#!/usr/bin/env python3
"""Measure how much STRUCTURE an Atlas capture carries, per rung.

"Flat" is the word T-1213/D-258 use for the defect the descent ladder exposes,
but a word cannot be an acceptance gate and an eyeball cannot be a regression
test. This turns the ladder into numbers.

WHY NOT JUST COUNT COLOURS
--------------------------
Because the count goes the wrong way. Measured on the 2026-08-16 cold ladder:

    rung      distinct   lum p1-p99
    Global        1581       145.69
    Region        2923        33.59
    District        53        13.72
    Quarter         46        11.01

Region carries almost TWICE Global's distinct-colour count while holding a
quarter of its structure — that is the dither/stipple pass (T-1194) adding colour
noise, not information. A metric that rewards speckle would have called the
flattest rung the richest. So the headline number here is the 1st-99th percentile
luminance spread, which ignores per-pixel noise and measures the large-scale
variation a map is actually read for; distinct-count is reported alongside
precisely so the two can be seen disagreeing.

Usage:
    tooling/atlas-flatness .cache/screenshots/atlas_GJ820Bc_land_Region.png [...]
    tooling/atlas-flatness --ladder            # the standard descent ladder
"""

import sys
from pathlib import Path

from tooling.core import config, console
from tooling.core.errors import ReachError

try:
    from PIL import Image
except ImportError:  # pragma: no cover - environment guard
    console.event("atlas-flatness: Pillow not installed", level="error")
    sys.exit(2)

REPO_ROOT = config.repo_root()
SHOTS = REPO_ROOT / ".cache" / "screenshots"

# The standard descent ladder: one body, one world point, once per rung.
LADDER = [
    ("Global", "atlas_GJ820Bc_Global.png"),
    ("Region", "atlas_GJ820Bc_land_Region.png"),
    ("District", "atlas_GJ820Bc_land_District.png"),
    ("Quarter", "atlas_GJ820Bc_land_Quarter.png"),
]

# Terrain-only crop. The header/legend panels sit top-left and the overlay chips
# top-right; both are flat UI fills that would drag every statistic toward
# whatever the panel colour happens to be, and they do not vary with the rung.
CROP_LEFT = 700
CROP_TOP = 120


def luminance(px) -> float:
    r, g, b = px[:3]
    return 0.2126 * r + 0.7152 * g + 0.0722 * b


def measure(path: Path) -> dict:
    img = Image.open(path).convert("RGB")
    w, h = img.size
    if w <= CROP_LEFT or h <= CROP_TOP:
        raise ValueError(f"{path.name} is {w}x{h}, smaller than the UI crop")
    img = img.crop((CROP_LEFT, CROP_TOP, w, h))
    # get_flattened_data() is the Pillow 12+ name; getdata() is deprecated there
    # and removed in 14, but is all that older Pillows have.
    reader = getattr(img, "get_flattened_data", None) or img.getdata
    pixels = list(reader())

    stats = {}
    for name, ch in zip("RGB", zip(*pixels)):
        n = len(ch)
        mean = sum(ch) / n
        stats[name] = (sum((v - mean) ** 2 for v in ch) / n) ** 0.5

    lums = sorted(luminance(p) for p in pixels)
    n = len(lums)
    return {
        "distinct": len(set(pixels)),
        "std": stats,
        "spread": lums[int(n * 0.99)] - lums[int(n * 0.01)],
    }


def report(images: list[Path], ladder: bool = False) -> int:
    """Measure capture structure per rung. Returns 0, or 1 if any file is missing."""
    targets = []
    if ladder:
        targets = [(label, SHOTS / name) for label, name in LADDER]
    targets += [(p.stem, p) for p in images]

    if not targets:
        raise ReachError(
            "no captures given",
            fix="pass image paths, or --ladder to measure the standard descent",
            exit_code=2,
        )

    console.out(
        f"{'rung':22} {'distinct':>9} {'R std':>7} {'G std':>7} {'B std':>7} {'lum p1-p99':>11}"
    )
    missing = 0
    for label, path in targets:
        if not path.exists():
            console.out(f"{label:22} MISSING  {path}")
            missing += 1
            continue
        m = measure(path)
        r, g, b = (m["std"][c] for c in "RGB")
        console.out(
            f"{label:22} {m['distinct']:>9} {r:>7.2f} {g:>7.2f} {b:>7.2f} {m['spread']:>11.2f}"
        )
    return 1 if missing else 0