Numéroter les zones après tri, lire le journal par la fin et corriger l'aide -g
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@ -200,7 +200,8 @@ def _apply_colormap(data, tif_file, resolution=None):
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info = RGB_LEGENDS[key]
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return data, None, info['title'], info['legend'], info['description'], True, None, None
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# Find matching colormap — sort by key length descending so 'mslrm' matches before 'lrm'
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# Find matching colormap — tri par longueur décroissante : en cas de
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# chevauchement de mots-clés dans un nom de fichier, le plus long prime
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for key in sorted(COLORMAPS.keys(), key=len, reverse=True):
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info = COLORMAPS[key]
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if key in name:
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@ -369,8 +370,8 @@ def tif_to_png(tif_file, vis_dir, resolution, keep_tif=False, source_info=None,
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resolution: Grid resolution in m/px.
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keep_tif: If True, keep the source TIFF after conversion.
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source_info: Dict with method/date/basename for metadata.
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quality: Image quality (1-100). Use 100 for lossless. Default 95.
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output_format: Output format ('webp' or 'avif'). Default 'webp'.
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quality: Image quality (1-100). Use 100 for lossless. Default 98.
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output_format: Output format ('webp' or 'avif'). Default 'avif'.
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Returns:
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Path to output image file, or None on failure.
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@ -915,7 +916,8 @@ def generate_pdf_report(basename, vis_dir, pdf_dir, resolution):
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# Sort analysis files by archaeological priority
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order = ['mslrm', 'svf', 'negative_openness',
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'positive_openness', 'sailore', 'hillshade_multi',
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'flow_acc', 'solar', 'slope', 'roughness', 'wavelet']
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'flow_acc', 'solar', 'slope', 'roughness', 'wavelet',
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'aspect', 'anomaly']
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def sort_key(f):
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name = f.stem.lower()
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