#!/usr/bin/env python3
"""
Quick test: Verify feature extraction works
"""

import sys
import pandas as pd
import numpy as np
from pathlib import Path

sys.path.insert(0, str(Path(__file__).parent))

from harvest_date_pred_utils import extract_features, load_model_and_config

project_name = "angata"
base_storage = Path("../laravel_app/storage/app") / project_name / "Data"
CI_DATA_FILE = base_storage / "extracted_ci" / "ci_data_for_python" / "ci_data_for_python.csv"

print("="*80)
print("DEBUG: Feature Extraction Test")
print("="*80)

# Load model config
print("\n[1] Loading model config...")
model, config, scalers = load_model_and_config(Path("."))
print(f"  Config features: {config['features']}")
print(f"  Number of features: {len(config['features'])}")

# Load CI data
print("\n[2] Loading CI data...")
ci_data = pd.read_csv(CI_DATA_FILE, dtype={'field': str})
ci_data['Date'] = pd.to_datetime(ci_data['Date'])
print(f"  Columns: {ci_data.columns.tolist()}")
print(f"  Total rows: {len(ci_data)}")

# Test on a single field
test_field = "1"
field_data = ci_data[ci_data['field'] == test_field].sort_values('Date').reset_index(drop=True)
print(f"\n[3] Testing on field {test_field}...")
print(f"  Data points: {len(field_data)}")
print(f"  Date range: {field_data['Date'].min().date()} to {field_data['Date'].max().date()}")
print(f"  Columns in field data: {field_data.columns.tolist()}")
print(f"  Sample values:")
print(field_data[['Date', 'value']].head())

# Test feature extraction on first 50 days
print(f"\n[4] Extracting features for first 50 days...")
try:
    subset = field_data.iloc[:50].copy()
    features = extract_features(subset, config['features'], ci_column='value')
    print(f"  ✓ Success!")
    print(f"  Feature shape: {features.shape}")
    print(f"  Expected shape: (50, {len(config['features'])})")
    print(f"  Feature values sample (first 5 days):")
    for i in range(min(5, features.shape[0])):
        print(f"    Day {i}: {features[i]}")
except Exception as e:
    print(f"  ✗ Error: {e}")
    import traceback
    traceback.print_exc()

print("\n[5] Testing on growing windows...")
try:
    for window_size in [10, 20, 30, 50]:
        window_data = field_data.iloc[:window_size].copy()
        features = extract_features(window_data, config['features'], ci_column='value')
        print(f"  Window size {window_size}: shape={features.shape}, min={features.min():.4f}, max={features.max():.4f}")
except Exception as e:
    print(f"  ✗ Error: {e}")
    import traceback
    traceback.print_exc()

print("\n✓ Feature extraction test complete")