diff --git a/pkg/dash/app_html.py b/pkg/dash/app_html.py
index a9bce85..7b40290 100644
--- a/pkg/dash/app_html.py
+++ b/pkg/dash/app_html.py
@@ -2,6 +2,7 @@ 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(
@@ -112,27 +113,16 @@ def layout_config(app):
'zIndex': 1000
}
),
- # Main content
html.Div([
- html.H1("Elon Musk Tweet Time Analysis (EST)"),
- html.Div(id='date-picker-container', children=[
+ html.Div(id='multi-interval-container', children=[
dcc.Dropdown(
- id='multi-date-picker',
- options=[{'label': str(date), 'value': str(date)} for date in render_data.all_dates],
- value=render_data.default_date,
- multi=True,
- searchable=True,
- placeholder="Search and select dates (YYYY-MM-DD)",
- style={'width': '100%'}
+ id='multi-interval-picker',
+ options=interval_options,
+ value=10,
+ style={'width': '50%', 'marginTop': '10px'}
)
]),
- dcc.Dropdown(
- id='multi-interval-picker',
- options=interval_options,
- value=10,
- style={'width': '50%', 'marginTop': '10px'}
- ),
- html.Div(id='days-display-container', style={'display': 'none'}, children=[
+ html.Div(id='days-display-container', children=[
dcc.Dropdown(
id='days-display-picker',
options=days_options,
@@ -141,18 +131,8 @@ def layout_config(app):
)
]),
html.Div(id='multi-day-warning', style={'color': 'red', 'margin': '10px'}),
- dcc.Checklist(
- id='time-zone-checklist',
- options=[
- {'label': 'California Time (PST)', 'value': 'PST'},
- {'label': 'Texas Time (CST)', 'value': 'CST'}
- ],
- value=['PST'],
- style={'margin': '10px'}
- ),
html.Div(id='multi-tweet-summary', style={'fontSize': '20px', 'margin': '10px'}),
- dcc.Tabs(id='tabs', value='line', children=[
- dcc.Tab(label='Line', value='line'),
+ dcc.Tabs(id='tabs', value='heatmap', children=[
dcc.Tab(label='Heatmap', value='heatmap'),
dcc.Tab(label='Heatmap(1-day)', value='one_day_heatmap'),
]),
@@ -193,83 +173,7 @@ def layout_config(app):
style={'width': '100%'}
)
)
- ]),
- html.Tr([
- html.Td("Predict Tweets Start:", style={'paddingRight': '10px'}),
- html.Td(
- dcc.Input(
- id='prob-start-input',
- type='number',
- placeholder='输入 Probability Start 值',
- value=525,
- style={'width': '100%'}
- )
- )
- ]),
- html.Tr([
- html.Td("Predict Tweets End:", style={'paddingRight': '10px'}),
- html.Td(
- dcc.Input(
- id='prob-end-input',
- type='number',
- placeholder='输入 Probability End 值',
- value=549,
- style={'width': '100%'}
- )
- )
- ]),
- html.Tr([
- html.Td("Calculate Probability:", style={'paddingRight': '10px'}),
- html.Td(
- html.Button('Calculate', id='update-button', n_clicks=0)
- )
- ]),
- html.Tr(id='manual-info-tooltip', style={'margin': '10px'})
- ], style={
- '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(
- html.Div([
- dcc.Input(
- id='test-time-input',
- type='text',
- placeholder='HH:MM:SS (e.g., 12:00:00)', # 增强提示
- value='12:00:00',
- pattern='[0-2][0-9]:[0-5][0-9]:[0-5][0-9]', # 限制格式
- style={'width': '100%'}
- ),
- html.Span(
- "Enter time in HH:MM:SS format (e.g., 12:00:00)",
- style={'fontSize': '12px', 'color': 'gray', 'marginTop': '5px', 'display': 'block'}
- )
- ])
- )
- ]),
- 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',
@@ -279,4 +183,4 @@ def layout_config(app):
dcc.Interval(id='clock-interval', interval=1000, n_intervals=0)
])
- return app
\ No newline at end of file
+ return app
diff --git a/pkg/dash/func/info_m.py b/pkg/dash/func/info_m.py
deleted file mode 100644
index 3c8b446..0000000
--- a/pkg/dash/func/info_m.py
+++ /dev/null
@@ -1,37 +0,0 @@
-from pkg.dash.func.info_func import *
-from pkg.dash.app_init import app
-from dash.dependencies import Input, Output
-from dash import html
-
-@app.callback(
- [Output('manual-info-tooltip', 'children')],
- [Input('update-button', 'n_clicks'),
- Input('prob-start-input', 'value'),
- Input('prob-end-input', 'value')]
-)
-def update_info_manual(n_clicks, prob_start, prob_end):
- if n_clicks == 0:
- return [html.Div("Click 'Manual Update' to see results.")]
-
- tweet_count, days_to_next_friday = get_pace_params()
- prob_start = int(prob_start) if prob_start is not None else 525
- prob_end = int(prob_end) if prob_end is not None else 549
-
- probability = calculate_tweet_probability(tweet_count, days_to_next_friday, prob_start, prob_end)
-
- prob_low, prob_high = map(float, probability.split(" - "))
- formatted_probability = f"{prob_low * 100:.2f}% - {prob_high * 100:.2f}%"
-
- pace_table_rows = [
- html.Tr([
- html.Th(f"Probability ({prob_start}-{prob_end})", colSpan=2, style={'paddingRight': '10px'}),
- html.Td(formatted_probability, colSpan=6, style={'paddingRight': '10px'})
- ])
- ]
- pace_table = html.Table(pace_table_rows, style={
- 'width': '100%',
- 'textAlign': 'left',
- 'borderCollapse': 'collapse'
- })
- return [pace_table]
-
diff --git a/pkg/dash/func/info_test.py b/pkg/dash/func/info_test.py
deleted file mode 100644
index 48ed5cf..0000000
--- a/pkg/dash/func/info_test.py
+++ /dev/null
@@ -1,219 +0,0 @@
-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 os
-import csv
-import pandas as pd
-import re
-from datetime import timedelta
-from tqdm import tqdm
-from concurrent.futures import ProcessPoolExecutor, as_completed
-import multiprocessing as mp
-
-# 全局数据，避免重复加载
-global_data = None
-
-def initialize_global_data():
- global global_data
- if global_data is None:
- global_data = render_data.global_agg_df.copy()
- # 预计算常用列，避免重复操作
- global_data['hours'] = global_data['minute_of_day'] // 60
- global_data['minutes'] = global_data['minute_of_day'] % 60
- global_data['datetime_est'] = pd.to_datetime(
- global_data['date'].astype(str) + ' ' +
- global_data['hours'].astype(str) + ':' +
- global_data['minutes'].astype(str) + ':00',
- errors='coerce'
- ).dt.tz_localize('US/Eastern', ambiguous='NaT')
-
-@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, data=None):
- if n_clicks == 0:
- return [html.Div("Click 'Test' to see historical probability results.")]
-
- est = pytz.timezone('US/Eastern')
- data = data if data is not None else render_data.global_agg_df.copy()
-
- if not test_date or not test_time:
- return [html.Div("Date or time input is empty. Please provide both date (YYYY-MM-DD) and time (HH:MM:SS).")]
-
- time_pattern = r'^(?:[01]\d|2[0-3]):[0-5]\d:[0-5]\d$'
- if not re.match(time_pattern, test_time):
- return [html.Div("Invalid time format. Use HH:MM:SS (e.g., 12:00:00).")]
-
- try:
- test_datetime = pd.to_datetime(f"{test_date} {test_time}", format='%Y-%m-%d %H:%M:%S').tz_localize(est, ambiguous=True)
- except ValueError:
- return [html.Div("Invalid date or time format. Use YYYY-MM-DD and HH:MM:SS (e.g., 12:00:00).")]
-
- test_day_of_week = test_datetime.weekday()
- test_hour = test_datetime.hour
- days_since_last_friday = (test_day_of_week - 4) % 7
- if test_hour < 12 and test_day_of_week == 4:
- cycle_start = test_datetime - timedelta(days=days_since_last_friday + 7)
- else:
- cycle_start = test_datetime - timedelta(days=days_since_last_friday)
- cycle_start = cycle_start.replace(hour=12, minute=0, second=0, microsecond=0)
-
- cycle_end = cycle_start + timedelta(days=7)
- 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)
- else:
- cycle_end = cycle_end.tz_convert(est)
-
- days_to_next_friday = (cycle_end - test_datetime).total_seconds() / (24 * 60 * 60)
- if days_to_next_friday <= 0:
- return [html.Div(f"Test time {test_datetime} is at or past cycle end {cycle_end}.")]
-
- cycle_data = data[(data['datetime_est'] >= cycle_start) & (data['datetime_est'] <= test_datetime)]
- if cycle_data.empty:
- return [html.Div(f"No data available from {cycle_start} to {test_datetime}")]
-
- tweet_count = cycle_data['tweet_count'].sum()
-
- actual_data = data[(data['datetime_est'] >= cycle_start) & (data['datetime_est'] <= cycle_end)]
- if actual_data.empty:
- return [html.Div(f"No data available for cycle ending {cycle_end}")]
- actual_end_count = actual_data['tweet_count'].sum()
-
- days_elapsed = (test_datetime - cycle_start).total_seconds() / (24 * 60 * 60)
- if days_elapsed <= 0:
- return [html.Div(f"Test time {test_datetime} is before cycle start {cycle_start}.")]
-
- daily_avg = tweet_count / days_elapsed
- predicted_end_count = daily_avg * 7
- prob_start = predicted_end_count * 0.9
- prob_end = predicted_end_count * 1.1
-
- try:
- 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}%"
- except Exception as e:
- return [html.Div(f"Error calculating probability: {str(e)}")]
-
- test_table_rows = [
- html.Tr([html.Th("Cycle Start:", colSpan=4), html.Td(str(cycle_start), colSpan=6)]),
- html.Tr([html.Th("Test Date and Time:", colSpan=4), html.Td(str(test_datetime), colSpan=6)]),
- html.Tr([html.Th("Cycle End:", colSpan=4), html.Td(str(cycle_end), colSpan=6)]),
- html.Tr([html.Th("Tweet Count at Test Time:", colSpan=4), html.Td(str(tweet_count), colSpan=6)]),
- html.Tr([html.Th("Actual Final Tweet Count:", colSpan=4), html.Td(str(actual_end_count), colSpan=6)]),
- html.Tr([html.Th(f"Predicted Range ({int(prob_start)}-{int(prob_end)}):", colSpan=4), html.Td(formatted_probability, colSpan=6)]),
- html.Tr([html.Th("Does Actual Fall in Range?", colSpan=4),
- html.Td("Yes" if prob_start <= actual_end_count <= prob_end else "No",
- colSpan=6, style={'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=4),
- html.Td(f"~{expected_prob * 100:.2f}%", colSpan=6)]))
- else:
- test_table_rows.append(html.Tr([html.Th("Note:", colSpan=4),
- html.Td("Prediction does not match actual outcome.", colSpan=6, style={'color': 'red'})]))
-
- test_table = html.Table(test_table_rows, style={'width': '100%', 'textAlign': 'left', 'borderCollapse': 'collapse'})
- return [test_table]
-
-
-def process_test_case(args):
- test_datetime, data = args
- test_date = test_datetime.date().strftime('%Y-%m-%d')
- test_time = test_datetime.time().strftime('%H:%M:%S')
- n_clicks = 1
-
- result = update_test_info(n_clicks, test_date, test_time, data)
-
- if isinstance(result[0], html.Table):
- table = result[0]
- rows = table.children
-
- cycle_start = str(rows[0].children[1].children)
- test_dt = str(rows[1].children[1].children)
- cycle_end = str(rows[2].children[1].children)
- tweet_count = int(rows[3].children[1].children)
- actual_end_count = int(rows[4].children[1].children)
- prob_range = rows[5].children[1].children
- prob_min, prob_max = [float(x.strip('%')) for x in prob_range.split(" - ")]
- prob_start, prob_end = map(int, rows[5].children[0].children.split("(")[1].split(")")[0].split("-"))
- in_range = rows[6].children[1].children == "Yes"
- expected_prob = None
- note = ""
- if len(rows) > 7:
- if "Expected" in rows[7].children[0].children:
- expected_prob = float(rows[7].children[1].children.split()[0][1:-1])
- elif "Note" in rows[7].children[0].children:
- note = rows[7].children[1].children
-
- return [
- test_date, test_time, cycle_start, cycle_end, tweet_count,
- actual_end_count, prob_start, prob_end, prob_min, prob_max,
- "Yes" if in_range else "No", expected_prob if expected_prob is not None else "", note
- ]
- else:
- return [test_date, test_time, "", "", "", "", "", "", "", "", "", "", result[0].children]
-
-
-def run_loop_test(start_date="2024-10-01", end_date="2025-03-12", interval_hours=1, output_file="test_results.csv", max_workers=None, chunk_size=1000):
- est = pytz.timezone('US/Eastern')
- start_dt = pd.to_datetime(start_date).tz_localize(est)
- end_dt = pd.to_datetime(end_date).tz_localize(est)
- time_points = []
- current_dt = start_dt
- while current_dt <= end_dt:
- time_points.append(current_dt)
- current_dt += timedelta(hours=interval_hours)
-
- headers = [
- "Test Date", "Test Time", "Cycle Start", "Cycle End", "Tweet Count at Test Time",
- "Actual Final Tweet Count", "Predicted Range Start", "Predicted Range End",
- "Probability Min (%)", "Probability Max (%)", "Actual in Range", "Expected Probability (%)", "Note"
- ]
-
- if not os.path.exists(output_file):
- with open(output_file, 'w', newline='') as f:
- writer = csv.writer(f)
- writer.writerow(headers)
-
- # 预加载数据
- initialize_global_data()
- data = global_data
-
- total_steps = len(time_points)
- max_workers = max_workers or os.cpu_count() or 4
- chunk_size = min(chunk_size, total_steps) # 确保 chunk_size 不超过总任务数
-
- # 分块处理时间点
- chunks = [time_points[i:i + chunk_size] for i in range(0, total_steps, chunk_size)]
-
- with tqdm(total=total_steps, desc="Processing Test Cases", unit="step") as pbar:
- for chunk in chunks:
- results = []
- with ProcessPoolExecutor(max_workers=max_workers) as executor:
- futures = {executor.submit(process_test_case, (test_datetime, data)): test_datetime for test_datetime in chunk}
- for future in as_completed(futures):
- try:
- result = future.result()
- results.append(result)
- pbar.update(1)
- except Exception as e:
- test_datetime = futures[future]
- results.append([test_datetime.date().strftime('%Y-%m-%d'),
- test_datetime.time().strftime('%H:%M:%S'),
- "", "", "", "", "", "", "", "", "", "", f"Error: {str(e)}"])
- pbar.update(1)
-
- with open(output_file, 'a', newline='') as f:
- writer = csv.writer(f)
- writer.writerows(results)
-
-if __name__ == "__main__":
- run_loop_test(start_date="2024-10-01", end_date="2025-03-12", interval_hours=1, output_file="test_results.csv", chunk_size=1000)
\ No newline at end of file
diff --git a/pkg/dash/func/render.py b/pkg/dash/func/render.py
index ddeaa5f..f5aeb05 100644
--- a/pkg/dash/func/render.py
+++ b/pkg/dash/func/render.py
@@ -2,37 +2,25 @@ from datetime import datetime, timedelta
from dash.dependencies import Input, Output
from pkg.dash.app_init import app
from pkg.config import render_data
-from pkg.tool import aggregate_data, generate_xticks, minutes_to_time, get_tweets_since_last_friday
+from pkg.tool import aggregate_data, minutes_to_time, get_tweets_since_last_friday
from dash import dcc
import plotly.graph_objs as go
import pandas as pd
-
@app.callback(
[Output('tabs-content', 'children'),
Output('multi-day-warning', 'children'),
Output('multi-tweet-summary', 'children')],
[Input('tabs', 'value'),
- Input('multi-date-picker', 'value'),
Input('multi-interval-picker', 'value'),
- Input('time-zone-checklist', 'value'),
Input('days-display-picker', 'value')]
)
-def render_tab_content(tab, selected_dates, interval, time_zones, days_to_display):
+def render_tab_content(tab, interval, days_to_display):
warning = ""
- if tab == 'line':
- if not selected_dates: # Handle None or empty list
- selected_dates = [datetime.now().date()] # Default to today
- warning = "No dates selected. Showing today’s data."
- if len(selected_dates) > 10:
- selected_dates = selected_dates[:10]
- warning = "Maximum of 10 days can be selected. Showing first 10 selected days."
- selected_dates = [datetime.strptime(date, '%Y-%m-%d').date() for date in selected_dates]
- else:
- available_dates = sorted(render_data.global_agg_df['date'].unique(), reverse=True)
- selected_dates = available_dates[:days_to_display] if available_dates else [datetime.now().date()]
- if not available_dates:
- warning = "No data available. Showing today’s date with zero tweets."
+ available_dates = sorted(render_data.global_agg_df['date'].unique(), reverse=True)
+ selected_dates = available_dates[:days_to_display] if available_dates else [datetime.now().date()]
+ if not available_dates:
+ warning = "No data available. Showing today’s date with zero tweets."
multi_data_agg = render_data.global_agg_df[render_data.global_agg_df['date'].isin(selected_dates)].copy()
if multi_data_agg.empty:
@@ -47,23 +35,8 @@ def render_tab_content(tab, selected_dates, interval, time_zones, days_to_displa
tweet_count_total = 0
agg_data = aggregate_data(multi_data_agg, interval)
- xticks, xtick_labels = generate_xticks(interval)
- if tab == 'line':
- fig = go.Figure()
- for date in selected_dates:
- day_data = agg_data[agg_data['date'] == date]
- hover_times = [f"{date} {minutes_to_time(minute)} EST" for minute in day_data['interval_group']]
- fig.add_trace(go.Scatter(
- x=day_data['interval_group'],
- y=day_data['tweet_count'],
- mode='lines',
- name=str(date),
- customdata=hover_times,
- hovertemplate='%{customdata}
Tweets: %{y}'
- ))
-
- elif tab == 'heatmap':
+ if tab == 'heatmap':
pivot_data = agg_data.pivot(index='date', columns='interval_group', values='tweet_count').fillna(0)
pivot_data.index = pivot_data.index.astype(str)
fig = go.Figure(data=go.Heatmap(
@@ -77,7 +50,7 @@ def render_tab_content(tab, selected_dates, interval, time_zones, days_to_displa
for i, date_str in enumerate(pivot_data.index):
date = datetime.strptime(date_str, '%Y-%m-%d').date()
- if date.weekday() == 4: # Friday
+ if date.weekday() == 4:
prev_date = date - timedelta(days=1)
if str(prev_date) in pivot_data.index:
y_position = i / len(pivot_data.index)
@@ -105,8 +78,8 @@ def render_tab_content(tab, selected_dates, interval, time_zones, days_to_displa
for _, row in one_day_data.iterrows():
minute = row['interval_group']
- hour = int(minute // 60) # Convert to integer
- interval_idx = int((minute % 60) // interval) # Convert to integer
+ hour = int(minute // 60)
+ interval_idx = int((minute % 60) // interval)
if hour < 24:
z_values[hour][interval_idx] = row['tweet_count']
@@ -126,20 +99,12 @@ def render_tab_content(tab, selected_dates, interval, time_zones, days_to_displa
hovertemplate='%{y}:%{x} EST
Tweets: %{z}
Rate: %{customdata:.2%}'
))
- if tab in ['line', 'one_day_heatmap']:
fig.update_layout(
- title=f'{"Line" if tab == "line" else "One-Day Heatmap"} Tweet Frequency (Interval: {interval} minutes, EST, {len(selected_dates)} days)',
- xaxis_title='Minutes' if tab == 'one_day_heatmap' else 'Eastern Time (HH:MM)',
- yaxis_title='Hour of Day' if tab == 'one_day_heatmap' else 'Tweet Count',
- xaxis=dict(
- range=[0, 1440] if tab == 'line' else None,
- tickvals=xticks if tab == 'line' else None,
- ticktext=xtick_labels if tab == 'line' else None,
- tickangle=45 if tab == 'line' else 0
- ),
+ title=f'One-Day Heatmap Tweet Frequency (Interval: {interval} minutes, EST, {len(selected_dates)} days)',
+ xaxis_title='Minutes',
+ yaxis_title='Hour of Day',
height=600,
- showlegend=(tab == 'line'),
- yaxis=dict(autorange='reversed') if tab == 'one_day_heatmap' else None
+ yaxis=dict(autorange='reversed')
)
summary = f"Total tweets: {get_tweets_since_last_friday()}"
diff --git a/pkg/dash/func/ui.py b/pkg/dash/func/ui.py
index f447ff0..730c0cb 100644
--- a/pkg/dash/func/ui.py
+++ b/pkg/dash/func/ui.py
@@ -3,12 +3,9 @@ from dash.dependencies import Input, Output
@app.callback(
- [Output('date-picker-container', 'style'),
- Output('days-display-container', 'style'),
- Output('time-zone-checklist', 'style')],
+ [Output('days-display-container', 'style'),
+ Output('multi-interval-container', 'style')],
[Input('tabs', 'value')]
)
def toggle_controls_visibility(tab):
- if tab == 'heatmap' or tab == 'one_day_heatmap':
- return {'display': 'none'}, {'display': 'block'}, {'display': 'none'}
- return {'display': 'block'}, {'display': 'none'}, {'display': 'block'}
+ return {'display': 'block'},{'display': 'block'}