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| import json | |
| import random | |
| import math | |
| from pathlib import Path | |
| from PIL import Image, ImageFilter | |
| # Maharashtra approximate bounds | |
| LAT_MIN, LAT_MAX = 15.6, 22.0 | |
| LON_MIN, LON_MAX = 72.6, 80.9 | |
| # For the PNG, we want high resolution | |
| # width = degrees * pixels_per_degree | |
| PIXELS_PER_DEGREE = 50 # 50 pixels per degree gives ~415x320 image, which is fast to generate | |
| WIDTH = int((LON_MAX - LON_MIN) * PIXELS_PER_DEGREE) | |
| HEIGHT = int((LAT_MAX - LAT_MIN) * PIXELS_PER_DEGREE) | |
| def get_temp_color(temp): | |
| if temp <= 22: return (0, 0, 0, 0) | |
| if temp <= 25: return (254, 217, 118, 150) | |
| if temp <= 30: return (254, 178, 76, 180) | |
| if temp <= 35: return (253, 141, 60, 200) | |
| if temp <= 40: return (252, 78, 42, 220) | |
| if temp <= 43: return (227, 26, 28, 240) | |
| return (177, 0, 38, 255) | |
| def get_rain_color(rain): | |
| if rain <= 1: return (0, 0, 0, 0) | |
| if rain <= 10: return (198, 219, 239, 100) | |
| if rain <= 40: return (158, 202, 225, 150) | |
| if rain <= 80: return (107, 174, 214, 180) | |
| if rain <= 120: return (66, 146, 198, 200) | |
| if rain <= 160: return (33, 113, 181, 220) | |
| return (8, 69, 148, 255) | |
| def generate_rasters(out_dir): | |
| # Create empty images (RGBA) | |
| temp_img = Image.new('RGBA', (WIDTH, HEIGHT), (0, 0, 0, 0)) | |
| rain_img = Image.new('RGBA', (WIDTH, HEIGHT), (0, 0, 0, 0)) | |
| temp_pixels = temp_img.load() | |
| rain_pixels = rain_img.load() | |
| # Iterate over pixels | |
| for y in range(HEIGHT): | |
| # Image Y=0 is TOP (LAT_MAX), Y=HEIGHT is BOTTOM (LAT_MIN) | |
| lat = LAT_MAX - (y / PIXELS_PER_DEGREE) | |
| for x in range(WIDTH): | |
| # Image X=0 is LEFT (LON_MIN), X=WIDTH is RIGHT (LON_MAX) | |
| lon = LON_MIN + (x / PIXELS_PER_DEGREE) | |
| # Patchy rain simulation using overlapping sine waves (fake Perlin noise) | |
| patchiness = math.sin(lat * 5.0) * math.cos(lon * 5.0) + math.sin(lat * 2.1 + lon * 3.3) | |
| # Base temperature: hotter inland (east) | |
| temp_base = 25 + (lon - LON_MIN) * 2.5 | |
| # Base rain | |
| if patchiness > 0.8: | |
| rain = random.uniform(50, 200) # Heavy patch | |
| elif patchiness > 0.2: | |
| rain = random.uniform(5, 50) # Light patch | |
| else: | |
| rain = 0 | |
| temp = temp_base + random.uniform(-2, 2) | |
| temp = max(20, min(temp, 45)) | |
| temp_pixels[x, y] = get_temp_color(temp) | |
| rain_pixels[x, y] = get_rain_color(rain) | |
| # Apply a slight blur so the noise isn't too sharp, creating a smooth raster feel | |
| temp_img = temp_img.filter(ImageFilter.GaussianBlur(radius=3)) | |
| rain_img = rain_img.filter(ImageFilter.GaussianBlur(radius=5)) | |
| temp_img.save(out_dir / "temp_raster.png") | |
| rain_img.save(out_dir / "rain_raster.png") | |
| print(f"Saved temp_raster.png and rain_raster.png ({WIDTH}x{HEIGHT}) to {out_dir}") | |
| if __name__ == "__main__": | |
| out_dir = Path(__file__).parent.parent / "frontend" / "public" / "data" | |
| out_dir.mkdir(parents=True, exist_ok=True) | |
| generate_rasters(out_dir) | |