Update core/plot.py

core/plot.py

@@ -6,7 +6,7 @@ import logging
 
 logging.basicConfig(level=logging.INFO)
 
-def plot_indicators(df, ticker, account_size=10000, risk_percent=1):
+def plot_indicators(df, ticker):
     try:
         fig = make_subplots(
             rows=5, cols=1, shared_xaxes=True, vertical_spacing=0.02,
@@ -16,9 +16,9 @@ def plot_indicators(df, ticker, account_size=10000, risk_percent=1):
         fig.add_trace(go.Candlestick(x=df['Date'], open=df['Open'], high=df['High'], low=df['Low'], close=df['value'],
                                      name='Price', increasing_line_color='#00CC96', decreasing_line_color='#EF553B'), row=1, col=1)
         for ma in ['sma_10', 'sma_20', 'sma_50', 'ema_12', 'ema_26', 'ema_50']:
-            if ma in df.columns:
+            if ma in df:
                 fig.add_trace(go.Scatter(x=df['Date'], y=df[ma], name=ma.upper(), line=dict(width=1)), row=1, col=1)
-        if 'bbu_20_2.0' in df.columns:
+        if 'bbu_20_2.0' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['bbu_20_2.0'], name='BB Upper', line=dict(color='gray', dash='dot')), row=1, col=1)
             fig.add_trace(go.Scatter(x=df['Date'], y=df['bbm_20_2.0'], name='BB Middle', line=dict(color='gray')), row=1, col=1)
             fig.add_trace(go.Scatter(x=df['Date'], y=df['bbl_20_2.0'], name='BB Lower', line=dict(color='gray', dash='dot')), row=1, col=1)
@@ -26,43 +26,66 @@ def plot_indicators(df, ticker, account_size=10000, risk_percent=1):
         sell_signals = df[df['Signal'] == 'Sell']
         fig.add_trace(go.Scatter(x=buy_signals['Date'], y=buy_signals['value'], mode='markers', name='Buy', marker=dict(symbol='triangle-up', size=12, color='green')), row=1, col=1)
         fig.add_trace(go.Scatter(x=sell_signals['Date'], y=sell_signals['value'], mode='markers', name='Sell', marker=dict(symbol='triangle-down', size=12, color='red')), row=1, col=1)
-        if 'atr_14' in df.columns:
+        if 'atr_14' in df:
             atr = df['atr_14'].iloc[-1]
             stop_distance = atr * 2
-            position_size = (account_size * (risk_percent / 100)) / stop_distance
-            fig.add_annotation(text=f"Suggested Position Size: {position_size:.0f} shares (Risk {risk_percent}%, ATR {atr:.2f})",
+            position_size = (10000 * (1 / 100)) / stop_distance
+            fig.add_annotation(text=f"Suggested Position Size: {position_size:.0f} shares (Risk 1%, ATR {atr:.2f})",
                                xref="paper", yref="paper", x=0.05, y=0.95, showarrow=False, font=dict(color="black", size=12))
         fig.add_trace(go.Bar(x=df['Date'], y=df['Volume'], name='Volume', marker_color='blue'), row=2, col=1)
-        if 'macd_12_26_9' in df.columns:
+        if 'macd_12_26_9' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['macd_12_26_9'], name='MACD', line=dict(color='blue')), row=3, col=1)
             fig.add_trace(go.Scatter(x=df['Date'], y=df['macds_12_26_9'], name='MACD Signal', line=dict(color='orange')), row=3, col=1)
             fig.add_trace(go.Bar(x=df['Date'], y=df['macdh_12_26_9'], name='MACD Hist', marker_color='gray'), row=3, col=1)
-        if 'rsi_14' in df.columns:
+        if 'rsi_14' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['rsi_14'], name='RSI 14', line=dict(color='purple')), row=3, col=1)
-            fig.add_hline(y=70, line_dash="dash", line_color="red", row=3, col=1, annotation_text="Overbought")
-            fig.add_hline(y=30, line_dash="dash", line_color="green", row=3, col=1, annotation_text="Oversold")
-        if 'stochk_14_3_3' in df.columns:
+            fig.add_hline(y=70, line_dash="dash", line_color="red", row=3, col=1)
+            fig.add_hline(y=30, line_dash="dash", line_color="green", row=3, col=1)
+        if 'stochk_14_3_3' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['stochk_14_3_3'], name='Stoch %K', line=dict(color='blue')), row=4, col=1)
             fig.add_trace(go.Scatter(x=df['Date'], y=df['stochd_14_3_3'], name='Stoch %D', line=dict(color='orange')), row=4, col=1)
-        if 'willr_14' in df.columns:
+        if 'willr_14' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['willr_14'], name='Williams %R', line=dict(color='green')), row=4, col=1)
             fig.add_hline(y=-20, line_dash="dash", line_color="red", row=4, col=1)
             fig.add_hline(y=-80, line_dash="dash", line_color="green", row=4, col=1)
-        if 'adx_14' in df.columns:
+        if 'adx_14' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['adx_14'], name='ADX', line=dict(color='blue')), row=5, col=1)
-            if 'pdi_14' in df.columns:
-                fig.add_trace(go.Scatter(x=df['Date'], y=df['pdi_14'], name='+DI', line=dict(color='green')), row=5, col=1)
-            if 'mdi_14' in df.columns:
-                fig.add_trace(go.Scatter(x=df['Date'], y=df['mdi_14'], name='-DI', line=dict(color='red')), row=5, col=1)
-        if 'atr_14' in df.columns:
+            fig.add_trace(go.Scatter(x=df['Date'], y=df.get('pdi_14'), name='+DI', line=dict(color='green')), row=5, col=1)
+            fig.add_trace(go.Scatter(x=df['Date'], y=df.get('mdi_14'), name='-DI', line=dict(color='red')), row=5, col=1)
+        if 'atr_14' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['atr_14'], name='ATR', line=dict(color='orange')), row=5, col=1)
-        if 'cci_20' in df.columns:
+        if 'cci_20' in df:
             fig.add_trace(go.Scatter(x=df['Date'], y=df['cci_20'], name='CCI', line=dict(color='purple')), row=5, col=1)
             fig.add_hline(y=100, line_dash="dash", line_color="red", row=5, col=1)
             fig.add_hline(y=-100, line_dash="dash", line_color="green", row=5, col=1)
-        fig.update_layout(title=f"{ticker} Advanced Trading Chart", height=1200, width=1400, template="plotly_white", showlegend=True, xaxis_rangeslider_visible=False)
-        fig.update_xaxes(tickformat="%Y-%m-%d %H:%M", rangeslider_visible=False, tickangle=45, automargin=True)
-        fig.update_yaxes(automargin=True)
+        fig.update_layout(title=f"{ticker} Price and Technical Indicators",
+                          template="plotly_white",
+                          height=2000,
+                          width=1400,
+                          showlegend=True,
+                          xaxis_rangeslider_visible=False,
+                          margin=dict(l=40, r=40, t=80, b=40),
+                          xaxis=dict(
+                              tickformat="%Y-%m-%d",
+                              minor=dict(ticks="inside", showgrid=True),
+                              gridcolor="lightgrey",
+                              minor_gridcolor="whitesmoke",
+                              showticklabels=True
+                          ),
+                          yaxis=dict(gridcolor="lightgrey", minor=dict(ticks="inside", showgrid=True), minor_gridcolor="whitesmoke"),
+                          title_font=dict(size=20, color="black"),
+                          plot_bgcolor="white",
+                          paper_bgcolor="white"
+                          )
+        for i in range(2, 6):
+            fig.update_xaxes(
+                tickformat="%Y-%m-%d",
+                minor=dict(ticks="inside", showgrid=True),
+                gridcolor="lightgrey",
+                minor_gridcolor="whitesmoke",
+                showticklabels=True if i == 5 else False,
+                row=i, col=1
+            )
         return fig
     except Exception as e:
         logging.error(f"Plot indicators error: {e}")
@@ -75,27 +98,24 @@ def plot_forecast(result, df):
         if len(actual) == 0 or len(forecast) == 0:
             logging.warning("No actual or forecast data provided for plotting.")
             return None
-        dates = df['Date'].iloc[-len(actual):]
+        if 'Date' not in df.columns:
+            logging.error("DataFrame missing 'Date' column.")
+            return None
+        dates = df['Date'].iloc[-len(actual):]  # Align with actual data length
         logging.info(f"Plotting forecast with date range: {dates.iloc[0]} to {dates.iloc[-1]}")
         if len(dates) != len(actual):
             logging.warning(f"Date length ({len(dates)}) does not match actual data length ({len(actual)}).")
             return None
         fig = go.Figure()
         fig.add_trace(go.Scatter(x=dates, y=actual, mode='lines', name='Actual', line=dict(color='#00CC96')))
-        prev = forecast[0]
-        for i in range(1, len(forecast)):
-            color = '#00FF00' if forecast[i] > prev else '#FF0000'
-            fig.add_trace(go.Scatter(x=dates[i-1:i+1], y=[forecast[i-1], forecast[i]], mode='lines', showlegend=False, line=dict(color=color, width=2)))
-            prev = forecast[i]
-        trend = 'Rising' if forecast[-1] > forecast[0] else 'Falling'
-        fig.add_annotation(text=f"Trend: {trend}", xref="paper", yref="paper", x=0.05, y=0.95, showarrow=False, font=dict(size=14, color="blue"))
+        fig.add_trace(go.Scatter(x=dates, y=forecast, mode='lines', name='Forecast', line=dict(color='#EF553B')))
         fig.update_layout(
             title="Actual vs Forecast",
             template="plotly_white",
             height=600,
             xaxis_title="Date",
             yaxis_title="Price",
-            xaxis=dict(tickformat="%Y-%m-%d %H:%M", tickangle=45, automargin=True, minor=dict(ticks="inside", showgrid=True), gridcolor="lightgrey", minor_gridcolor="whitesmoke"),
+            xaxis=dict(tickformat="%Y-%m-%d", minor=dict(ticks="inside", showgrid=True), gridcolor="lightgrey", minor_gridcolor="whitesmoke"),
             yaxis=dict(gridcolor="lightgrey", minor=dict(ticks="inside", showgrid=True), minor_gridcolor="whitesmoke"),
             plot_bgcolor="white",
             paper_bgcolor="white"
@@ -114,27 +134,15 @@ def plot_future_forecast(df, result, timeframe):
         freq_map = {'1m': 'T', '2m': '2T', '5m': '5T', '15m': '15T', '30m': '30T', '60m': 'H', '90m': '90T', '1h': 'H', '1d': 'D', '5d': '5D', '1wk': 'W', '1mo': 'M', '3mo': '3M'}
         future_dates = pd.date_range(start=last_date + pd.Timedelta(days=1), periods=len(latest_pred), freq=freq_map.get(timeframe, 'D'))
         fig = go.Figure()
-        hist_y = df['value'].tail(30).values
-        hist_x = df['Date'].tail(30)
-        fig.add_trace(go.Scatter(x=hist_x, y=hist_y, mode='lines', name='Historical', line=dict(color='#00CC96')))
-        prev = latest_pred[0]
-        for i in range(1, len(latest_pred)):
-            color = '#00FF00' if latest_pred[i] > prev else '#FF0000'
-            fig.add_trace(go.Scatter(x=[future_dates[i-1], future_dates[i]], y=[latest_pred[i-1], latest_pred[i]], mode='lines', showlegend=False, line=dict(color=color, width=2)))
-            prev = latest_pred[i]
-        ci_lower, ci_upper = result["metrics"].get("CI_Lower", latest_pred[0] - 1), result["metrics"].get("CI_Upper", latest_pred[0] + 1)
-        ci_width = (ci_upper - ci_lower) / 2
-        fig.add_trace(go.Scatter(x=future_dates, y=[p + ci_width for p in latest_pred], mode='lines', line=dict(color='transparent'), showlegend=False, name='CI Upper'))
-        fig.add_trace(go.Scatter(x=future_dates, y=[p - ci_width for p in latest_pred], fill='tonexty', mode='lines', line=dict(color='transparent'), fillcolor='rgba(0,100,80,0.2)', name='Confidence Interval'))
-        trend = 'Rising' if latest_pred[-1] > latest_pred[0] else 'Falling'
-        fig.add_annotation(text=f"Trend: {trend}", xref="paper", yref="paper", x=0.05, y=0.95, showarrow=False, font=dict(size=14, color="blue"))
+        fig.add_trace(go.Scatter(x=df['Date'].tail(30), y=df['value'].tail(30), mode='lines', name='Historical', line=dict(color='#00CC96')))
+        fig.add_trace(go.Scatter(x=future_dates, y=latest_pred, mode='lines', name='Forecast', line=dict(color='#EF553B')))
         fig.update_layout(
             title="Future Forecast",
             template="plotly_white",
             height=600,
             xaxis_title="Date",
             yaxis_title="Price",
-            xaxis=dict(tickformat="%Y-%m-%d %H:%M", tickangle=45, automargin=True, minor=dict(ticks="inside", showgrid=True), gridcolor="lightgrey", minor_gridcolor="whitesmoke"),
+            xaxis=dict(tickformat="%Y-%m-%d", minor=dict(ticks="inside", showgrid=True), gridcolor="lightgrey", minor_gridcolor="whitesmoke"),
             yaxis=dict(gridcolor="lightgrey", minor=dict(ticks="inside", showgrid=True), minor_gridcolor="whitesmoke"),
             plot_bgcolor="white",
             paper_bgcolor="white"
@@ -174,9 +182,12 @@ def plot_metrics_errors(result):
             return None
         fig = go.Figure()
         fig.add_trace(go.Bar(
-            x=['RMSE', 'MAE'],
-            y=[metrics.get('RMSE', 0), metrics.get('MAE', 0)],
-            marker_color=['#1E90FF', '#FF6347']
+            x=['RMSE', 'MAE', 'CI_Lower', 'CI_Upper'],
+            y=[
+                metrics.get('RMSE', 0), metrics.get('MAE', 0),
+                metrics.get('CI_Lower', 0), metrics.get('CI_Upper', 0)
+            ],
+            marker_color=['#1E90FF', '#FF6347', '#00CED1', '#FF4500']
         ))
         fig.update_layout(
             title="Error Metrics",