus('error', `Prediction failed: ${error.response?.data?.error || error.message}`);
|
|
} finally {
|
|
showLoading(false);
|
|
document.getElementById('predict-btn').disabled = false;
|
|
}
|
|
}
|
|
|
|
// Display prediction results
|
|
function displayPredictionResult(result) {
|
|
// Display chart
|
|
const chartData = JSON.parse(result.chart);
|
|
Plotly.newPlot('chart', chartData.data, chartData.layout);
|
|
|
|
// Display comparison analysis (if actual data exists)
|
|
if (result.has_comparison) {
|
|
displayComparisonAnalysis(result);
|
|
} else {
|
|
document.getElementById('comparison-section').style.display = 'none';
|
|
}
|
|
}
|
|
|
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// Display comparison analysis
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function displayComparisonAnalysis(result) {
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document.getElementById('comparison-section').style.display = 'block';
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// Update comparison information
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document.getElementById('prediction-type').textContent = result.prediction_type;
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document.getElementById('comparison-data').textContent = `${result.actual_data.length} actual data points`;
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// Calculate error statistics
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const errorStats = getPredictionQuality(result.prediction_results, result.actual_data);
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// Display error statistics
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document.getElementById('mae').textContent = errorStats.mae.toFixed(4);
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document.getElementById('rmse').textContent = errorStats.rmse.toFixed(4);
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document.getElementById('mape').textContent = errorStats.mape.toFixed(2);
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|
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// Fill comparison table
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fillComparisonTable(result.prediction_results, result.actual_data);
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}
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// Calculate prediction quality metrics
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|
function getPredictionQuality(predictions, actuals) {
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if (!predictions || !actuals || predictions.length === 0 || actuals.length === 0) {
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return { mae: 0, rmse: 0, mape: 0 };
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}
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|
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const minLen = Math.min(predictions.length, actuals.length);
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let mae = 0, rmse = 0, mape = 0;
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|
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for (let i = 0; i < minLen; i++) {
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const pred = predictions[i];
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const act = actuals[i];
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|
|
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// Use closing price to calculate errors
|
|
const error = Math.abs(pred.close - act.close);
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const percentError = (error / act.close) * 100;
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|
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mae += error;
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|
rmse += error * error;
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mape += percentError;
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}
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|
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mae /= minLen;
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|
rmse = Math.sqrt(rmse / minLen);
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mape /= minLen;
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|
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return { mae, rmse, mape };
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|
}
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|
|
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// Fill comparison table
|
|
function fillComparisonTable(predictions, actuals) {
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|
const tbody = document.getElementById('comparison-tbody');
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|
tbody.innerHTML = '';
|
|
|
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const minLen = Math.min(predictions.length, actuals.length);
|
|
|
|
for (let i = 0; i < minLen; i++) {
|
|
const pred = predictions[i];
|
|
const act = actuals[i];
|
|
|
|
const row = document.createElement('tr');
|
|
row.innerHTML = `
|
|
<td>${new Date(pred.timestamp).toLocaleString()}</td>
|
|
<td>${act.open.toFixed(4)}</td>
|
|
<td>${pred.open.toFixed(4)}</td>
|
|
<td>${act.high.toFixed(4)}</td>
|
|
<td>${pred.high.toFixed(4)}</td>
|
|
<td>${act.low.toFixed(4)}</td>
|
|
<td>${pred.low.toFixed(4)}</td>
|
|
<td>${act.close.toFixed(4)}</td>
|
|
<td>${pred.close.toFixed(4)}</td>
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|
`;
|
|
tbody.appendChild(row);
|
|
}
|
|
}
|
|
|
|
// Set up event listeners
|
|
function setupEventListeners() {
|
|
// Load model button
|
|
document.getElementById('load-model-btn').addEventListener('click', loadModel);
|
|
|
|
// Load data button
|
|
document.getElementById('load-data-btn').addEventListener('click', loadData);
|
|
|
|
// Prediction button
|
|
document.getElementById('predict-btn').addEventListener('click', startPrediction);
|
|
|
|
// Prediction quality parameter sliders
|
|
document.getElementById('temperature').addEventListener('input', function() {
|
|
document.getElementById('temperature-value').textContent = this.value;
|
|
});
|
|
|
|
document.getElementById('top-p').addEventListener('input', function() {
|
|
document.getElementById('top-p-value').textContent = this.value;
|
|
});
|
|
|
|
// Update slider when lookback window size changes
|
|
document.getElementById('lookback').addEventListener('input', updateSliderFromInputs);
|
|
document.getElementById('pred-len').addEventListener('input', updateSliderFromInputs);
|
|
}
|
|
|
|
// Display status information
|
|
function showStatus(type, message) {
|
|
const statusDiv = document.getElementById('model-status');
|
|
statusDiv.className = `status ${type}`;
|
|
statusDiv.textContent = message;
|
|
statusDiv.style.display = 'block';
|
|
|
|
// Auto-hide
|
|
setTimeout(() => {
|
|
statusDiv.style.display = 'none';
|
|
}, 5000);
|
|
}
|
|
|
|
// Show/hide loading status
|
|
function showLoading(show) {
|
|
const loadingDiv = document.getElementById('loading');
|
|
if (show) {
|
|
loadingDiv.classList.add('show');
|
|
} else {
|
|
loadingDiv.classList.remove('show');
|
|
}
|
|
}
|
|
</script>
|
|
</body>
|
|
</html>
|