Update app.py

app.py

@@ -17,7 +17,7 @@ DEVELOPER_NAME = "汪于捷、李哲弘、黃千宥、陳奕瑄、洪寓澤"
 NEWS_CSV_PATH = 'cryptonews.csv'
 BTC_CSV_PATH = 'BTC.csv'
 PROCESSED_DATA_PATH = 'processed_btc_sentiment_data.csv'
-
+PLOTLY_TEMPLATE = "plotly_dark"
 SENTIMENT_PIPELINE = None
 
 def initialize_pipeline():
@@ -146,7 +146,7 @@ def plot_price_and_sentiment(filtered_df, sentiment_col, sentiment_name, color):
         yaxis=dict(title='價格 (USD)', color='deepskyblue'),
         yaxis2=dict(title='情緒分數', overlaying='y', side='right', color=color, range=[-1, 1]),
         legend=dict(x=0.01, y=0.99, orientation='h'),
-        # template='plotly_dark', 
+        template=PLOTLY_TEMPLATE, 
         paper_bgcolor='rgba(0,0,0,0)', plot_bgcolor='rgba(0,0,0,0.2)'
     )
     return fig
@@ -158,7 +158,7 @@ def plot_subjectivity_trend(filtered_df):
         # title='🧐 每日新聞主觀性趨勢',
         xaxis_title='日期',
         yaxis=dict(title='主觀性分數 (0=客觀, 1=主觀)', color='lightgreen', range=[0, 1]),
-        # template='plotly_dark', 
+        template=PLOTLY_TEMPLATE, 
         paper_bgcolor='rgba(0,0,0,0)', plot_bgcolor='rgba(0,0,0,0.2)'
     )
     return fig
@@ -175,7 +175,7 @@ def plot_correlation(filtered_df, sentiment_col, lag_days):
     fig.update_layout(
         title=f'🔗 情緒與 {lag_days} 天後價格變化的關聯性 (相關係數: {correlation:.3f})',
         xaxis_title='每日平均情緒分數', yaxis_title=f'{lag_days} 天後價格變化 (%)',
-        # template='plotly_dark', 
+        template=PLOTLY_TEMPLATE, 
         paper_bgcolor='rgba(0,0,0,0)', plot_bgcolor='rgba(0,0,0,0.2)'
     )
     return fig, correlation, p_value