from pkg.dash.func.info_func import *
from pkg.dash.app_init import app
from dash.dependencies import Input, Output
from dash import html
import pandas as pd
from datetime import timedelta

@app.callback(
    [Output('test-info-tooltip', 'children')],
    [Input('test-button', 'n_clicks'),
     Input('test-date-input', 'date'),
     Input('test-time-input', 'value')]
)
def update_test_info(n_clicks, test_date, test_time):
    if n_clicks == 0:
        return [html.Div("Click 'Test' to see historical probability results.")]

    est = pytz.timezone('US/Eastern')

    # 解析测试日期和时间
    try:
        test_date = pd.to_datetime(test_date).date()
        test_datetime = pd.to_datetime(f"{test_date} {test_time}").tz_localize(est)  # 使用 est
    except ValueError:
        return [html.Div("Invalid date or time format. Use YYYY-MM-DD and HH:MM:SS (e.g., 12:00:00).")]

    # 1. 计算到 test_datetime 的累计推文数（模拟当时的 tweet_count）
    data = render_data.global_agg_df.copy()
    historical_data = data[data['datetime_est'] <= test_datetime]
    if historical_data.empty:
        return [html.Div(f"No data available up to {test_datetime}")]
    tweet_count = historical_data['tweet_count'].sum()

    # 2. 计算实际最终推文数（到当天结束时的总数）
    day_end = pd.to_datetime(f"{test_date} 23:59:59").tz_localize(est)  # 使用 est
    actual_data = data[(data['date'] == test_date) & (data['datetime_est'] <= day_end)]
    if actual_data.empty:
        return [html.Div(f"No data available for {test_date}")]
    actual_end_count = actual_data['tweet_count'].sum()

    # 3. 模拟 days_to_next_friday（从 test_datetime 到下周五）
    days_to_next_friday = (4 - test_date.weekday()) % 7
    next_friday = (test_datetime.replace(hour=12, minute=0, second=0, microsecond=0) +
                   timedelta(days=days_to_next_friday))
    if test_datetime > next_friday:
        next_friday += timedelta(days=7)
    days_to_next_friday = (next_friday - test_datetime).total_seconds() / (24 * 60 * 60)

    # 4. 设置预测范围（基于实际最终推文数的 ±10%）
    prob_start = actual_end_count * 0.9  # 90% of actual
    prob_end = actual_end_count * 1.1    # 110% of actual

    # 5. 调用原始的 calculate_tweet_probability() 计算概率
    probability = calculate_tweet_probability(tweet_count, days_to_next_friday, prob_start, prob_end)
    prob_min, prob_max = map(float, probability.split(" - "))
    formatted_probability = f"{prob_min * 100:.2f}% - {prob_max * 100:.2f}%"

    # 6. 构建测试结果表格
    test_table_rows = [
        html.Tr([
            html.Th("Test Date and Time:", colSpan=2, style={'paddingRight': '10px'}),
            html.Td(str(test_datetime), colSpan=6, style={'paddingRight': '10px'})
        ]),
        html.Tr([
            html.Th("Tweet Count at Test Time:", colSpan=2, style={'paddingRight': '10px'}),
            html.Td(str(tweet_count), colSpan=6, style={'paddingRight': '10px'})
        ]),
        html.Tr([
            html.Th("Actual Final Tweet Count:", colSpan=2, style={'paddingRight': '10px'}),
            html.Td(str(actual_end_count), colSpan=6, style={'paddingRight': '10px'})
        ]),
        html.Tr([
            html.Th(f"Predicted Range ({int(prob_start)}-{int(prob_end)}):", colSpan=2, style={'paddingRight': '10px'}),
            html.Td(formatted_probability, colSpan=6, style={'paddingRight': '10px'})
        ]),
        html.Tr([
            html.Th("Does Actual Fall in Range?", colSpan=2, style={'paddingRight': '10px'}),
            html.Td(
                "Yes" if prob_start <= actual_end_count <= prob_end else "No",
                colSpan=6,
                style={'paddingRight': '10px', 'color': 'green' if prob_start <= actual_end_count <= prob_end else 'red'}
            )
        ])
    ]
    if prob_start <= actual_end_count <= prob_end:
        expected_prob = (prob_max + prob_min) / 2
        test_table_rows.append(
            html.Tr([
                html.Th("Expected Probability:", colSpan=2, style={'paddingRight': '10px'}),
                html.Td(f"~{expected_prob * 100:.2f}% (should be high if model fits)", colSpan=6, style={'paddingRight': '10px'})
            ])
        )
    else:
        test_table_rows.append(
            html.Tr([
                html.Th("Note:", colSpan=2, style={'paddingRight': '10px'}),
                html.Td("Model prediction does not match actual outcome.", colSpan=6, style={'paddingRight': '10px', 'color': 'red'})
            ])
        )

    test_table = html.Table(test_table_rows, style={
        'width': '100%',
        'textAlign': 'left',
        'borderCollapse': 'collapse'
    })
    return [test_table]