"""Tests de l'export PDF (planche d'impression terrain).""" import pytest def test_layout_landscape_a4_dimensions(): from lidar_pipeline.export_pdf import layout lay = layout("A4", "paysage", 2000) assert (lay.page_w, lay.page_h) == (297.0, 210.0) and lay.dpi == 300 assert lay.map_w > 150 and lay.map_h > 150 assert lay.panel_x >= lay.map_x + lay.map_w # bandeau à droite assert lay.map_x + lay.map_w <= lay.page_w and lay.map_y + lay.map_h <= lay.page_h def test_layout_portrait_a3_panel_below(): from lidar_pipeline.export_pdf import layout lay = layout("A3", "portrait", 5000) assert (lay.page_w, lay.page_h) == (297.0, 420.0) and lay.dpi == 250 assert lay.panel_y + lay.panel_h <= lay.map_y # bandeau en bas @pytest.mark.parametrize("args", [("A5", "paysage", 2000), ("A4", "biais", 2000), ("A4", "paysage", 1234)]) def test_layout_rejects_invalid(args): from lidar_pipeline.export_pdf import layout with pytest.raises(ValueError): layout(*args) def test_map_bbox_matches_paper_times_scale(): from lidar_pipeline.export_pdf import layout, map_bbox lay = layout("A4", "paysage", 2000) b = map_bbox(652500.0, 6861500.0, lay) assert abs((b[2] - b[0]) - lay.map_w / 1000 * 2000) < 1e-6 assert abs((b[3] - b[1]) - lay.map_h / 1000 * 2000) < 1e-6 assert abs((b[0] + b[2]) / 2 - 652500.0) < 1e-6 def test_pixel_size_and_grid_step(): from lidar_pipeline.export_pdf import grid_step, layout, pixel_size assert pixel_size(layout("A4", "paysage", 1000)) == 0.2 # plafonné au natif assert abs(pixel_size(layout("A3", "paysage", 10000)) - 10000 * 0.0254 / 250) < 1e-9 assert [grid_step(s) for s in (1000, 2000, 5000, 10000)] == [100, 100, 500, 1000] def test_center_l93_rejects_non_finite(): from lidar_pipeline.export_pdf import center_l93 with pytest.raises(ValueError): center_l93(float("nan"), 2.0) def test_frame_roundtrip(): from lidar_pipeline.export_pdf import center_l93, frame lat, lon = 48.85, 2.35 f = frame(lat, lon, "A4", "paysage", 2000) cx, cy = center_l93(lat, lon) assert abs(f["cx"] - cx) < 1e-6 and abs(f["cy"] - cy) < 1e-6 assert len(f["corners"]) == 4 nw, ne, se, sw = f["corners"] assert nw[0] > sw[0] and ne[1] > nw[1] # [lat, lon] : nord en haut, est à droite assert f["width_m"] > f["height_m"] > 0 def test_export_modules_import_without_numpy(): import subprocess, sys code = ("import sys; sys.modules['numpy'] = None; " "import lidar_pipeline.export_pdf, lidar_pipeline.tiles; print('ok')") r = subprocess.run([sys.executable, "-c", code], capture_output=True, text=True) assert r.returncode == 0, r.stderr def _dalle(tmp_path, col, row, color=(200, 30, 30), px=100, layer="relief_oriente"): from lidar_pipeline import index, tiles from lidar_pipeline.tests.test_tiles import _make_dalle _make_dalle(tmp_path, col, row, [layer], color=color, px=px) tiles.source_index(tmp_path, force=True) def test_nodata_color_matches_visualizations(): from lidar_pipeline.export_pdf import NODATA_RGB from lidar_pipeline.visualizations import RELIEF_NODATA_RGB assert NODATA_RGB == tuple(RELIEF_NODATA_RGB) def test_compose_l93_full_cell(tmp_path, monkeypatch): from lidar_pipeline import index from lidar_pipeline.export_pdf import compose_l93 monkeypatch.setattr(index, "PANEL_VIZ", None) _dalle(tmp_path, 1054, 6882) img, mask, cells = compose_l93(tmp_path, (1054200.0, 6881200.0, 1054400.0, 6881300.0), 1.0) assert img.size == (200, 100) and cells == [(1054, 6882)] assert mask.getextrema() == (255, 255) r, g, b = img.getpixel((100, 50)) assert r > 150 and g < 80 and b < 80 def test_compose_l93_half_outside_is_white_hatched(tmp_path, monkeypatch): from lidar_pipeline import index from lidar_pipeline.export_pdf import compose_l93 monkeypatch.setattr(index, "PANEL_VIZ", None) _dalle(tmp_path, 1054, 6882) # moitié ouest dans la dalle, moitié est hors données img, mask, cells = compose_l93(tmp_path, (1054900.0, 6881400.0, 1055100.0, 6881500.0), 1.0) assert mask.getpixel((50, 50)) == 255 and mask.getpixel((150, 50)) == 0 east = img.crop((110, 0, 200, 100)).convert("L").getextrema() assert east[1] == 255 and east[0] < 255 # blanc + hachures def test_compose_l93_nodata_pixels_masked(tmp_path, monkeypatch): from lidar_pipeline import index from lidar_pipeline.export_pdf import NODATA_RGB, compose_l93 monkeypatch.setattr(index, "PANEL_VIZ", None) _dalle(tmp_path, 1054, 6882, color=NODATA_RGB) img, mask, cells = compose_l93(tmp_path, (1054200.0, 6881200.0, 1054400.0, 6881300.0), 1.0) assert mask.getextrema() == (0, 0) def test_compose_l93_no_data_returns_empty_cells(tmp_path): from lidar_pipeline.export_pdf import compose_l93 img, mask, cells = compose_l93(tmp_path, (0.0, 0.0, 100.0, 100.0), 1.0) assert cells == [] and mask.getextrema() == (0, 0)