2025-11-30 18:01:30 +01:00
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"""
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inkycal_today unittest
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"""
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import logging
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import unittest
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from inkycal.modules import Today
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from inkycal.modules.inky_image import Inkyimage, image_to_palette
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from tests import Config
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merge = Inkyimage.merge
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sample_url = Config.SAMPLE_ICAL_URL
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logger = logging.getLogger(__name__)
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logging.basicConfig(level=logging.DEBUG)
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# /workspaces/Inkycal/venv/bin/python3 -m pytest tests/test_inkycal_today.py::TestToday::test_generate_image -v -s
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tests = [
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{
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"name": "Today",
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"config": {
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2025-11-30 21:44:20 +01:00
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"size": [480, 390],
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2025-11-30 18:01:30 +01:00
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"week_starts_on": "Monday",
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"show_events": True,
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"date_format": "D MMM", "time_format": "HH:mm",
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2025-11-30 21:17:02 +01:00
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"padding_x": 10, "padding_y": 10, "fontsize": 14, "language": "zh",
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"font": "NotoSansCJKsc-Regular",
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2025-11-30 21:44:20 +01:00
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"webdav_hostname": "https://webdav.mhrooz.xyz",
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"webdav_login": "iicd",
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"webdav_password": "wjslldhs",
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"webdav_file_path": "/super-productivity/__meta_",
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2025-11-30 18:01:30 +01:00
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}
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},
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]
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class TestToday(unittest.TestCase):
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def test_generate_image(self):
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output_dir = Config.OUTPUT_DIR
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import os
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from PIL import Image, ImageDraw
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import numpy as np
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os.makedirs(output_dir, exist_ok=True)
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test_num = 0
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for test in tests:
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print(f'test {tests.index(test) + 1} generating image..', end="")
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module = Today(test)
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im_black, im_colour = module.generate_image()
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print('OK')
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# 创建最终的三色图像
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# 在 E-Paper 上: im_black 的黑色像素显示黑色, im_colour 的黑色像素显示红色
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result = Image.new('RGB', im_black.size, 'white')
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result_array = np.array(result)
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black_array = np.array(im_black)
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colour_array = np.array(im_colour)
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# 使用阈值处理抗锯齿：灰度值 < 128 的视为"黑色"
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# im_black 上的深色区域 -> 黑色 (0, 0, 0)
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black_gray = black_array[:,:,0] # 取灰度值（RGB相同）
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black_mask = black_gray < 128
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result_array[black_mask] = [0, 0, 0]
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# im_colour 上的深色区域 -> 红色 (255, 0, 0)
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colour_gray = colour_array[:,:,0]
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colour_mask = colour_gray < 128
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result_array[colour_mask] = [255, 0, 0]
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# 保存最终图像
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final_image = Image.fromarray(result_array)
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output_path = os.path.join(output_dir, f"today_test_{test_num}.png")
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final_image.save(output_path)
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print(f' -> Saved to {output_path}')
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# 统计颜色
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red_count = np.sum(colour_mask)
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black_count = np.sum(black_mask)
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print(f' 🔴 Red pixels: {red_count}, ⚫ Black pixels: {black_count}')
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test_num += 1
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if Config.USE_PREVIEW:
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final_image.show()
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