Remove RRIM and Multi-Hillshade RGB, fix DTM resolution reuse bug, add --init to docker run

- Remove generate_rrim, generate_multi_hillshade, _compute_openness_both
- Remove corresponding VIZ_STEPS entries, COLORMAPS, RGB_LEGENDS, and tests
- Fix DTM resolution mismatch: existing DTM at different resolution is now
  regenerated instead of silently reused
- Propagate actual DTM resolution to visualizations and rendering
- Add --init to docker run commands for proper signal handling on Ctrl+C
- Add .playwright-mcp/ to .gitignore

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

lidar_pipeline/tests/test_visualizations.py

@@ -201,71 +201,6 @@ class TestFlow:
             assert np.nanmin(valid) >= 0
 
 
-class TestRRIM:
-    def test_generates_tif(self, synthetic_dem, tmp_output_dir):
-        from lidar_pipeline.visualizations import generate_rrim
-        result = generate_rrim(synthetic_dem, "test", tmp_output_dir, 5.0)
-        assert result is not None
-        assert result.exists()
-        assert result.suffix == ".tif"
-
-    def test_rrim_is_rgb_3band(self, synthetic_dem, tmp_output_dir):
-        import rasterio
-        from lidar_pipeline.visualizations import generate_rrim
-        result = generate_rrim(synthetic_dem, "test", tmp_output_dir, 5.0)
-        with rasterio.open(result) as src:
-            assert src.count == 3, f"Expected 3 bands, got {src.count}"
-            assert src.dtypes[0] == 'uint8'
-
-    def test_rrim_values_0_255(self, synthetic_dem, tmp_output_dir):
-        import rasterio
-        from lidar_pipeline.visualizations import generate_rrim
-        result = generate_rrim(synthetic_dem, "test", tmp_output_dir, 5.0)
-        with rasterio.open(result) as src:
-            for band in range(1, 4):
-                data = src.read(band)
-                assert data.min() >= 0
-                assert data.max() <= 255
-
-    def test_rrim_no_nan(self, synthetic_dem, tmp_output_dir):
-        """RRIM is uint8 RGB — NaN zones are set to 0 (black)."""
-        import rasterio
-        from lidar_pipeline.visualizations import generate_rrim
-        result = generate_rrim(synthetic_dem, "test", tmp_output_dir, 5.0)
-        with rasterio.open(result) as src:
-            # uint8 bands should not have NaN
-            for band in range(1, 4):
-                data = src.read(band)
-                assert not np.isnan(data).any(), f"Band {band} has NaN values"
-
-
-class TestMultiHillshade:
-    def test_generates_tif(self, synthetic_dem, tmp_output_dir):
-        from lidar_pipeline.visualizations import generate_multi_hillshade
-        result = generate_multi_hillshade(synthetic_dem, "test", tmp_output_dir, 5.0)
-        assert result is not None
-        assert result.exists()
-        assert result.suffix == ".tif"
-
-    def test_multi_hillshade_is_rgb_3band(self, synthetic_dem, tmp_output_dir):
-        import rasterio
-        from lidar_pipeline.visualizations import generate_multi_hillshade
-        result = generate_multi_hillshade(synthetic_dem, "test", tmp_output_dir, 5.0)
-        with rasterio.open(result) as src:
-            assert src.count == 3, f"Expected 3 bands, got {src.count}"
-            assert src.dtypes[0] == 'uint8'
-
-    def test_multi_hillshade_values_0_255(self, synthetic_dem, tmp_output_dir):
-        import rasterio
-        from lidar_pipeline.visualizations import generate_multi_hillshade
-        result = generate_multi_hillshade(synthetic_dem, "test", tmp_output_dir, 5.0)
-        with rasterio.open(result) as src:
-            for band in range(1, 4):
-                data = src.read(band)
-                assert data.min() >= 0
-                assert data.max() <= 255
-
-
 class TestLocalDominance:
     def test_generates_tif(self, synthetic_dem, tmp_output_dir):
         from lidar_pipeline.visualizations import generate_local_dominance