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)
452 lines
17 KiB
Python
452 lines
17 KiB
Python
"""Tests pour la carte globale interactive (index.py)."""
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import json
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from pathlib import Path
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def test_parse_basename_coords_valid():
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"""Parse les coordonnées d'un basename LHD valide."""
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from lidar_pipeline.index import parse_basename_coords
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assert parse_basename_coords("LHD_FXX_1000_6881_PTS_LAMB93_IGN69") == (1000, 6881)
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assert parse_basename_coords("LHD_FXX_1049_6895_PTS_LAMB93_IGN69") == (1049, 6895)
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def test_parse_basename_coords_with_res_suffix():
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"""Les noms de dossier avec suffixe résolution sont aussi parsables."""
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from lidar_pipeline.index import parse_basename_coords
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assert parse_basename_coords("LHD_FXX_1000_6881_PTS_LAMB93_IGN69_r0p2") == (1000, 6881)
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def test_parse_basename_coords_invalid():
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"""Les noms non-LHD retournent None."""
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from lidar_pipeline.index import parse_basename_coords
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assert parse_basename_coords("random_dir") is None
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assert parse_basename_coords("DTM") is None
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assert parse_basename_coords("") is None
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def test_strip_res_suffix_primary():
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"""Dossier sans suffixe = résolution primaire (0.5)."""
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from lidar_pipeline.index import _strip_res_suffix
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base, res = _strip_res_suffix("LHD_FXX_1000_6881_PTS_LAMB93_IGN69")
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assert base == "LHD_FXX_1000_6881_PTS_LAMB93_IGN69"
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assert res == 0.5
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def test_strip_res_suffix_multi():
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"""Dossier avec suffixe _r0p2 = résolution 0.2."""
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from lidar_pipeline.index import _strip_res_suffix
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base, res = _strip_res_suffix("LHD_FXX_1000_6881_PTS_LAMB93_IGN69_r0p2")
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assert base == "LHD_FXX_1000_6881_PTS_LAMB93_IGN69"
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assert res == 0.2
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def test_compute_bbox():
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"""Calcule la bounding box d'un ensemble de tuiles."""
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from lidar_pipeline.index import compute_bbox
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tiles = [
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{'col': 1000, 'row': 6881},
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{'col': 1001, 'row': 6882},
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{'col': 1002, 'row': 6880},
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]
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bbox = compute_bbox(tiles)
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assert bbox == {'min_col': 1000, 'max_col': 1002, 'min_row': 6880, 'max_row': 6882}
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def test_compute_bbox_empty():
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"""Aucune tuile → None."""
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from lidar_pipeline.index import compute_bbox
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assert compute_bbox([]) is None
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def _make_fake_viz_dir(vis_dir, basename, col, row, viz_keys=('hillshade_multi', 'svf'), ext='webp', res_suffix=''):
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"""Crée un faux dossier de visualisations avec de petites images.
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Le suffixe de résolution apparaît seulement dans le nom du dossier (miroir
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du pipeline : les fichiers restent préfixés par le basename nu).
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"""
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from PIL import Image as PILImage
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import numpy as np
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dir_name = f"LHD_FXX_{col}_{row}_PTS_LAMB93_IGN69{res_suffix}"
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tile_dir = Path(vis_dir) / dir_name
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tile_dir.mkdir(parents=True, exist_ok=True)
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for v in viz_keys:
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arr = np.random.randint(0, 255, (50, 50, 3), dtype=np.uint8)
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img = PILImage.fromarray(arr)
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fname = f"LHD_FXX_{col}_{row}_PTS_LAMB93_IGN69_{v}.{ext}"
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img.save(str(tile_dir / fname), format='WEBP', quality=80)
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return tile_dir
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def test_scan_tiles(tmp_path):
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"""scan_tiles détecte les dossiers de tuiles et leurs visualisations."""
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from lidar_pipeline.index import scan_tiles
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vis_dir = tmp_path / "visualisations"
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vis_dir.mkdir()
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_make_fake_viz_dir(vis_dir, "a", 1000, 6881, ('hillshade_multi', 'svf'))
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_make_fake_viz_dir(vis_dir, "b", 1001, 6881, ('hillshade_multi',))
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tiles = scan_tiles(vis_dir)
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assert len(tiles) == 2
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names = sorted(t['dir_name'] for t in tiles)
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assert "LHD_FXX_1000_6881_PTS_LAMB93_IGN69" in names
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assert "LHD_FXX_1001_6881_PTS_LAMB93_IGN69" in names
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# Vérifie que les viz sont détectées
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t0 = next(t for t in tiles if t['col'] == 1000)
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assert 'hillshade_multi' in t0['viz']
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assert 'svf' in t0['viz']
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def test_scan_tiles_ignores_non_lhd(tmp_path):
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"""Les dossiers non-LHD (ex: temp, DTM) sont ignorés."""
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from lidar_pipeline.index import scan_tiles
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vis_dir = tmp_path / "visualisations"
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vis_dir.mkdir()
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(vis_dir / "random_folder").mkdir()
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_make_fake_viz_dir(vis_dir, "a", 1000, 6881)
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tiles = scan_tiles(vis_dir)
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assert len(tiles) == 1
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assert tiles[0]['col'] == 1000
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def test_scan_tiles_multi_resolution(tmp_path):
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"""Les dossiers avec suffixe résolution sont correctement décodés."""
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from lidar_pipeline.index import scan_tiles
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vis_dir = tmp_path / "visualisations"
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vis_dir.mkdir()
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_make_fake_viz_dir(vis_dir, "a", 1000, 6881, res_suffix='')
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_make_fake_viz_dir(vis_dir, "a", 1000, 6881, res_suffix='_r0p2')
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tiles = scan_tiles(vis_dir)
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assert len(tiles) == 2
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resolutions = sorted(t['resolution'] for t in tiles)
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assert resolutions == [0.2, 0.5]
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def test_res_suffix_str():
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"""Le suffixe de résolution reflète le nommage du pipeline (miroir)."""
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from lidar_pipeline.index import _res_suffix_str
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assert _res_suffix_str(0.5) == ''
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assert _res_suffix_str(0.2) == '_r0p2'
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def test_collect_tile_metadata(tmp_path):
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"""Les métadonnées lisent la méthode DTM et les dates/tailles des viz."""
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import os
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from datetime import datetime
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from lidar_pipeline.index import _collect_tile_metadata
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basename = "LHD_FXX_1000_6881_PTS_LAMB93_IGN69"
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tile_dir = tmp_path / "visualisations" / basename
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tile_dir.mkdir(parents=True)
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viz_file = tile_dir / f"{basename}_hillshade_multi.webp"
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viz_file.write_bytes(b"fake")
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dtm_dir = tmp_path / "DTM"
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dtm_dir.mkdir()
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method_file = dtm_dir / f"{basename}_dtm_method.txt"
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method_file.write_text("ign", encoding="utf-8")
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# Dates déterministes : method.txt plus ancien que la viz
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os.utime(method_file, (1600000000, 1600000000))
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os.utime(viz_file, (1700000000, 1700000000))
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fmt = lambda ts: datetime.fromtimestamp(ts).strftime('%Y-%m-%d %H:%M')
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tile = {
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'basename': basename, 'resolution': 0.5,
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'dir_path': str(tile_dir),
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'viz': {'hillshade_multi': {'filename': viz_file.name, 'ext': 'webp'}},
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}
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meta = _collect_tile_metadata(tile, dtm_dir)
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assert meta['method'] == 'ign'
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assert meta['generated'] == fmt(1600000000)
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assert meta['viz']['hillshade_multi']['size'] == 4
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assert meta['viz']['hillshade_multi']['date'] == fmt(1700000000)
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def test_collect_tile_metadata_resolution_suffix(tmp_path):
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"""Une tuile 0,2 m lit son sidecar _dtm_r0p2_method.txt dédié."""
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from lidar_pipeline.index import _collect_tile_metadata
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basename = "LHD_FXX_1000_6881_PTS_LAMB93_IGN69"
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tile_dir = tmp_path / "visualisations" / (basename + "_r0p2")
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tile_dir.mkdir(parents=True)
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dtm_dir = tmp_path / "DTM"
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dtm_dir.mkdir()
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(dtm_dir / f"{basename}_dtm_r0p2_method.txt").write_text("smrf", encoding="utf-8")
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tile = {'basename': basename, 'resolution': 0.2,
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'dir_path': str(tile_dir),
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'viz': {}}
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meta = _collect_tile_metadata(tile, dtm_dir)
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assert meta['method'] == 'smrf'
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# La date vient du sidecar (écrit juste après la création du DTM)
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assert meta['generated'] is not None
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assert meta['viz'] == {}
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def test_collect_tile_metadata_fallback_date(tmp_path):
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"""Sans sidecar DTM, la date de génération remonte au plus ancien fichier viz."""
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from lidar_pipeline.index import _collect_tile_metadata
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basename = "LHD_FXX_1000_6881_PTS_LAMB93_IGN69"
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tile_dir = tmp_path / "visualisations" / basename
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tile_dir.mkdir(parents=True)
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f = tile_dir / f"{basename}_svf.webp"
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f.write_bytes(b"x")
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tile = {'basename': basename, 'resolution': 0.5,
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'dir_path': str(tile_dir),
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'viz': {'svf': {'filename': f.name, 'ext': 'webp'}}}
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meta = _collect_tile_metadata(tile, tmp_path / "DTM")
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assert meta['method'] is None
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assert meta['generated'] is not None
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def test_build_index_generates_html(tmp_path):
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"""build_index génère index.html et les vignettes."""
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from lidar_pipeline.index import build_index
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output_dir = tmp_path / "output"
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vis_dir = output_dir / "visualisations"
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vis_dir.mkdir(parents=True)
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_make_fake_viz_dir(vis_dir, "a", 1000, 6881, ('hillshade_multi', 'svf'))
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_make_fake_viz_dir(vis_dir, "b", 1001, 6881, ('hillshade_multi',))
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result = build_index(output_dir)
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assert result is not None
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html_path = Path(result)
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assert html_path.exists()
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assert html_path.name == "index.html"
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content = html_path.read_text(encoding='utf-8')
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# Vérifie la présence des éléments clés
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assert "Carte LiDAR" in content
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assert "LHD_FXX_1000_6881" in content
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assert "LHD_FXX_1001_6881" in content
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# Vérifie que le JSON intégré est valide
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assert "const TILES" in content
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# Vérifie les assets de l'interface (CSS/JS séparés)
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assets = output_dir / "assets"
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assert (assets / "app.css").read_text(encoding='utf-8').startswith('/*')
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app_js = (assets / "app.js").read_text(encoding='utf-8')
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assert "Couches" in app_js or "layers" in app_js
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# Barre de génération : sélecteur multi-visualisations (wavelet, aniso_open,
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# openness positive, pente...) et envoi du champ viz à /api/generate
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assert 'id="genViz"' in content
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assert 'value="wavelet"' in content
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assert 'value="aniso_open"' in content
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assert 'value="pos_open"' in content
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assert 'value="slope"' in content
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assert "genViz" in app_js and "viz: vizSel.length" in app_js
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assert 'assets/app.css' in content
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# Bouton d'actualisation des couches (détection des nouveautés sur disque)
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assert 'id="layerRefresh"' in content
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assert "/api/layers" in app_js and "/api/rebuild" in app_js
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assert 'assets/app.js' in content
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# Vérifie les vignettes générées
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thumb_dir = output_dir / "index_thumbs"
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assert thumb_dir.is_dir()
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thumbs = list(thumb_dir.glob("*.jpg"))
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assert len(thumbs) >= 2 # au moins hillshade pour chaque tuile
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def test_subtiled_viz_covers_generation_choices():
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"""Les viz générables depuis la carte sont sous-tuilées (affichage fluide)."""
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from lidar_pipeline.index import _CARTO_SUBTILED_VIZ
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for key in ('aspect', 'hillshade_multi', 'slope', 'positive_openness',
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'aniso_open', 'wavelet'):
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assert key in _CARTO_SUBTILED_VIZ
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def test_panel_restricted_to_requested_layers():
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"""Le panneau et le sélecteur ne proposent que la base aspect + les 4 couches demandées."""
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from lidar_pipeline.index import PANEL_VIZ, GEN_VIZ_CHOICES
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assert PANEL_VIZ == ('aspect', 'slope', 'positive_openness', 'aniso_open', 'wavelet')
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assert {name for name, _ in GEN_VIZ_CHOICES} == {
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'aspect', 'slope', 'pos_open', 'aniso_open', 'wavelet'}
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def test_build_index_regenerates_stale_thumbnails(tmp_path):
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"""Une tuile recalculée (source plus récente) régénère sa vignette."""
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import os
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import time
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import numpy as np
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from PIL import Image as PILImage
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from lidar_pipeline.index import build_index
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output_dir = tmp_path / "output"
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vis_dir = output_dir / "visualisations"
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vis_dir.mkdir(parents=True)
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tile_dir = _make_fake_viz_dir(vis_dir, "a", 1000, 6881, ('hillshade_multi',))
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assert build_index(output_dir) is not None
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thumb_path = output_dir / "index_thumbs" / "LHD_FXX_1000_6881_PTS_LAMB93_IGN69_hillshade_multi.jpg"
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assert thumb_path.exists()
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m1 = thumb_path.stat().st_mtime
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# Recalcul de la tuile : source réécrite avec une mtime plus récente
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src = tile_dir / "LHD_FXX_1000_6881_PTS_LAMB93_IGN69_hillshade_multi.webp"
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arr = np.random.randint(0, 255, (50, 50, 3), dtype=np.uint8)
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PILImage.fromarray(arr).save(str(src), format='WEBP', quality=80)
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os.utime(src, (m1 + 5, m1 + 5))
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assert build_index(output_dir) is not None
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m2 = thumb_path.stat().st_mtime
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assert m2 > m1 # vignette régénérée
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# Source non modifiée depuis → pas de régénération inutile
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os.utime(src, (time.time() - 10, time.time() - 10))
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assert build_index(output_dir) is not None
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assert thumb_path.stat().st_mtime == m2
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def test_build_subtiles_regenerates_stale_crops(tmp_path):
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"""Une dalle 0,2 m recalculée régénère ses sous-tuiles (par visualisation)."""
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import os
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from lidar_pipeline.index import build_index
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output_dir = tmp_path / "output"
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vis_dir = output_dir / "visualisations"
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vis_dir.mkdir(parents=True)
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tile_dir = _make_fake_viz_dir(vis_dir, "a", 1000, 6881,
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('hillshade_multi', 'aspect'), res_suffix='_r0p2')
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assert build_index(output_dir) is not None
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sub_dir = output_dir / "index_subtiles"
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hill_avif = sub_dir / "LHD_FXX_1000_6881_PTS_LAMB93_IGN69_r0p2_hillshade_multi_0_0.avif"
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aspect_avif = sub_dir / "LHD_FXX_1000_6881_PTS_LAMB93_IGN69_r0p2_aspect_0_0.avif"
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assert hill_avif.exists() and aspect_avif.exists()
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m_hill_1 = hill_avif.stat().st_mtime
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m_aspect_1 = aspect_avif.stat().st_mtime
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# Recalcul : seule la source hillshade est plus récente
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src = tile_dir / "LHD_FXX_1000_6881_PTS_LAMB93_IGN69_hillshade_multi.webp"
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os.utime(src, (m_hill_1 + 5, m_hill_1 + 5))
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assert build_index(output_dir) is not None
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assert hill_avif.stat().st_mtime > m_hill_1 # sous-tuiles hillshade régénérées
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assert aspect_avif.stat().st_mtime == m_aspect_1 # aspect intact
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def test_build_index_empty_returns_none(tmp_path):
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"""Aucune tuile → build_index retourne None sans crash."""
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from lidar_pipeline.index import build_index
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output_dir = tmp_path / "output"
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(output_dir / "visualisations").mkdir(parents=True)
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result = build_index(output_dir)
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assert result is None
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def test_build_index_embeds_valid_json(tmp_path):
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"""Le JSON embarqué dans le HTML est valide et contient les tuiles."""
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from lidar_pipeline.index import build_index
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output_dir = tmp_path / "output"
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vis_dir = output_dir / "visualisations"
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vis_dir.mkdir(parents=True)
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_make_fake_viz_dir(vis_dir, "a", 1000, 6881, ('hillshade_multi',))
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build_index(output_dir)
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content = (output_dir / "index.html").read_text(encoding='utf-8')
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# Extrait le JSON entre "const TILES = " et la fin de déclaration
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start = content.index("const TILES = ") + len("const TILES = ")
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# Trouve le ; de fin de déclaration
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depth = 0
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end = start
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for i, ch in enumerate(content[start:], start):
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if ch in ('{', '['):
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depth += 1
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elif ch in ('}', ']'):
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depth -= 1
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if depth == 0:
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end = i + 1
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break
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data = json.loads(content[start:end])
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assert len(data) > 0
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assert data[0]['col'] == 1000
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assert data[0]['row'] == 6881
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def test_attach_gps_bounds():
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"""attach_gps_bounds ajoute des bounds GPS ordonnées (France métropolitaine)."""
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from lidar_pipeline.index import attach_gps_bounds
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tiles = [{'col': 1000, 'row': 6881}, {'col': 1042, 'row': 6900}]
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attach_gps_bounds(tiles)
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for t in tiles:
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assert 'bounds' in t
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(lat_s, lon_w), (lat_n, lon_e) = t['bounds']
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assert lat_n > lat_s
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assert lon_e > lon_w
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# France métropolitaine
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assert 41 < lat_s < 51
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assert -5 < lon_w < 10
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def test_attach_gps_bounds_row_is_north_edge():
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"""Le numéro de ligne du fichier = bord NORD (convention LiDAR HD IGN).
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Vérifié sur les bounds des DTM : X ∈ [col, col+1] km, Y ∈ [row-1, row] km.
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La régression historique plaçait Y ∈ [row, row+1] (1 km trop au nord).
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"""
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from rasterio.warp import transform as warp_transform
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||
from lidar_pipeline.index import attach_gps_bounds
|
||
|
||
col, row = 1054, 6882
|
||
tiles = [{'col': col, 'row': row}]
|
||
attach_gps_bounds(tiles)
|
||
corners = tiles[0]['corners']
|
||
|
||
# Référence exacte de la vraie cellule : SW, SE, NE, NW
|
||
xs = [col * 1000, (col + 1) * 1000, (col + 1) * 1000, col * 1000]
|
||
ys = [(row - 1) * 1000, (row - 1) * 1000, row * 1000, row * 1000]
|
||
lons, lats = warp_transform('EPSG:2154', 'EPSG:4326', xs, ys)
|
||
for k in range(4):
|
||
assert abs(corners[k][0] - lats[k]) < 1e-9
|
||
assert abs(corners[k][1] - lons[k]) < 1e-9
|
||
|
||
# L'ancienne convention (row = bord sud) serait décalée d'environ 1 km
|
||
lat_n = max(c[0] for c in corners)
|
||
assert abs(lat_n - max(lats)) < 1e-9 # bord nord = Y = row×1000
|
||
|
||
|
||
|
||
def test_pick_display_viz_prefers_hillshade():
|
||
"""Le choix de viz par défaut privilégie hillshade_multi."""
|
||
from lidar_pipeline.index import _pick_display_viz
|
||
assert _pick_display_viz(['svf', 'hillshade_multi', 'slope']) == 'hillshade_multi'
|
||
assert _pick_display_viz(['svf', 'slope']) == 'svf'
|
||
assert _pick_display_viz(['topo']) == 'topo'
|
||
|
||
|
||
def test_subdivision_k():
|
||
"""0,5 m/px (2000 px) reste entier ; 0,2 m/px (5000 px) est découpé en 2×2."""
|
||
from lidar_pipeline.index import _subdivision_k
|
||
assert _subdivision_k(0.5) == 1
|
||
assert _subdivision_k(0.2) == 2
|
||
assert _subdivision_k(1.0) == 1
|
||
|
||
|
||
def test_subtile_corners_grid():
|
||
"""Les sous-tuiles reconstruisent exactement la grille de la dalle."""
|
||
from lidar_pipeline.index import _subtile_corners
|
||
corners = [[10.0, 2.0], [10.0, 3.0], [11.0, 3.0], [11.0, 2.0]] # SW SE NE NW
|
||
k = 2
|
||
sw_quad = _subtile_corners(corners, 0, 0, k) # quadrant sud-ouest
|
||
ne_quad = _subtile_corners(corners, 1, 1, k) # quadrant nord-est
|
||
# Le quadrant SW partage le coin SW de la dalle
|
||
assert sw_quad[0] == corners[0]
|
||
# Le quadrant NE partage le coin NE de la dalle
|
||
assert ne_quad[2] == corners[2]
|
||
# Le quadrant SW a son coin NE au centre de la dalle
|
||
assert sw_quad[2] == [10.5, 2.5]
|
||
# Adjacence : bord est du SW = bord ouest du SE (0,0)-(1,0)
|
||
se_quad = _subtile_corners(corners, 1, 0, k)
|
||
assert sw_quad[1] == se_quad[0]
|
||
assert sw_quad[2] == se_quad[3]
|