"""Tests du serveur web de génération de zones (webapp)."""


def test_bbox_to_cells_single_km_cell():
    """Une bbox couvrant ~1 km² retourne la cellule L93 correspondante."""
    from lidar_pipeline.webapp import bbox_to_cells
    # Cellule 1054,6882 : X∈[1054000,1055000], Y∈[6881000,6882000] (L93)
    from rasterio.warp import transform as warp_transform
    lons, lats = warp_transform('EPSG:2154', 'EPSG:4326',
                                [1054100, 1054900], [6881100, 6881900])
    cells = bbox_to_cells(min(lons), min(lats), max(lons), max(lats))
    assert (1054, 6882) in cells
    # La sélection reste locale : pas de cellule lointaine
    for (c, r) in cells:
        assert abs(c - 1054) <= 1 and abs(r - 6882) <= 1


def test_bbox_to_cells_empty_for_tiny_bbox():
    """Une bbox quasi ponctuelle ne sélectionne rien (rétrécie sous 1 m)."""
    from lidar_pipeline.webapp import bbox_to_cells
    assert bbox_to_cells(7.850000, 48.930000, 7.850001, 48.930001) == []


def test_processed_cells(tmp_path):
    """processed_cells lit les dossiers de visualisations."""
    from lidar_pipeline.webapp import processed_cells
    vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_r0p2"
    vis.mkdir(parents=True)
    (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_r0p2_aspect.avif").write_bytes(b"x")
    assert processed_cells(tmp_path) == {(1054, 6882)}


def test_missing_cells_filters_processed(tmp_path):
    """Les cellules déjà traitées sont exclues, les autres gardent leurs coins."""
    from lidar_pipeline.webapp import missing_cells_with_corners
    vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69"
    vis.mkdir(parents=True)
    (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x")
    todo = missing_cells_with_corners([(1054, 6882), (1055, 6882)], tmp_path)
    assert len(todo) == 1
    assert todo[0]['col'] == 1055 and todo[0]['row'] == 6882
    assert len(todo[0]['corners']) == 4  # SW, SE, NE, NW


def test_missing_cells_include_done(tmp_path):
    """include_done=True conserve les cellules déjà traitées (régénération)."""
    from lidar_pipeline.webapp import missing_cells_with_corners
    vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69"
    vis.mkdir(parents=True)
    (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_aspect.avif").write_bytes(b"x")
    todo = missing_cells_with_corners([(1054, 6882), (1055, 6882)], tmp_path,
                                      include_done=True)
    assert {(t['col'], t['row']) for t in todo} == {(1054, 6882), (1055, 6882)}


def test_build_command_regenerate():
    """regenerate=True ajoute --force --force-classification à la commande."""
    from lidar_pipeline.webapp import _build_command
    cmd = " ".join(_build_command([(1054, 6882)], regenerate=True))
    assert "--force" in cmd
    assert "--force-classification" in cmd
    cmd = " ".join(_build_command([(1054, 6882)]))
    assert "--force" not in cmd
    assert "--force-classification" not in cmd


def test_build_command_ground_classification():
    """La commande utilise la méthode de classification demandée (défaut : ign)."""
    from lidar_pipeline.webapp import _build_command, GROUND_CLASS_METHODS
    # Défaut : ign (pré-classification)
    cmd = _build_command([(1054, 6882)])
    i = cmd.index("--ground-classification")
    assert cmd[i + 1] == "ign"
    # Chaque méthode valide est transmise telle quelle, avec ou sans régénération
    for method in GROUND_CLASS_METHODS:
        for regenerate in (False, True):
            cmd = _build_command([(1054, 6882)], regenerate=regenerate, ground_class=method)
            i = cmd.index("--ground-classification")
            assert cmd[i + 1] == method
            assert ("--force" in cmd) == regenerate
            assert ("--force-classification" in cmd) == regenerate


def test_build_command_default_viz_aspect():
    """Sans choix de visualisation, la commande génère uniquement aspect."""
    from lidar_pipeline.webapp import _build_command
    cmd = _build_command([(1054, 6882)])
    i = cmd.index("--only")
    assert cmd[i + 1] == "aspect"


def test_build_command_custom_viz():
    """Les visualisations demandées sont passées à --only dans l'ordre."""
    from lidar_pipeline.webapp import _build_command
    cmd = _build_command([(1054, 6882)], viz=["aspect", "wavelet", "aniso_open"])
    i = cmd.index("--only")
    assert cmd[i + 1:i + 4] == ["aspect", "wavelet", "aniso_open"]


def test_viz_step_names_match_pipeline():
    """Les noms acceptés par l'API sont exactement les étapes VIZ_STEPS du pipeline."""
    from lidar_pipeline.webapp import _viz_step_names
    from lidar_pipeline.pipeline import VIZ_STEPS
    assert _viz_step_names() == [n for n, _ in VIZ_STEPS]


def test_generate_rejects_unknown_viz():
    """L'API refuse un nom de visualisation inconnu (HTTPException 400)."""
    from fastapi import HTTPException
    from lidar_pipeline.webapp import generate, GenerateRequest
    req = GenerateRequest(tiles=[[1054, 6882]], viz=["wavelet", "inconnu"])
    try:
        generate(req)
        assert False, "une HTTPException était attendue"
    except HTTPException as e:
        assert e.status_code == 400
        assert "inconnu" in e.detail


def test_generate_accepts_wavelet_and_aniso():
    """L'API accepte wavelet + aniso_open et les transmet à --only."""
    import subprocess
    import lidar_pipeline.webapp as webapp
    captured = {}

    def fake_popen(cmd, **kwargs):
        captured["cmd"] = cmd

        class _P:
            def wait(self):
                return 0

            def poll(self):
                return 0
        return _P()

    webapp.subprocess.Popen = fake_popen
    try:
        req = webapp.GenerateRequest(tiles=[[1054, 6882]],
                                     viz=["wavelet", "aniso_open"])
        result = webapp.generate(req)
        assert result["demarré"] is True
        i = captured["cmd"].index("--only")
        assert captured["cmd"][i + 1:i + 3] == ["wavelet", "aniso_open"]
    finally:
        webapp.subprocess.Popen = subprocess.Popen


def test_available_layers_scans_disk(tmp_path, monkeypatch):
    """/api/layers retourne les couches présentes (clé → label)."""
    import lidar_pipeline.webapp as webapp
    monkeypatch.setattr(webapp, "OUTPUT_DIR", tmp_path)
    vis = tmp_path / "visualisations" / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69"
    vis.mkdir(parents=True)
    (vis / "LHD_FXX_1054_6882_PTS_LAMB93_IGN69_wavelet.avif").write_bytes(b"x")
    layers = webapp.available_layers()
    assert layers.get("wavelet")
    assert "aspect" not in layers


def test_rebuild_index_background(tmp_path, monkeypatch):
    """POST /api/rebuild lance build_index en arrière-plan puis termine."""
    import time as _time
    import lidar_pipeline.webapp as webapp
    import lidar_pipeline.index as index_mod
    calls = []
    monkeypatch.setattr(index_mod, "build_index", lambda out: calls.append(out))
    assert webapp.rebuild_index()["demarré"] is True
    for _ in range(100):
        if not webapp.rebuild_status()["running"]:
            break
        _time.sleep(0.05)
    assert calls  # build_index a bien été appelé
    assert webapp.rebuild_status()["running"] is False
    assert webapp.rebuild_status()["done"] is not None