8ca65155db
- webapp.py: FastAPI serving the continuous map (port 8973) with /api/preview, /api/generate and /api/status; tiles are downloaded from IGN and processed in a logged subprocess, tracked live in a side "File de génération" panel that survives page reloads - fetch_ign.py: download missing 1 km LiDAR HD tiles from the IGN geoplateforme before processing - index.py: tile thumbnails and 500 m subtiles are now invalidated by mtime so regenerating a tile refreshes its cached images; progress logging per tile - dtm.py: back to the historical gap handling (small gaps filled by fillnodata only, larger holes left as nodata rendered black); lowest-return floor only via --bare-earth, IGN class selection via --ign-classes - cli.py: positional input now optional (--rebuild-index works alone) - docker-compose.yml: serve (GPU, port 8973) and process services; launch via docker compose only (documented in AGENTS.md/AGENTS.md) - tests: 131 passing, incl. regressions for thumbnail staleness, --rebuild-index without input, and nodata rendering
169 lines
7.3 KiB
Python
169 lines
7.3 KiB
Python
"""Tests for pipeline orchestration."""
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import pytest
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from pathlib import Path
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class TestVizSteps:
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def test_viz_steps_not_empty(self):
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from lidar_pipeline.pipeline import VIZ_STEPS
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assert len(VIZ_STEPS) > 0
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def test_viz_steps_have_callable_functions(self):
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from lidar_pipeline.pipeline import VIZ_STEPS
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for name, func in VIZ_STEPS:
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assert callable(func), f"VIZ_STEPS entry '{name}' is not callable"
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def test_viz_steps_names_unique(self):
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from lidar_pipeline.pipeline import VIZ_STEPS
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names = [name for name, _ in VIZ_STEPS]
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assert len(names) == len(set(names)), "VIZ_STEPS has duplicate names"
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def test_expected_visualization_count(self):
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"""Should have 16 visualizations (14 terrain + ortho + topo)."""
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from lidar_pipeline.pipeline import VIZ_STEPS
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assert len(VIZ_STEPS) == 16
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def test_ortho_and_topo_present(self):
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from lidar_pipeline.pipeline import VIZ_STEPS
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names = [name for name, _ in VIZ_STEPS]
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assert "ortho" in names
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assert "topo" in names
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class TestLidarArchaeoPipeline:
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def test_init_creates_dirs(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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output_dir = tmp_path / "output"
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pipeline = LidarArchaeoPipeline(str(input_dir), str(output_dir))
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assert (tmp_path / "output").exists()
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assert (tmp_path / "output" / "DTM").exists()
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assert (tmp_path / "output" / "visualisations").exists()
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assert (tmp_path / "output" / "temp").exists()
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def test_init_raises_on_missing_input(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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with pytest.raises(ValueError, match="introuvable"):
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LidarArchaeoPipeline("/nonexistent/path", str(tmp_path / "output"))
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def test_find_laz_files_empty(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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pipeline = LidarArchaeoPipeline(str(input_dir), str(tmp_path / "output"))
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files = pipeline.find_laz_files()
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assert files == []
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def test_find_laz_files(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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(input_dir / "test.laz").touch()
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(input_dir / "other.las").touch()
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(input_dir / "readme.txt").touch()
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pipeline = LidarArchaeoPipeline(str(input_dir), str(tmp_path / "output"))
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files = pipeline.find_laz_files()
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names = [f.name for f in files]
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assert "test.laz" in names
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assert "other.las" in names
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assert "readme.txt" not in names
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class TestDtmMethodSidecar:
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"""Méthode de classification enregistrée à côté du DTM (invalidation du cache)."""
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def test_missing_sidecar_matches(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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pipeline = LidarArchaeoPipeline(str(input_dir), str(tmp_path / "output"), ground_method='csf')
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# Aucun sidecar écrit → cache conservé (considéré compatible).
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assert pipeline._dtm_method_matches("tileA", "") is True
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def test_matching_method(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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pipeline = LidarArchaeoPipeline(str(input_dir), str(tmp_path / "output"), ground_method='csf')
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pipeline._write_dtm_method("tileA", "")
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assert pipeline._dtm_method_matches("tileA", "") is True
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def test_different_method_invalidates_cache(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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out = str(tmp_path / "output")
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LidarArchaeoPipeline(str(input_dir), out, ground_method='ign')._write_dtm_method("tileA", "")
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csf = LidarArchaeoPipeline(str(input_dir), out, ground_method='csf')
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assert csf._dtm_method_matches("tileA", "") is False
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def test_write_dtm_method(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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pipeline = LidarArchaeoPipeline(str(input_dir), str(tmp_path / "output"), ground_method='smrf')
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pipeline._write_dtm_method("tileA", "_r0p2")
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sidecar = tmp_path / "output" / "DTM" / "tileA_dtm_r0p2_method.txt"
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assert sidecar.exists()
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assert sidecar.read_text(encoding="utf-8").strip() == "smrf"
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assert pipeline._dtm_method_name("tileA", "_r0p2") == "smrf"
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# Le sidecar est un fichier .txt : il ne gêne pas la recherche des DTM .tif.
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dtm = tmp_path / "output" / "DTM" / "tileA_dtm_r0p2.tif"
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dtm.touch()
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assert [p.name for p in (tmp_path / "output" / "DTM").glob("*.tif")] == ["tileA_dtm_r0p2.tif"]
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def test_force_images_regenerates_existing(self, tmp_path):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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input_dir = tmp_path / "input"
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input_dir.mkdir()
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pipeline = LidarArchaeoPipeline(str(input_dir), str(tmp_path / "output"), output_format='avif')
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calls = []
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def fake_ortho(dem_file, basename, vis_dir, resolution):
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calls.append(basename)
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return vis_dir / f"{basename}_ortho.avif"
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pipeline.viz_steps = [('ortho', fake_ortho)]
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vis_dir = tmp_path / "output" / "visualisations" / "tileA"
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vis_dir.mkdir(parents=True)
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(vis_dir / "tileA_ortho.avif").touch()
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dtm = tmp_path / "dtm.tif"
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# Image existante, pas de force → ignorée (pas de régénération).
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pipeline.generate_all_visualizations(dtm, "tileA", resolution=0.5, vis_dir=vis_dir, force_images=False)
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assert calls == []
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# Image existante, force_images=True → régénérée.
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calls.clear()
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pipeline.generate_all_visualizations(dtm, "tileA", resolution=0.5, vis_dir=vis_dir, force_images=True)
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assert calls == ["tileA"]
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class TestEffectiveGroundMethod:
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def test_ign_label_encodes_classes(self):
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"""Les classes IGN sont encodées dans l'étiquette de cache (reclassification)."""
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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import tempfile
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with tempfile.TemporaryDirectory() as tmpdir:
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p = LidarArchaeoPipeline(tmpdir, tmpdir, ground_method='ign',
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ign_classes="sol,unclassified")
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assert p._effective_ground_method() == "ign_1_2"
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def test_ign_default_label(self):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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import tempfile
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with tempfile.TemporaryDirectory() as tmpdir:
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p = LidarArchaeoPipeline(tmpdir, tmpdir, ground_method='ign')
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assert p._effective_ground_method() == "ign"
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def test_other_methods_unchanged(self):
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from lidar_pipeline.pipeline import LidarArchaeoPipeline
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import tempfile
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with tempfile.TemporaryDirectory() as tmpdir:
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p = LidarArchaeoPipeline(tmpdir, tmpdir, ground_method='smrf',
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ign_classes="sol,unclassified")
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assert p._effective_ground_method() == "smrf"
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