Handle empty point clouds gracefully at every pipeline stage

Fixes "zero-size array to reduction operation" crash on corrupt/incomplete
LAZ files. Added checks at each step:

- validate_laz(): check point_count > 0 via laspy header, parse PDAL
  info JSON for point count when using PDAL fallback
- detect_ground_method(): return 'smrf' default if point cloud is empty
  after PDAL conversion instead of crashing on np.max(empty_array)
- _read_with_pdal(): log warning and return None if converted file has
  0 points
- create_dtm_fast(): fail gracefully if ground file has 0 points
- classify_ground(): check output file size after PDAL pipeline to
  catch empty ground classifications early

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

lidar_pipeline/dtm.py

@@ -128,17 +128,21 @@ def validate_laz(laz_file):
     """Quick integrity check for a LAZ/LAS file.
 
     Tries laspy first (fast header read), then PDAL as fallback for COPC files
-    that laspy cannot read.
+    that laspy cannot read. Also checks that the file contains points.
 
     Returns:
-        True if file is readable, False otherwise.
+        True if file is readable and contains points, False otherwise.
     """
     # Try laspy first (fast)
     import laspy
     try:
         with laspy.open(str(laz_file)) as f:
             header = f.header
-            _ = header.point_count
+            point_count = header.point_count
+            if point_count == 0:
+                logger.error(f"  ✗ Fichier vide (0 points): {laz_file.name}")
+                logger.error(f"    → Re-télécharger depuis https://ign.fr/lidar-hd")
+                return False
         return True
     except Exception:
         pass
@@ -151,6 +155,17 @@ def validate_laz(laz_file):
             capture_output=True, text=True, timeout=30
         )
         if result.returncode == 0:
+            # Check point count from PDAL info output
+            import json as _json
+            try:
+                info = _json.loads(result.stdout)
+                count = info.get('summary', {}).get('num_points', 0)
+                if count == 0:
+                    logger.error(f"  ✗ Fichier vide (0 points PDAL): {laz_file.name}")
+                    logger.error(f"    → Re-télécharger depuis https://ign.fr/lidar-hd")
+                    return False
+            except Exception:
+                pass  # Can't parse — assume valid
             return True
         logger.error(f"  ✗ Fichier illisible: {laz_file.name}")
         logger.error(f"    PDAL: {result.stderr.strip()[:200]}")
@@ -200,6 +215,9 @@ def _read_with_pdal(laz_file):
             os.unlink(tmp_path)
         except Exception:
             pass
+        if len(las.points) == 0:
+            logger.warning(f"  PDAL: conversion réussie mais 0 points")
+            return None
         return las
 
     except Exception as e:
@@ -238,6 +256,10 @@ def detect_ground_method(laz_file):
         return 'smrf'
 
     total_points = len(las.points)
+    if total_points == 0:
+        logger.warning(f"  Nuage vide (0 points) — méthode par défaut: SMRF")
+        return 'smrf'
+
     z = np.array(las.z)
 
     # Height variance (always available)
@@ -321,6 +343,11 @@ def classify_ground(laz_file, temp_dir, method='auto', force=False):
             ["pdal", "pipeline", str(pipeline_file)],
             capture_output=True, check=True
         )
+        # Verify that ground file has points
+        if output_las.exists() and output_las.stat().st_size < 100:
+            logger.error(f"  ✗ Fichier ground vide (taille < 100 octets)")
+            output_las.unlink(missing_ok=True)
+            return None
         logger.info(f"  ✓ Classification sol {method.upper()} terminée")
         return output_las
     except subprocess.CalledProcessError as e:
@@ -409,6 +436,10 @@ def create_dtm_fast(las_file, basename, dtm_dir, resolution, force=False):
             logger.error(f"  ✗ Impossible de lire {las_file.name}")
             return None
 
+    if len(las.points) == 0:
+        logger.error(f"  ✗ Fichier vide (0 points): {las_file.name}")
+        return None
+
     try:
 
         min_x, max_x = float(las.header.min[0]), float(las.header.max[0])