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| import os | |
| from typing import List, Dict | |
| import matplotlib | |
| matplotlib.use("Agg") | |
| import matplotlib.pyplot as plt | |
| from .data_loader import NDVIPoint | |
| class CropImageGenerator: | |
| def __init__(self, config_cls): | |
| self.cfg = config_cls | |
| def generate_growth_visualization( | |
| self, | |
| ndvi_series: List[NDVIPoint], | |
| forecast: Dict, | |
| rotation_plan: List[Dict], | |
| output_path: str, | |
| scenario: str, | |
| ): | |
| if not ndvi_series: | |
| raise ValueError("NDVI series is empty") | |
| dates = [p.date for p in ndvi_series] | |
| ndvi_values = [p.ndvi for p in ndvi_series] | |
| evi_values = [p.evi for p in ndvi_series] | |
| timeline = forecast.get("growth_timeline", []) | |
| fig, axes = plt.subplots(2, 2, figsize=(10, 6)) | |
| ax1, ax2, ax3, ax4 = axes.ravel() | |
| ax1.plot(dates, ndvi_values, label="NDVI") | |
| ax1.plot(dates, evi_values, linestyle="--", label="EVI") | |
| ax1.set_title("Historical Vegetation Indices") | |
| ax1.set_xlabel("Date") | |
| ax1.set_ylabel("Index") | |
| ax1.legend() | |
| ax1.grid(True, alpha=0.3) | |
| if timeline: | |
| f_dates = [t["date"] for t in timeline] | |
| growth_scores = [t["growth_score"] for t in timeline] | |
| ax2.plot(f_dates, growth_scores) | |
| ax2.set_title("Forecast Growth Trajectory") | |
| ax2.set_xlabel("Date") | |
| ax2.set_ylabel("Growth score") | |
| ax2.tick_params(axis="x", rotation=45) | |
| ax2.grid(True, alpha=0.3) | |
| crops = [r["crop"] for r in rotation_plan] | |
| health = [r.get("rotation_health", 0.5) for r in rotation_plan] | |
| ax3.bar(range(len(crops)), health) | |
| ax3.set_xticks(range(len(crops))) | |
| ax3.set_xticklabels(crops, rotation=30, ha="right") | |
| ax3.set_ylim(0, 1) | |
| ax3.set_title("Rotation Health by Season") | |
| ax3.set_ylabel("Health index") | |
| yield_index = forecast.get("yield_index", 0.0) | |
| stress_risk = forecast.get("stress_risk", 0.0) | |
| soil_score = forecast.get("soil_score", 0.0) | |
| crop_suggestions = forecast.get("crop_suggestions", [])[:3] | |
| ax4.axis("off") | |
| lines = [ | |
| f"Scenario: {scenario}", | |
| f"Yield index: {yield_index:.2f}", | |
| f"Stress risk: {stress_risk:.2f}", | |
| f"Soil score: {soil_score:.2f}", | |
| "", | |
| "Top crop suggestions:", | |
| ] | |
| for s in crop_suggestions: | |
| lines.append(f"- {s['crop']}: {s['suitability']:.2f}") | |
| ax4.text(0.02, 0.98, "\n".join(lines), va="top", ha="left") | |
| plt.tight_layout() | |
| os.makedirs(os.path.dirname(output_path), exist_ok=True) | |
| fig.savefig(output_path, dpi=120, bbox_inches="tight") | |
| plt.close(fig) | |