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+probability(debug&test)

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NY 2025-03-14 16:22:00 +08:00
parent 8a2614b073
commit 4ddb6f051f
1 changed files with 12 additions and 8 deletions
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20
pkg/dash/func/info_test.py
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@ -53,17 +53,19 @@ def update_test_info(n_clicks, test_date, test_time):
return [html.Div("Invalid date or time format. Use YYYY-MM-DD and HH:MM:SS (e.g., 12:00:00).")]
# 计算周期开始时间（上一个周五 12:00 PM）
test_date_only = test_datetime.replace(hour=0, minute=0, second=0, microsecond=0) # 只考虑日期部分
days_to_last_friday = (test_date_only.weekday() - 4) % 7 # 4 表示周五
cycle_start = test_date_only - timedelta(days=days_to_last_friday)
cycle_start = cycle_start.replace(hour=12, minute=0, second=0, microsecond=0) # 已经是 tz-aware，直接调整时间
days_since_last_friday = (test_datetime.weekday() - 4) % 7 # 4 表示周五
cycle_start = test_datetime - timedelta(days=days_since_last_friday)
cycle_start = cycle_start.replace(hour=12, minute=0, second=0, microsecond=0)
# 确保周期结束时间（下周五 12:00 PM EDT）考虑夏令时
cycle_end = cycle_start + timedelta(days=7)
if cycle_end.month == 3 and 8 <= cycle_end.day <= 14: # 粗略检查夏令时开始（3月第二个星期日）
cycle_end = cycle_end.tz_convert(est) # 转换为 EDT
# 精确计算夏令时开始（2025年3月9日，第二个星期日）
first_day = cycle_end.replace(day=1)
second_sunday = first_day + timedelta(days=((6 - first_day.weekday()) % 7) + 7)
if cycle_end.month == 3 and cycle_end >= second_sunday.replace(hour=2):
cycle_end = cycle_end.tz_convert(est) # EDT
else:
cycle_end = cycle_end.tz_convert(est) # 保持一致
cycle_end = cycle_end.tz_convert(est) # EST 或 EDT
# 调试：打印周期信息
print(f"Cycle Start: {cycle_start}, Cycle End: {cycle_end}")
@ -92,9 +94,11 @@ def update_test_info(n_clicks, test_date, test_time):
prob_min, prob_max = map(float, probability.split(" - "))
formatted_probability = f"{prob_min * 100:.2f}% - {prob_max * 100:.2f}%"
# 构建测试结果表格
# 构建测试结果表格（包含 Cycle End）
test_table_rows = [
html.Tr([html.Th("Test Date and Time:", colSpan=2), html.Td(str(test_datetime), colSpan=6)]),
html.Tr([html.Th("Cycle Start:", colSpan=2), html.Td(str(cycle_start), colSpan=6)]),
html.Tr([html.Th("Cycle End:", colSpan=2), html.Td(str(cycle_end), colSpan=6)]),
html.Tr([html.Th("Tweet Count at Test Time:", colSpan=2), html.Td(str(tweet_count), colSpan=6)]),
html.Tr([html.Th("Actual Final Tweet Count:", colSpan=2), html.Td(str(actual_end_count), colSpan=6)]),
html.Tr([html.Th(f"Predicted Range ({int(prob_start)}-{int(prob_end)}):", colSpan=2), html.Td(formatted_probability, colSpan=6)]),