Akiba So
fc468464b2
Context: Build a spatial risk assessment system correlating air quality data with children's respiratory disease incidence across Wuhan. Approach: FastAPI backend serving PostGIS spatial queries, React frontend with Deck.gl maps, and a PyTorch SpatialTemporalGCN pipeline for multi-day (1d/3d/7d) risk prediction. Changes: - backend/ — FastAPI API with auth (JWT), alerts, risk analysis, geocoded case data, grid statistics, and report endpoints - frontend/ — React dashboard with interactive risk maps, alert monitoring, district comparison charts, and timeline player - models/ — SpatialTemporalGCN model with trained weights and ONNX export for inference - scripts/ — ETL pipeline for weather + medical data, grid generation, feature engineering, training, and daily inference - deploy/ — Docker Compose configs for backend, frontend, and MLflow - docs/ — API docs, deployment guide, user guide, and code review Impact: Enables spatial risk visualization, alert monitoring, and ML-driven health risk forecasting for environmental health teams.
51 lines
1.1 KiB
JavaScript
51 lines
1.1 KiB
JavaScript
/** @type {import('tailwindcss').Config} */
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export default {
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content: [
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"./index.html",
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"./src/**/*.{js,ts,jsx,tsx}",
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],
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theme: {
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extend: {
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colors: {
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primary: {
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DEFAULT: '#2563EB',
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light: '#3B82F6',
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muted: '#DBEAFE',
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},
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success: {
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DEFAULT: '#059669',
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light: '#D1FAE5',
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},
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warning: {
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DEFAULT: '#D97706',
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light: '#FEF3C7',
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},
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danger: {
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DEFAULT: '#DC2626',
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light: '#FEE2E2',
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},
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bg: {
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page: '#F8FAFC',
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card: '#FFFFFF',
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hover: '#F1F5F9',
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active: '#E2E8F0',
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},
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text: {
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primary: '#1E293B',
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secondary: '#64748B',
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muted: '#94A3B8',
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},
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border: {
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DEFAULT: '#E2E8F0',
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light: '#F1F5F9',
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},
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},
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fontFamily: {
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sans: ['Inter', 'Noto Sans SC', 'system-ui', 'sans-serif'],
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display: ['Source Sans Pro', 'sans-serif'],
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},
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},
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},
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plugins: [],
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}
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