import unittest

import numpy as np

from wechat_bot import WeChatBot


class SessionFingerprintTest(unittest.TestCase):
    @staticmethod
    def _bot():
        bot = WeChatBot.__new__(WeChatBot)
        bot.scale = 1.0
        bot.session_item_h = 64
        bot._known_fps = set()
        return bot

    @staticmethod
    def _row(name_variant: int) -> np.ndarray:
        img = np.full((64, 230, 3), 238, dtype=np.uint8)

        # 两个客户使用完全相同的高对比头像。
        for y in range(20, 44):
            for x in range(12, 42):
                tone = 45 if ((x // 5) + (y // 4)) % 2 else 205
                img[y, x, :] = tone

        # 在昵称首行画两组分布明显不同的合成字形。
        if name_variant == 1:
            for x in (62, 68, 76, 84, 96, 108, 122):
                img[12:28, x:x + 2, :] = 35
            img[13:15, 62:126, :] = 35
            img[21:23, 68:110, :] = 35
        else:
            for y in (12, 16, 21, 26):
                img[y:y + 2, 62:132, :] = 35
            for offset in range(16):
                img[11 + offset, 136 + offset:138 + offset, :] = 35
        return img

    def test_same_avatar_different_name_patterns_are_isolated(self):
        bot = self._bot()
        first = bot._session_fingerprint(self._row(1), 32)
        second = bot._session_fingerprint(self._row(2), 32)

        self.assertEqual(16, len(first))
        self.assertEqual(16, len(second))
        self.assertEqual(first[:8], second[:8], "测试前提：头像哈希必须相同")
        self.assertNotEqual(first, second)

    def test_small_render_noise_and_label_inversion_are_normalized(self):
        bot = self._bot()
        original = self._row(1)
        canonical = bot._session_fingerprint(original, 32)

        rng = np.random.default_rng(20260723)
        noise = rng.integers(-2, 3, size=original.shape, dtype=np.int16)
        variant = np.clip(original.astype(np.int16) + noise, 0, 255).astype(np.uint8)
        # 模拟选中态：文字区前景/背景同时反相，绝对边缘强度仍应稳定。
        variant[9:30, 58:190, :] = 255 - variant[9:30, 58:190, :]

        self.assertEqual(canonical, bot._session_fingerprint(variant, 32))

    def test_new_composite_fingerprint_never_merges_into_legacy_avatar_key(self):
        bot = self._bot()
        composite = bot._session_fingerprint(self._row(1), 32)
        legacy = composite[:8]

        bot._known_fps = {legacy}
        self.assertEqual(composite, bot._canonical_fp(composite))
        self.assertIn(composite, bot._known_fps)

    def test_identical_visible_rows_use_isolated_fallbacks(self):
        bot = self._bot()
        first_row = self._row(1)
        second_row = first_row.copy()
        # 消息预览属于可见行兜底摘要，但不参与稳定昵称签名。
        first_row[38:45, 70:100, :] = 60
        second_row[38:45, 120:160, :] = 60
        image = np.vstack((first_row, second_row))

        first = bot._session_fingerprint(image, 32)
        second = bot._session_fingerprint(image, 96)
        self.assertEqual(16, len(first))
        self.assertEqual(16, len(second))
        self.assertNotEqual(first, second)

    def test_out_of_bounds_fallback_is_16_bytes_and_image_specific(self):
        bot = self._bot()
        first_img = np.zeros((8, 10, 3), dtype=np.uint8)
        second_img = first_img.copy()
        second_img[0, 0, 0] = 1

        first = bot._session_fingerprint(first_img, 0)
        second = bot._session_fingerprint(second_img, 0)
        self.assertEqual(16, len(first))
        self.assertEqual(16, len(second))
        self.assertNotEqual(first, second)


if __name__ == "__main__":
    unittest.main()