Update app.py

app.py

@@ -361,7 +361,7 @@ def generate_trading_signals(df):
     df['Stochastic_Signal'] = np.where((df['SlowK'] > 100) & (df['SlowD'] > 100), -1, df['Stochastic_Signal'])
 
     # Less strict CMF Signal - Use ±0.1 instead of ±0.4
-    df['CMF_Signal'] = np.where(df['CMF'] > 0.3, -1, np.where(df['CMF'] < -0.3, 1, 0))
+    df['CMF_Signal'] = np.where(df['CMF'] > 0.4, -1, np.where(df['CMF'] < -0.4, 1, 0))
 
     # Less strict CCI Signal - Standard thresholds (±100 instead of ±220)
     df['CCI_Signal'] = np.where(df['CCI'] < -100, 1, 0)
@@ -373,7 +373,7 @@ def generate_trading_signals(df):
 
     return df
 
-def plot_combined_signals(df, ticker):
+def plot_combined(df, ticker):
     # Create a figure
     fig = go.Figure()
 
@@ -445,6 +445,48 @@ def plot_combined_signals(df, ticker):
 
     return fig
 
+import plotly.graph_objects as go
+
+def plot_combined_signals(df, ticker):
+    """
+    Creates a focused plot of JUST the combined signal strength.
+    Bars are colored green for positive (buy) signals and red for negative (sell) signals.
+    """
+    # Create a new figure
+    fig = go.Figure()
+
+    # Define colors based on the signal value (positive/negative)
+    colors = ['#2ECC71' if val >= 0 else '#E74C3C' for val in df['Combined_Signal']]
+    
+    # Add the bar chart for the combined signal
+    fig.add_trace(go.Bar(
+        x=df.index,
+        y=df['Combined_Signal'],
+        name='Signal Strength',
+        marker_color=colors,
+        # Add hover text for clarity
+        hovertemplate='<b>Date</b>: %{x}<br><b>Signal</b>: %{y}<extra></extra>'
+    ))
+
+    # Update the layout for a clean, focused look
+    fig.update_layout(
+        title={
+            'text': f'Strength Indicator for {ticker}',
+            'y':0.9,
+            'x':0.5,
+            'xanchor': 'center',
+            'yanchor': 'top',
+            'font': {'size': 20}
+        },
+        template='plotly_dark',
+        xaxis_title='Date',
+        yaxis_title='Signal Strength Score',
+        yaxis=dict(zeroline=True, zerolinewidth=2, zerolinecolor='gray'),
+        showlegend=False # Not needed for a single trace
+    )
+
+    return fig
+
 def plot_individual_signals(df, ticker):
     # Create a figure
     fig = go.Figure()