Fix numpy warnings: MaskedArray partition et Mean of empty slice

- Convert MaskedArray to ndarray avant np.percentile() via
  np.asarray(data.compressed()) et np.ma.filled(data, np.nan)
- Supprimer RuntimeWarning "Mean of empty slice" dans MSRM et
  ondelette avec warnings.catch_warnings()
- Ajout import warnings dans visualizations.py

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

lidar_pipeline/visualizations.py

@@ -6,6 +6,7 @@ parameters and returns the path to the output GeoTIFF file, or None on error.
 
 import logging
 import time
+import warnings
 from pathlib import Path
 
 import numpy as np
@@ -391,8 +392,10 @@ def generate_mslrm(dem_file, basename, vis_dir, resolution):
             lrm_stack.append(lrm_norm.astype(np.float32))
 
         lrm_array = np.array(lrm_stack)
-        with np.errstate(invalid='ignore'):
-            mslrm = np.sqrt(np.nanmean(lrm_array ** 2, axis=0))
+        with np.errstate(invalid='ignore', divide='ignore'):
+            with warnings.catch_warnings():
+                warnings.filterwarnings('ignore', message='Mean of empty slice')
+                mslrm = np.sqrt(np.nanmean(lrm_array ** 2, axis=0))
         mslrm[nan_mask] = np.nan
         _save_tif(output, mslrm.astype(np.float32), transform, crs)
         logger.info(f"  ✓ MSRM terminé ({time.time()-t0:.1f}s){gpu_tag}")
@@ -659,8 +662,10 @@ def generate_wavelet(dem_file, basename, vis_dir, resolution):
             response = response / std_val
             wavelet_stack.append(response)
 
-        with np.errstate(invalid='ignore'):
-            combined = np.sqrt(np.nanmean(np.array(wavelet_stack) ** 2, axis=0))
+        with np.errstate(invalid='ignore', divide='ignore'):
+            with warnings.catch_warnings():
+                warnings.filterwarnings('ignore', message='Mean of empty slice')
+                combined = np.sqrt(np.nanmean(np.array(wavelet_stack) ** 2, axis=0))
         combined[nan_mask] = np.nan
 
         _save_tif(output, combined.astype(np.float32), transform, crs)