244 lines
10 KiB
Python
244 lines
10 KiB
Python
"""Tests de l'export PDF (planche d'impression terrain)."""
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import pytest
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def test_layout_landscape_a4_dimensions():
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from lidar_pipeline.export_pdf import layout
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lay = layout("A4", "paysage", 2000)
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assert (lay.page_w, lay.page_h) == (297.0, 210.0) and lay.dpi == 300
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assert lay.map_w > 150 and lay.map_h > 150
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assert lay.panel_x >= lay.map_x + lay.map_w # bandeau à droite
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assert lay.map_x + lay.map_w <= lay.page_w and lay.map_y + lay.map_h <= lay.page_h
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def test_layout_portrait_a3_panel_below():
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from lidar_pipeline.export_pdf import layout
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lay = layout("A3", "portrait", 5000)
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assert (lay.page_w, lay.page_h) == (297.0, 420.0) and lay.dpi == 250
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assert lay.panel_y + lay.panel_h <= lay.map_y # bandeau en bas
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@pytest.mark.parametrize("args", [("A5", "paysage", 2000), ("A4", "biais", 2000),
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("A4", "paysage", 1234)])
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def test_layout_rejects_invalid(args):
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from lidar_pipeline.export_pdf import layout
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with pytest.raises(ValueError):
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layout(*args)
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def test_map_bbox_matches_paper_times_scale():
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from lidar_pipeline.export_pdf import layout, map_bbox
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lay = layout("A4", "paysage", 2000)
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b = map_bbox(652500.0, 6861500.0, lay)
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assert abs((b[2] - b[0]) - lay.map_w / 1000 * 2000) < 1e-6
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assert abs((b[3] - b[1]) - lay.map_h / 1000 * 2000) < 1e-6
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assert abs((b[0] + b[2]) / 2 - 652500.0) < 1e-6
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def test_pixel_size_and_grid_step():
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from lidar_pipeline.export_pdf import grid_step, layout, pixel_size
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assert pixel_size(layout("A4", "paysage", 1000)) == 0.2 # plafonné au natif
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assert abs(pixel_size(layout("A3", "paysage", 10000)) - 10000 * 0.0254 / 250) < 1e-9
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assert [grid_step(s) for s in (1000, 2000, 5000, 10000)] == [100, 100, 500, 1000]
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def test_center_l93_rejects_non_finite():
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from lidar_pipeline.export_pdf import center_l93
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with pytest.raises(ValueError):
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center_l93(float("nan"), 2.0)
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def test_frame_roundtrip():
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from lidar_pipeline.export_pdf import center_l93, frame
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lat, lon = 48.85, 2.35
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f = frame(lat, lon, "A4", "paysage", 2000)
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cx, cy = center_l93(lat, lon)
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assert abs(f["cx"] - cx) < 1e-6 and abs(f["cy"] - cy) < 1e-6
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assert len(f["corners"]) == 4
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nw, ne, se, sw = f["corners"]
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assert nw[0] > sw[0] and ne[1] > nw[1] # [lat, lon] : nord en haut, est à droite
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assert f["width_m"] > f["height_m"] > 0
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def test_export_modules_import_without_numpy():
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import subprocess, sys
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code = ("import sys; sys.modules['numpy'] = None; "
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"import lidar_pipeline.export_pdf, lidar_pipeline.tiles; print('ok')")
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r = subprocess.run([sys.executable, "-c", code], capture_output=True, text=True)
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assert r.returncode == 0, r.stderr
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def _dalle(tmp_path, col, row, color=(200, 30, 30), px=100, layer="relief_oriente"):
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from lidar_pipeline import index, tiles
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from lidar_pipeline.tests.test_tiles import _make_dalle
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_make_dalle(tmp_path, col, row, [layer], color=color, px=px)
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tiles.source_index(tmp_path, force=True)
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def test_nodata_color_matches_visualizations():
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from lidar_pipeline.export_pdf import NODATA_RGB
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from lidar_pipeline.visualizations import RELIEF_NODATA_RGB
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assert NODATA_RGB == tuple(RELIEF_NODATA_RGB)
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def test_compose_l93_full_cell(tmp_path, monkeypatch):
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from lidar_pipeline import index
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from lidar_pipeline.export_pdf import compose_l93
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monkeypatch.setattr(index, "PANEL_VIZ", None)
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_dalle(tmp_path, 1054, 6882)
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img, mask, cells = compose_l93(tmp_path, (1054200.0, 6881200.0, 1054400.0, 6881300.0), 1.0)
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assert img.size == (200, 100) and cells == [(1054, 6882)]
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assert mask.getextrema() == (255, 255)
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r, g, b = img.getpixel((100, 50))
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assert r > 150 and g < 80 and b < 80
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def test_compose_l93_half_outside_is_white_hatched(tmp_path, monkeypatch):
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from lidar_pipeline import index
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from lidar_pipeline.export_pdf import compose_l93
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monkeypatch.setattr(index, "PANEL_VIZ", None)
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_dalle(tmp_path, 1054, 6882)
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# moitié ouest dans la dalle, moitié est hors données
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img, mask, cells = compose_l93(tmp_path, (1054900.0, 6881400.0, 1055100.0, 6881500.0), 1.0)
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assert mask.getpixel((50, 50)) == 255 and mask.getpixel((150, 50)) == 0
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east = img.crop((110, 0, 200, 100)).convert("L").getextrema()
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assert east[1] == 255 and east[0] < 255 # blanc + hachures
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def test_compose_l93_nodata_pixels_masked(tmp_path, monkeypatch):
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from lidar_pipeline import index
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from lidar_pipeline.export_pdf import NODATA_RGB, compose_l93
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monkeypatch.setattr(index, "PANEL_VIZ", None)
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_dalle(tmp_path, 1054, 6882, color=NODATA_RGB)
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img, mask, cells = compose_l93(tmp_path, (1054200.0, 6881200.0, 1054400.0, 6881300.0), 1.0)
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assert mask.getextrema() == (0, 0)
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def test_compose_l93_no_data_returns_empty_cells(tmp_path):
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from lidar_pipeline.export_pdf import compose_l93
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img, mask, cells = compose_l93(tmp_path, (0.0, 0.0, 100.0, 100.0), 1.0)
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assert cells == [] and mask.getextrema() == (0, 0)
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def test_lab_to_rgb_matches_numpy_reference():
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import numpy as np
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from lidar_pipeline.export_pdf import lab_to_rgb
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from lidar_pipeline.visualizations import _lab_to_srgb
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for L, a, b in [(64, 30, -20), (20, 0, 0), (90, -10, 40), (50, 60, 0)]:
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ref = tuple(int(round(v * 255)) for v in _lab_to_srgb(
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np.array(L, float), np.array(a, float), np.array(b, float)))
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assert all(abs(p - q) <= 1 for p, q in zip(lab_to_rgb(L, a, b), ref))
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def test_rose_color_distinct_orientations():
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from lidar_pipeline.export_pdf import rose_color
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colors = {rose_color(c) for c in (0, 90, 180, 270)}
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assert len(colors) == 4
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def test_density_color_classes():
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from lidar_pipeline.export_pdf import DENSITY_CLASSES, density_color
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assert density_color(0.0) == DENSITY_CLASSES[0][2]
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assert density_color(50.0) == DENSITY_CLASSES[-1][2]
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def test_pdf_text_replaces_unencodable():
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from lidar_pipeline.export_pdf import _pdf_text
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assert _pdf_text("Relief orienté — 1:2 000 ≥ 🚀") == "Relief orienté — 1:2 000 ? ?"
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def _q(density, start="2023-03-15", end="2023-03-17", empty=0.1):
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return {"version": 1, "ground_density": density,
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"density_grid": [[density] * 20 for _ in range(20)],
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"empty_fraction": empty, "acq_start": start, "acq_end": end,
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"acq_source": "gps"}
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def test_zone_quality_aggregates_two_cells():
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from lidar_pipeline.export_pdf import zone_quality
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table = {"LHD_FXX_1054_6882_PTS_LAMB93_IGN69": _q(4.0, "2023-03-15", "2023-03-15"),
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"LHD_FXX_1055_6882_PTS_LAMB93_IGN69": _q(8.0, "2023-04-02", "2023-04-03", 0.3)}
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bbox = (1054500.0, 6881500.0, 1055500.0, 6881600.0) # moitié de chaque dalle
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z = zone_quality(bbox, table, [(1054, 6882), (1055, 6882)])
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assert abs(z["density_mean"] - 6.0) < 1e-6 and z["density_min"] == 4.0
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assert abs(z["empty_fraction"] - 0.2) < 1e-6
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assert (z["acq_start"], z["acq_end"]) == ("2023-03-15", "2023-04-03")
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assert z["missing_relief"] == [] and z["missing_quality"] == []
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assert len(z["grid_cells"]) == 2 * 10 * 2 # 10 mailles en x × 2 en y par dalle
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def test_zone_quality_missing_cells():
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from lidar_pipeline.export_pdf import zone_quality
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bbox = (1054500.0, 6881500.0, 1055500.0, 6881600.0)
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z = zone_quality(bbox, {}, [(1054, 6882)])
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assert z["density_mean"] is None and z["acq_start"] is None
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assert z["missing_quality"] == [(1054, 6882), (1055, 6882)]
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assert z["missing_relief"] == [(1055, 6882)]
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def _mediabox(pdf):
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import re
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m = re.search(rb"/MediaBox \[\s*0 0 ([\d.]+) ([\d.]+)\s*\]", pdf)
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return float(m.group(1)), float(m.group(2))
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def _cell_center_wgs84(col, row):
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from lidar_pipeline.tiles import _transformer
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lon, lat = _transformer("EPSG:2154", "EPSG:4326").transform(col * 1000 + 500, (row - 1) * 1000 + 500)
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return lat, lon
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def test_build_pdf_a4_landscape(tmp_path, monkeypatch):
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from lidar_pipeline import index
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from lidar_pipeline.export_pdf import build_pdf
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from lidar_pipeline.quality import write_quality
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monkeypatch.setattr(index, "PANEL_VIZ", None)
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_dalle(tmp_path, 1054, 6882, px=200)
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write_quality(tmp_path, "LHD_FXX_1054_6882_PTS_LAMB93_IGN69", _q(6.5))
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lat, lon = _cell_center_wgs84(1054, 6882)
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pdf, name = build_pdf(tmp_path, lat, lon, "A4", "paysage", 2000,
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title="Prospection 🚀 bois", compress=False)
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assert pdf.startswith(b"%PDF")
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w, h = _mediabox(pdf)
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assert abs(w - 841.89) < 0.5 and abs(h - 595.28) < 0.5
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assert name.startswith("relief_1054.") and name.endswith("_1-2000.pdf")
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for s in (b"Prospection ? bois", b"1:2 000", b"Densit", b"2023-03-15", b"LiDAR HD"):
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assert s in pdf, s
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def test_build_pdf_a3_portrait_size(tmp_path, monkeypatch):
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from lidar_pipeline import index
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from lidar_pipeline.export_pdf import build_pdf
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monkeypatch.setattr(index, "PANEL_VIZ", None)
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_dalle(tmp_path, 1054, 6882)
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lat, lon = _cell_center_wgs84(1054, 6882)
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pdf, _name = build_pdf(tmp_path, lat, lon, "A3", "portrait", 5000)
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w, h = _mediabox(pdf)
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assert abs(w - 841.89) < 0.5 and abs(h - 1190.55) < 0.5
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def test_build_pdf_partial_zone_hatched(tmp_path, monkeypatch):
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"""Zone à cheval sur le bord des données : planche produite, dalle absente listée."""
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from lidar_pipeline import index
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from lidar_pipeline.export_pdf import build_pdf
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from lidar_pipeline.tiles import _transformer
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monkeypatch.setattr(index, "PANEL_VIZ", None)
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_dalle(tmp_path, 1054, 6882)
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lon, lat = _transformer("EPSG:2154", "EPSG:4326").transform(1055000.0, 6881500.0)
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pdf, _ = build_pdf(tmp_path, lat, lon, "A4", "paysage", 2000, compress=False)
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assert pdf.startswith(b"%PDF") and b"1055_6882" in pdf
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assert b"non renseign" in pdf
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def test_build_pdf_no_data_raises(tmp_path):
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import pytest
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from lidar_pipeline.export_pdf import NoDataError, build_pdf
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with pytest.raises(NoDataError):
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build_pdf(tmp_path, 46.5, 2.5, "A4", "paysage", 2000)
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def test_fmt_int():
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from lidar_pipeline.export_pdf import _fmt_int
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assert _fmt_int(2000) == "2 000" and _fmt_int(500) == "500"
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