加了target

pkg/dash/app_html.py

@@ -160,7 +160,15 @@ def layout_config(app):
                 dcc.Tab(label='Heatmap(1-day)', value='one_day_heatmap'),
             ]),
             html.Div(id='tabs-content'),
+            dcc.Input(
+                id='target-input',
+                type='number',
+                placeholder='输入 Target 值',
+                value=None,
+                style={'marginTop': '10px', 'width': '50%'}
+            ),
         ], style={'marginLeft': '50px'}),
+
         dcc.Interval(id='clock-interval', interval=1000, n_intervals=0)
     ])
     return app

pkg/dash/func/info.py

@@ -1,5 +1,5 @@
 import pytz
-from pkg.tool import get_tweets_since_last_friday, format_time_str, get_time_since_last_tweet
+from pkg.tool import get_tweets_since_last_friday, format_time_str, get_time_since_last_tweet, get_hourly_weighted_array
 from pkg.dash.app_init import app
 from dash.dependencies import Input, Output
 from datetime import timedelta
@@ -9,19 +9,25 @@ from dash import html
 
 @app.callback(
     [Output('info-tooltip', 'children')],
-    [Input('clock-interval', 'n_intervals')]
+    [Input('clock-interval', 'n_intervals'),
+     Input('target-input', 'value')]
 )
-def update_info(n):
+def update_info(n, target_value):
-    # 获取所有指标
     pace = calculate_tweet_pace()
     decline_rates = calculate_pace_decline_rate()
     pace_increases = calculate_pace_increase_in_hour()
-    _, days_to_next_friday = get_pace_params()
+    tweet_count, days_to_next_friday = get_pace_params()
+    remain_hours = days_to_next_friday * 24
+    now = tweet_count
     table_style_border = {'textAlign': 'center', 'border': '1px solid white'}
     table_style_c = {'textAlign': 'center'}
     table_style_l = {'textAlign': 'left'}
 
-    # First table for Pace
+    target = int(target_value) if target_value is not None else None
+    avg_tweets_per_day = calculate_avg_tweets_per_day(target, now, remain_hours) if target is not None else "未计算"
+    days_passed = 7 - days_to_next_friday
+    avg_tweets = round(tweet_count / days_passed, 2) if days_passed > 0 else 0
+
     pace_table_rows = [
         html.Tr([
             html.Th('Pace', style=table_style_border),
@@ -66,6 +72,22 @@ def update_info(n):
             html.Td("1.Check Reply",
                     colSpan=7,
                     style=table_style_l)
+        ]),
+        html.Tr([
+            html.Td(f"Target: {target if target else '[未设置]'}",
+                    colSpan=4,
+                    style=table_style_c),
+            html.Td(f"Need's Avg Tweets Per Day: {avg_tweets_per_day}",
+                    colSpan=4,
+                    style=table_style_l)
+        ]),
+        html.Tr([
+            html.Td(f"Avg Tweets: {avg_tweets}",
+                    colSpan=4,
+                    style=table_style_c),
+            html.Td("",  # 右侧留空，与上一行对齐
+                    colSpan=4,
+                    style=table_style_l)
         ])
     ]
     pace_table = html.Table(pace_table_rows, style={
@@ -114,6 +136,42 @@ def calculate_pace_increase_in_hour():
         new_tweet_count = tweet_count + increment
         new_pace = (new_tweet_count / (7 - future_days)) * future_days + new_tweet_count
         pace_increase = new_pace - current_pace
-        # Add current pace to the increase value
         pace_increases[f'increase_{increment}'] = round(current_pace + pace_increase, 2)
     return pace_increases
+
+
+def calculate_avg_tweets_per_day(target, now, remain):
+    Xi = get_hourly_weighted_array()
+    if remain <= 0:
+        return "剩余时间不足，无法计算"
+    if target <= now:
+        return "目标已达成，无需额外发帖"
+
+    fx = max(remain - 12, 0)
+
+    if remain > 12:
+        fy = sum(Xi[0:12]) * 24
+    else:
+        full_hours = int(remain)
+        fractional_hour = remain - full_hours
+        if full_hours >= 24:
+            print(f"Debug: full_hours={full_hours} exceeds 24, capping at 23")
+            full_hours = 23
+            fractional_hour = 0  # 如果超过24小时，小数部分忽略
+
+        if full_hours < 0:
+            print(f"Debug: full_hours={full_hours} is negative, setting to 0")
+            full_hours = 0
+
+        if full_hours > 0:
+            fy = sum(Xi[0:full_hours]) + Xi[full_hours] * fractional_hour
+        else:
+            fy = Xi[0] * fractional_hour
+        fy *= 24
+
+    if fx + fy == 0:
+        return "计算无效，请检查剩余时间"
+
+    result = (target - now) / ((fx + fy) / 24)
+    print(f"Debug: fx={fx}, fy={fy}, result={result}")
+    return round(result, 2)

pkg/dash/func/render.py

@@ -112,13 +112,18 @@ def render_tab_content(tab, selected_dates, interval, time_zones, days_to_displa
 
         x_labels = [f"{i * interval:02d}" for i in range(intervals_per_hour)]
 
+        rate_values = [[z_values[h][i] / tweet_count_total if tweet_count_total > 0 else 0
+                        for i in range(intervals_per_hour)]
+                       for h in range(24)]
+
         fig = go.Figure(data=go.Heatmap(
             z=z_values,
             x=x_labels,
             y=[f"{h:02d}" for h in hours],
             colorscale='Viridis',
             hoverongaps=False,
-            hovertemplate='%{y}:%{x} EST<br>Tweets: %{z}<extra></extra>'
+            customdata=rate_values,
+            hovertemplate='%{y}:%{x} EST<br>Tweets: %{z}<br>Rate: %{customdata:.2%}<extra></extra>'
         ))
 
     if tab in ['line', 'one_day_heatmap']:

pkg/tool.py

@@ -95,3 +95,33 @@ def format_time_str(days_to_next_friday):
     seconds = int(total_seconds % 60)
     total_hours = round(days_to_next_friday * 24, 2)
     return f"{days}d {hours:02d}h {minutes:02d}m {seconds:02d}s ({total_hours}h)"
+
+
+def get_hourly_weighted_array():
+    est = pytz.timezone('US/Eastern')
+    now = datetime.now(est).date()
+    last_7_days = [now - timedelta(days=i) for i in range(7)]
+
+    multi_data_agg = render_data.global_agg_df[
+        render_data.global_agg_df['date'].isin(last_7_days)].copy()
+
+    if multi_data_agg.empty:
+        return [1 / 24] * 24
+
+    agg_data = aggregate_data(multi_data_agg, 60)
+    one_day_data = agg_data.groupby('interval_group')['tweet_count'].sum().reset_index()
+    tweet_count_total = one_day_data['tweet_count'].sum()
+
+    hourly_rates = [0] * 24
+    for _, row in one_day_data.iterrows():
+        minute = row['interval_group']
+        hour = int(minute // 60)
+        if hour < 24:
+            hourly_rates[hour] = row['tweet_count'] / tweet_count_total if tweet_count_total > 0 else 0
+
+    total_rate = sum(hourly_rates)
+    if total_rate > 0:
+        hourly_rates = [rate / total_rate for rate in hourly_rates]
+    else:
+        hourly_rates = [1 / 24] * 24
+    return hourly_rates

plan.md

@@ -1,5 +1,7 @@
 #### 后续
 1. 考虑通过 tweets 数预测市场曲线的模型（人工智能）
 2. 考虑elon jets的效果
+3. 推算出达到某个市场要求，这七天内的发帖情况应该是什么样的。
+4. peak点预期：人工智能预测peak时间段，并列举出peak情况对应市场期望。