From 8e3962db65d7e410da749d076c231586a3d67d12 Mon Sep 17 00:00:00 2001
From: NY <nnn@qq.com>
Date: Thu, 20 Mar 2025 09:48:47 +0800
Subject: [PATCH] fix

---
 pkg/config.py              | 4 +++-
 pkg/dash/func/info_test.py | 1 -
 pkg/tool.py                | 4 +---
 3 files changed, 4 insertions(+), 5 deletions(-)

diff --git a/pkg/config.py b/pkg/config.py
index 40d3f3d..2638681 100644
--- a/pkg/config.py
+++ b/pkg/config.py
@@ -26,7 +26,9 @@ interval_options = [
     {'label': '5 minutes', 'value': 5},
     {'label': '10 minutes', 'value': 10},
     {'label': '30 minutes', 'value': 30},
-    {'label': '60 minutes', 'value': 60}
+    {'label': '60 minutes', 'value': 60},
+    {'label': '⅓ day', 'value': 480},
+    {'label': '1 day', 'value': 1440}
 ]
 days_options = [
     {'label': '7 days', 'value': 7},
diff --git a/pkg/dash/func/info_test.py b/pkg/dash/func/info_test.py
index 5b9e6d2..48ed5cf 100644
--- a/pkg/dash/func/info_test.py
+++ b/pkg/dash/func/info_test.py
@@ -211,7 +211,6 @@ def run_loop_test(start_date="2024-10-01", end_date="2025-03-12", interval_hours
                                        "", "", "", "", "", "", "", "", "", "", f"Error: {str(e)}"])
                         pbar.update(1)
 
-            # 每处理完一个块写入 CSV
             with open(output_file, 'a', newline='') as f:
                 writer = csv.writer(f)
                 writer.writerows(results)
diff --git a/pkg/tool.py b/pkg/tool.py
index 5ab23b8..a3c70c7 100644
--- a/pkg/tool.py
+++ b/pkg/tool.py
@@ -1,6 +1,5 @@
 from datetime import datetime, timedelta
 import pandas as pd
-import numpy as np
 from pkg.config import render_data
 import pytz
 
@@ -17,7 +16,7 @@ def aggregate_data(data, interval):
     for date in data['date'].unique():
         day_data = data[data['date'] == date].copy()
         day_data['interval_group'] = (day_data['minute_of_day'] // interval) * interval
-        agg = day_data.groupby('interval_group').size().reset_index(name='tweet_count')
+        agg = day_data.groupby('interval_group')['tweet_count'].sum().reset_index(name='tweet_count')
         complete_data = all_minutes.merge(agg, on='interval_group', how='left').fillna({'tweet_count': 0})
         complete_data['date'] = date
         result.append(complete_data)
@@ -30,7 +29,6 @@ def aggregate_data(data, interval):
 
     return pd.concat(result, ignore_index=True)
 
-
 def generate_xticks(interval):
     if interval <= 5:
         tick_step = 60