import os
import sys
import tempfile
from pathlib import Path

import cv2
import numpy as np

os.environ["SKIP_MODEL_LOAD"] = "1"
ROOT = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(ROOT))

import app  # noqa: E402


def write_video(path, frames, fps=12):
    height, width = frames[0].shape[:2]
    writer = cv2.VideoWriter(str(path), cv2.VideoWriter_fourcc(*"mp4v"), fps, (width, height))
    for frame in frames:
        writer.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR))
    writer.release()


def solid_frames(count=36, size=96, color=(30, 30, 30)):
    return [np.full((size, size, 3), color, dtype=np.uint8) for _ in range(count)]


def moving_square_frames(count=36, size=96):
    frames = solid_frames(count=count, size=size)
    for i in range(18, count):
        x = 8 + (i - 18) * 3
        cv2.rectangle(frames[i], (x, 36), (x + 16, 52), (230, 230, 230), -1)
    return frames


def flicker_frames(count=36, size=96):
    frames = solid_frames(count=count, size=size, color=(40, 40, 40))
    for i in range(18, count):
        frames[i][:] = (120, 120, 120)
    return frames


def particle_frames(count=36, size=96):
    rng = np.random.default_rng(123)
    frames = solid_frames(count=count, size=size, color=(20, 20, 25))
    for i in range(16, count):
        for _ in range(18):
            x = int(rng.integers(8, size - 8))
            y = int((i * 5 + rng.integers(0, size)) % size)
            cv2.circle(frames[i], (x, y), 2, (220, 220, 240), -1)
    return frames


def analyze_frames(frames, tmp_path, sensitivity=0.55):
    video_path = tmp_path / "sample.mp4"
    write_video(video_path, frames)
    samples = app.read_video_samples(str(video_path), max_duration_seconds=5, sample_fps=4)
    series = app.compute_temporal_series(samples)
    events = app.select_events(series, sensitivity=sensitivity, max_events=5)
    return samples, series, events


def test_no_change_returns_no_major_events():
    with tempfile.TemporaryDirectory() as tmp:
        _, _, events = analyze_frames(solid_frames(), Path(tmp), sensitivity=0.8)
        assert len(events) == 0


def test_single_motion_event_detects_near_known_timestamp():
    with tempfile.TemporaryDirectory() as tmp:
        _, _, events = analyze_frames(moving_square_frames(), Path(tmp), sensitivity=0.45)
        assert events
        assert any(1.2 <= event["timestamp"] <= 2.4 for event in events)
        assert any("Motion" in event["evidence_type"] or "Appearance" in event["evidence_type"] for event in events)


def test_lighting_flicker_is_labeled_as_intensity_change():
    with tempfile.TemporaryDirectory() as tmp:
        _, _, events = analyze_frames(flicker_frames(), Path(tmp), sensitivity=0.45)
        assert events
        assert any(event["evidence_type"] == "Lighting / exposure change" for event in events)


def test_particle_motion_produces_high_flow_or_diff_score():
    with tempfile.TemporaryDirectory() as tmp:
        _, _, events = analyze_frames(particle_frames(), Path(tmp), sensitivity=0.45)
        assert events
        assert max(event["score"] for event in events) > 0.3