ed3e90ea89
- Web map: multi-select picker in the generation bar (aspect, slope, positive openness, anisotropic openness, wavelet) passed to the API; the layer panel is restricted to the same shortlist (PANEL_VIZ) and a refresh button rebuilds the index when new layers appear on disk; jobs started outside the UI are now adopted into the visible queue - Uniform colors across tiles: openness/anisotropic/sailore now store local z-scores, and all renderers use fixed ranges (0-3 sigma, SVF 0-1 physical, slope 0-30 deg) instead of per-tile percentile stretches - Ray-tracing falls back to CPU when VRAM is exhausted so openness and SVF no longer fail silently on shared GPUs - build_index merges visualizations available at only one resolution into the displayed tile so in-progress layers stay visible - 11 new tests (142 passing)
176 lines
7.2 KiB
Python
176 lines
7.2 KiB
Python
"""Tests du serveur web de génération de zones (webapp)."""
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def test_bbox_to_cells_single_km_cell():
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"""Une bbox couvrant ~1 km² retourne la cellule L93 correspondante."""
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from lidar_pipeline.webapp import bbox_to_cells
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# Cellule 1054,6882 : X∈[1054000,1055000], Y∈[6881000,6882000] (L93)
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from rasterio.warp import transform as warp_transform
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lons, lats = warp_transform('EPSG:2154', 'EPSG:4326',
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[1054100, 1054900], [6881100, 6881900])
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cells = bbox_to_cells(min(lons), min(lats), max(lons), max(lats))
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assert (1054, 6882) in cells
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# La sélection reste locale : pas de cellule lointaine
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for (c, r) in cells:
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assert abs(c - 1054) <= 1 and abs(r - 6882) <= 1
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def test_bbox_to_cells_empty_for_tiny_bbox():
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"""Une bbox quasi ponctuelle ne sélectionne rien (rétrécie sous 1 m)."""
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from lidar_pipeline.webapp import bbox_to_cells
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assert bbox_to_cells(7.850000, 48.930000, 7.850001, 48.930001) == []
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def test_processed_cells(tmp_path):
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"""processed_cells lit les dossiers de visualisations."""
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from lidar_pipeline.webapp import processed_cells
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vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_r0p2"
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vis.mkdir(parents=True)
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(vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_r0p2_aspect.avif").write_bytes(b"x")
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assert processed_cells(tmp_path) == {(1054, 6882)}
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def test_missing_cells_filters_processed(tmp_path):
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"""Les cellules déjà traitées sont exclues, les autres gardent leurs coins."""
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from lidar_pipeline.webapp import missing_cells_with_corners
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vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69"
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vis.mkdir(parents=True)
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(vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x")
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todo = missing_cells_with_corners([(1054, 6882), (1055, 6882)], tmp_path)
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assert len(todo) == 1
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assert todo[0]['col'] == 1055 and todo[0]['row'] == 6882
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assert len(todo[0]['corners']) == 4 # SW, SE, NE, NW
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def test_missing_cells_include_done(tmp_path):
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"""include_done=True conserve les cellules déjà traitées (régénération)."""
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from lidar_pipeline.webapp import missing_cells_with_corners
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vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69"
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vis.mkdir(parents=True)
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(vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x")
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todo = missing_cells_with_corners([(1054, 6882), (1055, 6882)], tmp_path,
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include_done=True)
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assert {(t['col'], t['row']) for t in todo} == {(1054, 6882), (1055, 6882)}
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def test_build_command_regenerate():
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"""regenerate=True ajoute --force --force-classification à la commande."""
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from lidar_pipeline.webapp import _build_command
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cmd = " ".join(_build_command([(1054, 6882)], regenerate=True))
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assert "--force" in cmd
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assert "--force-classification" in cmd
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cmd = " ".join(_build_command([(1054, 6882)]))
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assert "--force" not in cmd
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assert "--force-classification" not in cmd
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def test_build_command_ground_classification():
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"""La commande utilise la méthode de classification demandée (défaut : ign)."""
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from lidar_pipeline.webapp import _build_command, GROUND_CLASS_METHODS
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# Défaut : ign (pré-classification)
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cmd = _build_command([(1054, 6882)])
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i = cmd.index("--ground-classification")
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assert cmd[i + 1] == "ign"
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# Chaque méthode valide est transmise telle quelle, avec ou sans régénération
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for method in GROUND_CLASS_METHODS:
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for regenerate in (False, True):
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cmd = _build_command([(1054, 6882)], regenerate=regenerate, ground_class=method)
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i = cmd.index("--ground-classification")
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assert cmd[i + 1] == method
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assert ("--force" in cmd) == regenerate
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assert ("--force-classification" in cmd) == regenerate
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def test_build_command_default_viz_aspect():
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"""Sans choix de visualisation, la commande génère uniquement aspect."""
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from lidar_pipeline.webapp import _build_command
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cmd = _build_command([(1054, 6882)])
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i = cmd.index("--only")
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assert cmd[i + 1] == "aspect"
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def test_build_command_custom_viz():
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"""Les visualisations demandées sont passées à --only dans l'ordre."""
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from lidar_pipeline.webapp import _build_command
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cmd = _build_command([(1054, 6882)], viz=["aspect", "wavelet", "aniso_open"])
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i = cmd.index("--only")
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assert cmd[i + 1:i + 4] == ["aspect", "wavelet", "aniso_open"]
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def test_viz_step_names_match_pipeline():
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"""Les noms acceptés par l'API sont exactement les étapes VIZ_STEPS du pipeline."""
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from lidar_pipeline.webapp import _viz_step_names
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from lidar_pipeline.pipeline import VIZ_STEPS
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assert _viz_step_names() == [n for n, _ in VIZ_STEPS]
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def test_generate_rejects_unknown_viz():
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"""L'API refuse un nom de visualisation inconnu (HTTPException 400)."""
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from fastapi import HTTPException
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from lidar_pipeline.webapp import generate, GenerateRequest
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req = GenerateRequest(tiles=[[1054, 6882]], viz=["wavelet", "inconnu"])
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try:
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generate(req)
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assert False, "une HTTPException était attendue"
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except HTTPException as e:
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assert e.status_code == 400
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assert "inconnu" in e.detail
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def test_generate_accepts_wavelet_and_aniso():
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"""L'API accepte wavelet + aniso_open et les transmet à --only."""
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import subprocess
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import lidar_pipeline.webapp as webapp
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captured = {}
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def fake_popen(cmd, **kwargs):
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captured["cmd"] = cmd
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class _P:
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def wait(self):
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return 0
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def poll(self):
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return 0
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return _P()
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webapp.subprocess.Popen = fake_popen
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try:
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req = webapp.GenerateRequest(tiles=[[1054, 6882]],
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viz=["wavelet", "aniso_open"])
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result = webapp.generate(req)
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assert result["demarré"] is True
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i = captured["cmd"].index("--only")
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assert captured["cmd"][i + 1:i + 3] == ["wavelet", "aniso_open"]
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finally:
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webapp.subprocess.Popen = subprocess.Popen
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def test_available_layers_scans_disk(tmp_path, monkeypatch):
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"""/api/layers retourne les couches présentes (clé → label)."""
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import lidar_pipeline.webapp as webapp
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monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path)
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vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69"
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vis.mkdir(parents=True)
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(vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_wavelet.avif").write_bytes(b"x")
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layers = webapp.available_layers()
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assert layers.get("wavelet")
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assert "aspect" not in layers
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def test_rebuild_index_background(tmp_path, monkeypatch):
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"""POST /api/rebuild lance build_index en arrière-plan puis termine."""
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import time as _time
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import lidar_pipeline.webapp as webapp
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import lidar_pipeline.index as index_mod
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calls = []
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monkeypatch.setattr(index_mod, "build_index", lambda out: calls.append(out))
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assert webapp.rebuild_index()["demarré"] is True
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for _ in range(100):
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if not webapp.rebuild_status()["running"]:
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break
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_time.sleep(0.05)
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assert calls # build_index a bien été appelé
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assert webapp.rebuild_status()["running"] is False
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assert webapp.rebuild_status()["done"] is not None
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