refactor: reorganize project structure by moving core modules and update import paths in API server

2026-07-18 01:24:30 +07:00
parent abab846884
commit a82b2f6fa5
155 changed files with 25 additions and 370 deletions
@@ -0,0 +1,39 @@
+#!/usr/bin/env python
+# coding: utf-8
+import os
+import json
+import joblib
+import numpy as np
+from statsmodels.tsa.statespace.sarimax import SARIMAX
+from core.ndvi_data_loader import NDVITimeSeriesDataset
+
+print("=" * 70)
+print("🚀 Training Statistical Model (SARIMA) for NDVI (REAL DATA & CPU)")
+print("=" * 70)
+
+dataset = NDVITimeSeriesDataset(sequence_length=10, spatial=False)
+
+# Flatten data for ARIMA (1D series)
+timeseries = []
+for x, y in dataset:
+    timeseries.append(y.item())
+
+print(f"\n[TRAIN] Bắt đầu Training SARIMA với {len(timeseries)} điểm dữ liệu...")
+# Use a simple ARIMA (1, 1, 1)
+model = SARIMAX(timeseries, order=(1, 1, 1))
+results = model.fit(disp=False)
+mse = np.mean(results.resid ** 2)
+
+model_dir = "ndvi_forecast_model"
+model_path = os.path.join(model_dir, "ndvi_statistical_real.joblib")
+joblib.dump(results, model_path)
+print(f"\n[SAVE] Model saved to {model_path}")
+
+with open(os.path.join(model_dir, "ndvi_statistical_real_info.json"), "w") as f:
+    json.dump({
+        "model_type": "Statistical SARIMA (Real Data & CPU)",
+        "target": "NDVI",
+        "rmse": float(mse**0.5),
+        "mae": float(np.mean(np.abs(results.resid)))
+    }, f, indent=2)
+print("[SAVE] Model info saved.")