51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
import rasterio
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import geopandas as gpd
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import numpy as np
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import matplotlib.pyplot as plt
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import os
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# --- CONFIG ---
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raster_path = os.path.join('geodata', 's2_2025.tif')
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geojson_path = os.path.join('geodata', 'Trinkbrunnen_Berlin.geojson')
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output_dir = os.path.join('datenvisualisierung')
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os.makedirs(output_dir, exist_ok=True)
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# --- LOAD RASTER ---
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with rasterio.open(raster_path) as src:
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map_img = src.read([1, 2, 3])
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map_img = np.transpose(map_img, (1, 2, 0))
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map_transform = src.transform
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map_crs = src.crs
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map_bounds = src.bounds
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map_width = src.width
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map_height = src.height
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# --- LOAD GEOJSON ---
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gdf = gpd.read_file(geojson_path)
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if gdf.crs != map_crs:
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gdf = gdf.to_crs(map_crs)
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# --- PROJECT POINTS TO PIXELS ---
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pixel_positions = []
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for geom in gdf.geometry:
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if geom and geom.type == 'Point':
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x, y = geom.x, geom.y
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px, py = ~map_transform * (x, y)
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pixel_positions.append((int(px), int(py)))
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# --- VISUALIZE ---
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plt.figure(figsize=(10, 10))
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plt.imshow(map_img)
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for px, py in pixel_positions:
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plt.scatter(px, py, c='deepskyblue', s=40, edgecolors='black', label='Trinkbrunnen')
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plt.title('Trinkbrunnen auf der Berlin-Karte')
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plt.axis('off')
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plt.savefig(os.path.join(output_dir, 'trinkbrunnen_karte.png'), bbox_inches='tight', dpi=200)
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plt.show()
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# --- EXPORT PIXEL POSITIONS FOR GAME ---
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# Save as npy for easy loading in pygame
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np.save('trinkbrunnen_pixel_positions.npy', np.array(pixel_positions))
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print(f"{len(pixel_positions)} Trinkbrunnen-Pixelpositionen wurden in trinkbrunnen_pixel_positions.npy gespeichert.")
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