Suppression éclairage solaire, GPU accéléré, --file multi, tests unitaires

- Suppression de generate_solar (éclairage solaire) des visualisations
- Accélération GPU de hillshade, slope, aspect, curvature, depressions,
  anomalies, roughness, texture GLCM, flow (sink filling)
- Nettoyage mémoire GPU entre visualisations (gpu_cleanup)
- Correction OOM texture GLCM: calcul entropie bin par bin au lieu d'un
  tableau 3D massif sur GPU
- Correction bug: xp_minimum_filter manquant dans imports visualizations
- Option --file accepte plusieurs noms complets sans extension
- run.sh affiche l'aide si appelé sans arguments
- Option --test pour exécuter les tests unitaires dans Docker
- Filtre ReturnNumber>=1 intégré dans le pipeline PDAL (plus d'erreur SMRF)
- 60 tests unitaires: GPU, visualisations, rendering, DTM, pipeline, CLI
- Ajout pytest au Dockerfile

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

lidar_pipeline/tests/test_rendering.py

@@ -0,0 +1,98 @@
+"""Tests for rendering module (colormaps, tif_to_png)."""
+
+import numpy as np
+import rasterio
+from rasterio.transform import from_bounds
+import pytest
+from pathlib import Path
+
+
+def _make_test_tif(tmp_path, data=None, size=50):
+    """Create a small test GeoTIFF and return its path."""
+    if data is None:
+        rng = np.random.default_rng(42)
+        data = rng.normal(0, 1, (size, size)).astype(np.float32)
+
+    transform = from_bounds(660000, 6700000, 661000, 6701000, size, size)
+    tif_file = tmp_path / "test_vis.tif"
+    with rasterio.open(
+        tif_file, 'w', driver='GTiff', height=size, width=size,
+        count=1, dtype='float32', crs='EPSG:2154', transform=transform,
+        compress='lzw'
+    ) as dst:
+        dst.write(data, 1)
+    return tif_file
+
+
+class TestColormaps:
+    def test_colormaps_dict_exists(self):
+        from lidar_pipeline.rendering import COLORMAPS
+        assert isinstance(COLORMAPS, dict)
+
+    def test_all_viz_steps_have_colormaps(self):
+        """Every VIZ_STEPS entry should have a corresponding COLORMAPS entry or render correctly."""
+        from lidar_pipeline.pipeline import VIZ_STEPS
+        from lidar_pipeline.rendering import COLORMAPS
+        # Some viz names differ from colormap keys
+        name_map = {
+            'pos_open': 'positive_openness',
+            'neg_open': 'negative_openness',
+        }
+        # IGN overlays (ortho, topo) are RGB images — no colormap needed
+        skip = {'ortho', 'topo'}
+        for name, _ in VIZ_STEPS:
+            if name in skip:
+                continue
+            cmap_key = name_map.get(name, name)
+            assert cmap_key in COLORMAPS, f"Missing colormap for: {name} (looked as {cmap_key})"
+
+    def test_colormap_has_required_keys(self):
+        """Each colormap entry must have cmap, title, legend, description."""
+        from lidar_pipeline.rendering import COLORMAPS
+        required = {'cmap', 'title', 'legend', 'description'}
+        for name, entry in COLORMAPS.items():
+            missing = required - set(entry.keys())
+            assert not missing, f"Colormap '{name}' missing keys: {missing}"
+
+
+class TestTifToPng:
+    def test_converts_tif_to_webp(self, tmp_path):
+        from lidar_pipeline.rendering import tif_to_png
+        tif_file = _make_test_tif(tmp_path)
+        result = tif_to_png(tif_file, tmp_path, 5.0)
+        assert result is not None
+        assert result.exists()
+        assert result.suffix == '.webp'
+
+    def test_removes_source_tif(self, tmp_path):
+        from lidar_pipeline.rendering import tif_to_png
+        tif_file = _make_test_tif(tmp_path)
+        assert tif_file.exists()
+        tif_to_png(tif_file, tmp_path, 5.0)
+        assert not tif_file.exists(), "Source TIF should be deleted after conversion"
+
+    def test_webp_has_content(self, tmp_path):
+        from lidar_pipeline.rendering import tif_to_png
+        tif_file = _make_test_tif(tmp_path)
+        result = tif_to_png(tif_file, tmp_path, 5.0)
+        assert result.stat().st_size > 1000  # Must be a real image
+
+
+class TestApplyColormap:
+    def test_symmetric_mode(self, tmp_path):
+        from lidar_pipeline.rendering import COLORMAPS, tif_to_png
+        # LRM uses symmetric mode
+        data = np.random.default_rng(42).normal(0, 0.5, (50, 50)).astype(np.float32)
+        tif_file = _make_test_tif(tmp_path, data)
+        result = tif_to_png(tif_file, tmp_path, 5.0)
+        assert result is not None
+        assert result.exists()
+
+    def test_percentile_mode(self, tmp_path):
+        from lidar_pipeline.rendering import tif_to_png
+        # Most visualizations use percentile mode
+        data = np.random.default_rng(42).normal(50, 10, (50, 50)).astype(np.float32)
+        tif_file = _make_test_tif(tmp_path, data)
+        result = tif_to_png(tif_file, tmp_path, 5.0)
+        assert result is not None
+        assert result.exists()