"""Export PDF d'une zone : planche d'impression terrain du relief orienté.

Composée directement en Lambert 93 depuis les sources de la pyramide
(tiles.py) — échelle exacte, quadrillage aligné sur les dalles — puis
dessinée avec reportlab (texte, grille et légende vectoriels). Tourne dans
l'image légère : Pillow + pyproj + reportlab, sans numpy.
"""

import logging
import math
from dataclasses import dataclass

logger = logging.getLogger("lidar")

LAYER = "relief_oriente"
PAPERS_MM = {"A4": (210.0, 297.0), "A3": (297.0, 420.0)}
ORIENTS = ("portrait", "paysage")
SCALES = (1000, 2000, 5000, 10000)
DPI = {"A4": 300, "A3": 250}          # borne la mémoire du Pi (~36 Mo en A3)
NATIVE_RES_M = 0.2
MARGIN_MM = 10.0                      # bord non imprimable
ANNOT_MM = 7.0                        # bande des coordonnées autour de la carte
PANEL_SIDE_MM = 64.0                  # bandeau à droite (paysage)
PANEL_BOTTOM_MM = 72.0                # bandeau en bas (portrait)
_GRID_STEPS = {1000: 100, 2000: 100, 5000: 500, 10000: 1000}


@dataclass(frozen=True)
class Layout:
    """Géométrie de la planche, en mm, origine en bas à gauche (reportlab)."""
    paper: str
    orient: str
    scale: int
    dpi: int
    page_w: float
    page_h: float
    map_x: float
    map_y: float
    map_w: float
    map_h: float
    panel_x: float
    panel_y: float
    panel_w: float
    panel_h: float


def layout(paper, orient, scale):
    """Géométrie d'une planche ; ValueError si un réglage est invalide."""
    if paper not in PAPERS_MM:
        raise ValueError(f"format inconnu : {paper} (A4 ou A3)")
    if orient not in ORIENTS:
        raise ValueError(f"orientation inconnue : {orient} (portrait ou paysage)")
    try:
        scale = int(scale)
    except (TypeError, ValueError):
        raise ValueError(f"échelle invalide : {scale}") from None
    if scale not in SCALES:
        raise ValueError("échelle non proposée : 1:" + str(scale)
                         + " (1:1000, 1:2000, 1:5000 ou 1:10000)")
    w, h = PAPERS_MM[paper]
    if orient == "paysage":
        w, h = h, w
    inner = MARGIN_MM + ANNOT_MM
    if orient == "paysage":
        map_w = w - 2 * inner - PANEL_SIDE_MM
        map_h = h - 2 * inner
        return Layout(paper, orient, scale, DPI[paper], w, h, inner, inner, map_w, map_h,
                      w - MARGIN_MM - PANEL_SIDE_MM, MARGIN_MM, PANEL_SIDE_MM, h - 2 * MARGIN_MM)
    map_w = w - 2 * inner
    map_h = h - 2 * inner - PANEL_BOTTOM_MM
    return Layout(paper, orient, scale, DPI[paper], w, h, inner, MARGIN_MM + PANEL_BOTTOM_MM + ANNOT_MM,
                  map_w, map_h, MARGIN_MM, MARGIN_MM, w - 2 * MARGIN_MM, PANEL_BOTTOM_MM)


def center_l93(lat, lon):
    """Centre WGS84 → Lambert 93 ; ValueError si non fini."""
    from .tiles import wgs84_to_l93
    lat, lon = float(lat), float(lon)
    if not (math.isfinite(lat) and math.isfinite(lon)):
        raise ValueError("coordonnées du centre invalides")
    cx, cy = wgs84_to_l93(lon, lat)
    if not (math.isfinite(cx) and math.isfinite(cy)):
        raise ValueError("centre hors du domaine Lambert 93")
    return cx, cy


def map_bbox(cx, cy, lay):
    """Emprise terrain L93 de la zone carte (papier × échelle)."""
    half_w = lay.map_w / 1000.0 * lay.scale / 2
    half_h = lay.map_h / 1000.0 * lay.scale / 2
    return (cx - half_w, cy - half_h, cx + half_w, cy + half_h)


def pixel_size(lay):
    """Taille terrain d'un pixel imprimé (m), jamais plus fine que le natif."""
    return max(NATIVE_RES_M, lay.scale * 0.0254 / lay.dpi)


def grid_step(scale):
    """Pas du quadrillage L93 (m) selon l'échelle."""
    return _GRID_STEPS[int(scale)]


def _to_wgs84(x, y):
    from .tiles import _transformer
    lon, lat = _transformer("EPSG:2154", "EPSG:4326").transform(x, y)
    return lat, lon


def frame(lat, lon, paper, orient, scale):
    """Cadre imprimable pour la carte : emprise L93 et coins WGS84 (NO, NE, SE, SO)."""
    lay = layout(paper, orient, scale)
    cx, cy = center_l93(lat, lon)
    b = map_bbox(cx, cy, lay)
    corners = [_to_wgs84(b[0], b[3]), _to_wgs84(b[2], b[3]),
               _to_wgs84(b[2], b[1]), _to_wgs84(b[0], b[1])]
    return {"cx": cx, "cy": cy, "bbox_l93": list(b),
            "corners": [[round(a, 7), round(o, 7)] for a, o in corners],
            "width_m": round(b[2] - b[0]), "height_m": round(b[3] - b[1])}


# Couleur des pixels sans donnée du relief orienté (recopie de
# visualizations.RELIEF_NODATA_RGB : ce module importe numpy, absent de
# l'image légère ; égalité vérifiée par les tests).
NODATA_RGB = (38, 38, 41)
_NODATA_TOLERANCE = 3        # écart par canal toléré (rééchantillonnage)
_HATCH_STEP_PX = 14


def _paste_l93(canvas, mask, src, bbox, px):
    """Recadre et rééchantillonne une source L93 dans l'image de la planche."""
    from PIL import Image, ImageChops
    from . import tiles

    img = tiles.load_source(src)
    if img is None:
        return False
    w, h = img.size
    sx0, sy0, sx1, sy1 = src.bounds
    ix0, ix1 = max(bbox[0], sx0), min(bbox[2], sx1)
    iy0, iy1 = max(bbox[1], sy0), min(bbox[3], sy1)
    if ix1 <= ix0 or iy1 <= iy0:
        return False
    dx0 = int(round((ix0 - bbox[0]) / px)); dx1 = int(round((ix1 - bbox[0]) / px))
    dy0 = int(round((bbox[3] - iy1) / px)); dy1 = int(round((bbox[3] - iy0) / px))
    if dx1 <= dx0 or dy1 <= dy0:
        return False
    rx, ry = (sx1 - sx0) / w, (sy1 - sy0) / h
    gx0, gx1 = bbox[0] + dx0 * px, bbox[0] + dx1 * px
    gy1, gy0 = bbox[3] - dy0 * px, bbox[3] - dy1 * px
    box = (max(0.0, (gx0 - sx0) / rx), max(0.0, (sy1 - gy1) / ry),
           min(float(w), (gx1 - sx0) / rx), min(float(h), (sy1 - gy0) / ry))
    part = img.resize((dx1 - dx0, dy1 - dy0), Image.LANCZOS, box=box)
    rgb = part.convert("RGB")
    diff = ImageChops.difference(rgb, Image.new("RGB", rgb.size, NODATA_RGB))
    r, g, b = diff.split()
    valid = ImageChops.lighter(ImageChops.lighter(r, g), b).point(
        lambda v: 255 if v > _NODATA_TOLERANCE else 0)
    if part.mode == "RGBA":
        valid = ImageChops.multiply(valid, part.getchannel("A").point(
            lambda v: 255 if v >= 128 else 0))
    canvas.paste(rgb, (dx0, dy0), valid)
    mask.paste(255, (dx0, dy0, dx1, dy1), valid)
    return True


def _hatch(size):
    """Motif blanc à hachures grises (zones sans donnée)."""
    from PIL import Image, ImageDraw
    w, h = size
    pat = Image.new("RGB", size, (255, 255, 255))
    draw = ImageDraw.Draw(pat)
    for k in range(-h, w, _HATCH_STEP_PX):
        draw.line([(k, h), (k + h, 0)], fill=(200, 200, 200), width=2)
    return pat


def compose_l93(output_dir, bbox, px_size, layer=LAYER):
    """Image RGB de l'emprise L93 à px_size m/px, masque des pixels peints et
    dalles contributrices. Hors données : blanc hachuré."""
    from PIL import Image, ImageOps
    from . import tiles

    width = max(1, int(round((bbox[2] - bbox[0]) / px_size)))
    height = max(1, int(round((bbox[3] - bbox[1]) / px_size)))
    canvas = Image.new("RGB", (width, height), (255, 255, 255))
    mask = Image.new("L", (width, height), 0)
    cells = set()
    for cell, src in tiles.sources_in_bbox(output_dir, layer, bbox, px_size):
        if _paste_l93(canvas, mask, src, bbox, px_size):
            cells.add(cell)
    if mask.getextrema() != (255, 255):
        canvas.paste(_hatch(canvas.size), (0, 0), ImageOps.invert(mask))
    return canvas, mask, sorted(cells)


ROSE_L = 64.0
ROSE_CHROMA = 60.0           # = visualizations.RELIEF_CHROMA
# Classes de densité de points sol (pts/m²) : rouge = donnée faible.
DENSITY_CLASSES = [
    (0.0, "moins de 1", "#d7301f"),
    (1.0, "1 à 3", "#fc8d59"),
    (3.0, "3 à 6", "#fdcc8a"),
    (6.0, "6 à 10", "#a1d99b"),
    (10.0, "10 et plus", "#31a354"),
]


def lab_to_rgb(L, a, b):
    """CIELAB (D65) → sRGB 8 bits, même formule que la carte (labToRgb)."""
    fy = (L + 16) / 116
    fx, fz = fy + a / 500, fy - b / 200

    def finv(t):
        return t ** 3 if t > 6 / 29 else 3 * (6 / 29) ** 2 * (t - 4 / 29)

    X, Y, Z = 0.95047 * finv(fx), finv(fy), 1.08883 * finv(fz)
    lin = (3.2406 * X - 1.5372 * Y - 0.4986 * Z,
           -0.9689 * X + 1.8758 * Y + 0.0415 * Z,
           0.0557 * X - 0.2040 * Y + 1.0570 * Z)
    out = []
    for c in lin:
        v = 12.92 * c if c <= 0.0031308 else 1.055 * max(c, 0.0) ** (1 / 2.4) - 0.055
        out.append(int(round(min(1.0, max(0.0, v)) * 255)))
    return tuple(out)


def rose_color(compass_deg):
    """Couleur d'une orientation de pente (0 = N, sens horaire), comme la rose de la carte."""
    chroma = ROSE_CHROMA * min(1.0, ROSE_L * (100 - ROSE_L) / 2500)
    h = math.radians((compass_deg + 90) % 360)
    return lab_to_rgb(ROSE_L, chroma * math.cos(h), chroma * math.sin(h))


def density_color(v):
    """Couleur de classe d'une densité sol (pts/m²)."""
    color = DENSITY_CLASSES[0][2]
    for low, _label, c in DENSITY_CLASSES:
        if v >= low:
            color = c
    return color


def _pdf_text(s):
    """Texte encodable par les polices standard (WinAnsi/cp1252)."""
    return "".join(ch if ch.encode("cp1252", "ignore") else "?" for ch in str(s))


def _cells_of_bbox(bbox):
    """Dalles LHD 1 km intersectant une emprise L93."""
    c0, c1 = int(math.floor(bbox[0] / 1000)), int(math.ceil(bbox[2] / 1000))
    r0, r1 = int(math.floor(bbox[1] / 1000)) + 1, int(math.ceil(bbox[3] / 1000))
    return [(c, r) for c in range(c0, c1) for r in range(r1, r0 - 1, -1)]


def zone_quality(bbox, table, cells_with_relief):
    """Agrège la qualité des dalles sur une emprise (pondérée par la surface)."""
    from .index import parse_basename_coords
    from .quality import DENSITY_CELL_M

    by_cell = {}
    for base, data in table.items():
        coords = parse_basename_coords(base)
        if coords is not None:
            by_cell[tuple(coords)] = data
    cells = _cells_of_bbox(bbox)
    relief = set(map(tuple, cells_with_relief))
    total_w = dens_w = empty_w = 0.0
    dmin = None
    starts, ends, sources = [], [], set()
    grid_cells, missing_q = [], []
    for col, row in cells:
        q = by_cell.get((col, row))
        if q is None:
            missing_q.append((col, row))
            continue
        x0, y1 = col * 1000.0, row * 1000.0
        grid = q.get("density_grid") or []
        for j, line in enumerate(grid):
            for i, v in enumerate(line):
                gx0, gx1 = x0 + i * DENSITY_CELL_M, x0 + (i + 1) * DENSITY_CELL_M
                gy1, gy0 = y1 - j * DENSITY_CELL_M, y1 - (j + 1) * DENSITY_CELL_M
                ox = min(gx1, bbox[2]) - max(gx0, bbox[0])
                oy = min(gy1, bbox[3]) - max(gy0, bbox[1])
                if ox <= 0 or oy <= 0:
                    continue
                area = ox * oy
                total_w += area
                dens_w += v * area
                empty_w += float(q.get("empty_fraction") or 0.0) * area
                dmin = v if dmin is None else min(dmin, v)
                grid_cells.append((gx0, gy0, gx1, gy1, v))
        if q.get("acq_start"):
            starts.append(q["acq_start"]); ends.append(q["acq_end"] or q["acq_start"])
            sources.add(q.get("acq_source"))
    return {
        "density_mean": dens_w / total_w if total_w else None,
        "density_min": dmin,
        "empty_fraction": empty_w / total_w if total_w else None,
        "acq_start": min(starts) if starts else None,
        "acq_end": max(ends) if ends else None,
        "acq_sources": sources,
        "cells": cells,
        "missing_relief": [c for c in cells if c not in relief],
        "missing_quality": missing_q,
        "grid_cells": grid_cells,
    }