+probability(unfinished)

This commit is contained in:
NY 2025-03-14 15:27:11 +08:00
parent ce8127cadb
commit 192bd42d0e
2 changed files with 146 additions and 2 deletions

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@ -1,7 +1,7 @@
from datetime import timedelta, datetime
from dash import dcc, html
from pkg.config import interval_options, days_options, render_data
def layout_config(app):
app.layout = html.Div([
html.Div(
@ -229,6 +229,44 @@ def layout_config(app):
'width': '50%',
'marginTop': '10px',
'borderCollapse': 'collapse'
}),
# 新增测试区域
html.H2("Historical Probability Test", style={'marginTop': '20px'}),
html.Table([
html.Tr([
html.Td("Test Date:", style={'paddingRight': '10px'}),
html.Td(
dcc.DatePickerSingle(
id='test-date-input',
date=(datetime.now().date() - timedelta(days=1)).strftime('%Y-%m-%d'), # 默认昨天
display_format='YYYY-MM-DD',
style={'width': '100%'}
)
)
]),
html.Tr([
html.Td("Test Time:", style={'paddingRight': '10px'}),
html.Td(
dcc.Input(
id='test-time-input',
type='text',
placeholder='HH:MM:SS (e.g., 12:00:00)',
value='12:00:00',
style={'width': '100%'}
)
)
]),
html.Tr([
html.Td("Test Probability:", style={'paddingRight': '10px'}),
html.Td(
html.Button('Test', id='test-button', n_clicks=0)
)
]),
html.Tr(id='test-info-tooltip', style={'margin': '10px'})
], style={
'width': '50%',
'marginTop': '10px',
'borderCollapse': 'collapse'
})
], style={'marginLeft': '50px'}),

106
pkg/dash/func/info_test.py Normal file
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@ -0,0 +1,106 @@
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]