"""Tests for src/atm/detector.py."""
from __future__ import annotations

import numpy as np
import pytest

from atm.config import (
    CanaryRegion,
    ColorSpec,
    Config,
    DiscordCfg,
    ROI,
    TelegramCfg,
    YAxisCalib,
)
from atm.detector import DetectionResult, Detector

# ---------------------------------------------------------------------------
# Constants
# ---------------------------------------------------------------------------
DOT_ROI = ROI(x=10, y=10, w=280, h=80)
BG_VAL = 18  # background pixel value (18, 18, 18)

# BGR values (OpenCV convention: B, G, R)
# turquoise  RGB=(0,255,255)  → BGR=(255,255,0)
# yellow     RGB=(255,255,0)  → BGR=(0,255,255)
TURQUOISE_BGR = (255, 255, 0)
YELLOW_BGR = (0, 255, 255)
# A purple-ish colour far from every palette entry (RGB=(100,150,50))
UNKNOWN_BGR = (50, 150, 100)


# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------

def _make_frame(*dot_specs: tuple[tuple[int, int, int], int, int]) -> np.ndarray:
    """Create a (100, 300, 3) uint8 BGR frame filled with background.

    Each spec is (bgr_color, roi_x_start, roi_x_end) and paints a
    full-height stripe inside DOT_ROI.  roi_x_end=280 reaches the right
    boundary so pixel_rgb sampling stays within the dot.
    """
    frame = np.full((100, 300, 3), BG_VAL, dtype=np.uint8)
    for bgr, x0, x1 in dot_specs:
        fx0 = DOT_ROI.x + x0
        fx1 = DOT_ROI.x + x1
        fy0 = DOT_ROI.y
        fy1 = DOT_ROI.y + DOT_ROI.h
        frame[fy0:fy1, fx0:fx1] = bgr
    return frame


def _make_cfg(debounce_depth: int = 1) -> Config:
    colors = {
        "turquoise":   ColorSpec(rgb=(0, 255, 255),   tolerance=30.0),
        "yellow":      ColorSpec(rgb=(255, 255, 0),   tolerance=30.0),
        "dark_green":  ColorSpec(rgb=(0, 100, 0),     tolerance=30.0),
        "dark_red":    ColorSpec(rgb=(100, 0, 0),     tolerance=30.0),
        "light_green": ColorSpec(rgb=(0, 255, 0),     tolerance=30.0),
        "light_red":   ColorSpec(rgb=(255, 0, 0),     tolerance=30.0),
        "gray":        ColorSpec(rgb=(128, 128, 128), tolerance=30.0),
    }
    return Config(
        window_title="test",
        dot_roi=DOT_ROI,
        chart_roi=ROI(x=0, y=0, w=600, h=400),
        colors=colors,
        y_axis=YAxisCalib(p1_y=0, p1_price=100.0, p2_y=400, p2_price=80.0),
        canary=CanaryRegion(
            roi=ROI(x=0, y=0, w=50, h=50),
            baseline_phash="0" * 64,
            drift_threshold=8,
        ),
        discord=DiscordCfg(webhook_url="http://example.com/hook"),
        telegram=TelegramCfg(bot_token="tok", chat_id="123"),
        debounce_depth=debounce_depth,
    )


# ---------------------------------------------------------------------------
# Tests
# ---------------------------------------------------------------------------

def test_empty_roi_no_dot() -> None:
    """All-background frame → dot not found."""
    frame = np.full((100, 300, 3), BG_VAL, dtype=np.uint8)
    cfg = _make_cfg()
    det = Detector(cfg, capture=lambda: frame)

    r = det.step(0.0)

    assert r.window_found is True
    assert r.dot_found is False
    assert r.rgb is None
    assert r.match is None
    assert r.accepted is False


def test_rightmost_cluster() -> None:
    """Two dots at different x positions → detector returns rightmost colour."""
    # turquoise on the left, yellow extending to the right ROI edge
    frame = _make_frame(
        (TURQUOISE_BGR, 50, 100),   # roi_x [50, 100)
        (YELLOW_BGR, 200, 280),     # roi_x [200, 280) → right edge
    )
    cfg = _make_cfg()
    det = Detector(cfg, capture=lambda: frame)

    r = det.step(0.0)

    assert r.dot_found is True
    assert r.match is not None
    assert r.match.name == "yellow"


def test_debounce_depth_1() -> None:
    """depth=1: single valid frame → accepted=True."""
    frame = _make_frame((YELLOW_BGR, 200, 280))
    cfg = _make_cfg(debounce_depth=1)
    det = Detector(cfg, capture=lambda: frame)

    r = det.step(0.0)

    assert r.accepted is True
    assert r.color == "yellow"


def test_debounce_depth_2() -> None:
    """depth=2: first frame → accepted=False; second same → accepted=True."""
    frame = _make_frame((YELLOW_BGR, 200, 280))
    cfg = _make_cfg(debounce_depth=2)
    det = Detector(cfg, capture=lambda: frame)

    r1 = det.step(0.0)
    r2 = det.step(1.0)

    assert r1.accepted is False
    assert r2.accepted is True
    assert r2.color == "yellow"


def test_debounce_reset_on_change() -> None:
    """depth=2: A then B → neither accepted."""
    frame_a = _make_frame((TURQUOISE_BGR, 200, 280))
    frame_b = _make_frame((YELLOW_BGR, 200, 280))
    cfg = _make_cfg(debounce_depth=2)
    frames = iter([frame_a, frame_b])
    det = Detector(cfg, capture=lambda: next(frames))

    r1 = det.step(0.0)
    r2 = det.step(1.0)

    assert r1.accepted is False
    assert r2.accepted is False


def test_unknown_not_accepted() -> None:
    """Colour outside every palette tolerance → UNKNOWN, accepted=False."""
    frame = _make_frame((UNKNOWN_BGR, 200, 280))
    cfg = _make_cfg(debounce_depth=1)
    det = Detector(cfg, capture=lambda: frame)

    r = det.step(0.0)

    assert r.dot_found is True
    assert r.match is not None
    assert r.match.name == "UNKNOWN"
    assert r.accepted is False
    assert r.color is None


def test_window_lost() -> None:
    """capture() returns None → window_found=False, safe defaults."""
    cfg = _make_cfg()
    det = Detector(cfg, capture=lambda: None)

    r = det.step(0.0)

    assert r.window_found is False
    assert r.dot_found is False
    assert r.rgb is None
    assert r.match is None
    assert r.accepted is False
    assert r.color is None


def test_rolling_window() -> None:
    """Rolling window never exceeds 20 entries."""
    frame = _make_frame((YELLOW_BGR, 200, 280))
    cfg = _make_cfg()
    det = Detector(cfg, capture=lambda: frame)

    for i in range(25):
        det.step(float(i))

    assert len(det.rolling) <= 20
    assert len(det.rolling) == 20


# ---------------------------------------------------------------------------
# Fused-blob regression: anti-aliased bridges merge adjacent dots into one
# connected component. The rightmost component's centroid then lands on an
# interior dot (wrong colour). find_rightmost_dot must anchor to the right
# edge for wide blobs so the truly-rightmost dot is sampled.
# See vision.find_rightmost_dot and logs/fires/20260420_210649_ss.png.
# ---------------------------------------------------------------------------

def _make_fused_stripe_frame(
    gray_segments: int,
    tail_bgr: tuple[int, int, int],
    seg_w: int = 13,
    stripe_h: int = 13,
) -> np.ndarray:
    """Continuous multi-colour stripe: N gray segments + one tail-colour segment.

    Survives 2-iter erosion as a single component — exactly the failure mode on
    real screenshots where anti-aliased bridges fuse the whole dot row into one
    component. Centroid lands on an interior gray segment; the right edge lies
    inside the tail colour.
    """
    frame = np.full((100, 300, 3), BG_VAL, dtype=np.uint8)
    y0 = DOT_ROI.y + (DOT_ROI.h - stripe_h) // 2
    x0 = DOT_ROI.x + 40
    gray_bgr = (128, 128, 128)
    for i in range(gray_segments):
        xs = x0 + i * seg_w
        frame[y0:y0 + stripe_h, xs:xs + seg_w] = gray_bgr
    xs = x0 + gray_segments * seg_w
    frame[y0:y0 + stripe_h, xs:xs + seg_w] = tail_bgr
    return frame


@pytest.mark.parametrize(
    ("screenshot", "expected"),
    [
        ("logs/fires/20260420_210649_ss.png", "dark_red"),
        ("logs/fires/20260420_200603_poll.png", "dark_green"),
    ],
)
def test_real_screenshot_rightmost_dot(screenshot: str, expected: str) -> None:
    """Regression on live-capture frames where fused blobs hid the rightmost dot.

    2026-04-20 live session missed both a dark_red (21:06:49) and a dark_green
    (20:06:03) because find_rightmost_dot returned the centroid of a multi-dot
    fused component. Skips cleanly if the sample PNG is not checked out locally
    (logs/fires/ is gitignored).
    """
    import cv2
    from pathlib import Path

    from atm.config import ROI
    from atm.vision import classify_pixel, crop_roi, find_rightmost_dot, pixel_rgb

    path = Path(screenshot)
    if not path.exists():
        pytest.skip(f"sample not available: {path}")

    frame = cv2.imread(str(path))
    assert frame is not None

    # Matches configs/2026-04-18-1220.toml dot_roi — the live config that missed
    # these alerts.
    roi = ROI(x=0, y=712, w=1796, h=35)
    crop = crop_roi(frame, roi)

    dot = find_rightmost_dot(crop, bg_rgb=(0, 0, 0), bg_tol=25.0)
    assert dot is not None, "rightmost dot must be found"

    rgb = pixel_rgb(crop, *dot)
    palette = {
        "turquoise":   ((0, 153, 153), 60.0),
        "yellow":      ((153, 153, 0), 60.0),
        "dark_green":  ((0, 122, 0),   60.0),
        "dark_red":    ((128, 0, 0),   60.0),
        "light_green": ((0, 171, 0),   60.0),
        "light_red":   ((171, 0, 0),   60.0),
        "gray":        ((128, 128, 128), 60.0),
    }
    match = classify_pixel(rgb, palette)
    assert match.name == expected, (
        f"{path.name}: expected {expected}, got {match.name} at {dot} RGB={rgb}"
    )


def test_fused_blob_samples_rightmost_dot() -> None:
    """Fused multi-colour stripe must classify the rightmost colour, not the
    centroid colour. Pre-fix the centroid fell on an interior gray segment
    on real screenshots (2026-04-20 dark_red/dark_green misses)."""
    dark_red_bgr = (0, 0, 100)  # BGR for dark_red RGB=(100,0,0)
    frame = _make_fused_stripe_frame(gray_segments=7, tail_bgr=dark_red_bgr)

    cfg = _make_cfg()
    from atm.config import ColorSpec
    cfg.colors["gray"] = ColorSpec(rgb=(128, 128, 128), tolerance=30.0)
    cfg.colors["dark_red"] = ColorSpec(rgb=(100, 0, 0), tolerance=30.0)

    det = Detector(cfg, capture=lambda: frame)
    r = det.step(0.0)

    assert r.dot_found is True
    assert r.match is not None
    assert r.match.name == "dark_red", (
        f"expected dark_red (rightmost segment), got {r.match.name} at "
        f"{r.dot_pos_abs} RGB={r.rgb} — centroid regression"
    )