Create src/visualizers/chart_renderer.py

src/visualizers/chart_renderer.py

@@ -0,0 +1,216 @@
+import plotly.graph_objects as go
+from plotly.subplots import make_subplots
+import numpy as np
+
+class ChartRenderer:
+    def __init__(self):
+        pass
+    
+    def render_price_chart(self, prices, actions=None, current_step=0):
+        """Render price chart with actions"""
+        fig = go.Figure()
+        
+        if not prices:
+            # Return empty figure if no data
+            fig.update_layout(
+                title="Price Chart - No Data Available",
+                xaxis_title="Time Step",
+                yaxis_title="Price",
+                height=300,
+                template="plotly_white"
+            )
+            return fig
+        
+        # Add price line
+        fig.add_trace(go.Scatter(
+            x=list(range(len(prices))),
+            y=prices,
+            mode='lines',
+            name='Price',
+            line=dict(color='blue', width=2)
+        ))
+        
+        # Add action markers if provided
+        if actions and len(actions) == len(prices):
+            buy_indices = [i for i, action in enumerate(actions) if action == 1]
+            sell_indices = [i for i, action in enumerate(actions) if action == 2]
+            close_indices = [i for i, action in enumerate(actions) if action == 3]
+            
+            if buy_indices:
+                fig.add_trace(go.Scatter(
+                    x=buy_indices,
+                    y=[prices[i] for i in buy_indices],
+                    mode='markers',
+                    name='Buy',
+                    marker=dict(color='green', size=10, symbol='triangle-up', 
+                              line=dict(width=2, color='darkgreen'))
+                ))
+            
+            if sell_indices:
+                fig.add_trace(go.Scatter(
+                    x=sell_indices,
+                    y=[prices[i] for i in sell_indices],
+                    mode='markers',
+                    name='Sell',
+                    marker=dict(color='red', size=10, symbol='triangle-down', 
+                              line=dict(width=2, color='darkred'))
+                ))
+            
+            if close_indices:
+                fig.add_trace(go.Scatter(
+                    x=close_indices,
+                    y=[prices[i] for i in close_indices],
+                    mode='markers',
+                    name='Close',
+                    marker=dict(color='orange', size=8, symbol='x', 
+                              line=dict(width=2, color='darkorange'))
+                ))
+        
+        fig.update_layout(
+            title=f"Price Chart (Step: {current_step})",
+            xaxis_title="Time Step",
+            yaxis_title="Price",
+            height=300,
+            showlegend=True,
+            template="plotly_white"
+        )
+        
+        return fig
+    
+    def create_performance_chart(self, net_worth_history, reward_history, initial_balance):
+        """Create portfolio performance chart"""
+        fig = make_subplots(
+            rows=2, cols=1,
+            subplot_titles=['Portfolio Value Over Time', 'Step Rewards'],
+            vertical_spacing=0.15
+        )
+        
+        if not net_worth_history:
+            fig.update_layout(title="No Data Available", height=400)
+            return fig
+        
+        # Portfolio value
+        fig.add_trace(go.Scatter(
+            x=list(range(len(net_worth_history))),
+            y=net_worth_history,
+            mode='lines+markers',
+            name='Net Worth',
+            line=dict(color='green', width=3),
+            marker=dict(size=4)
+        ), row=1, col=1)
+        
+        # Add initial balance reference line
+        fig.add_hline(y=initial_balance, line_dash="dash", 
+                     line_color="red", annotation_text="Initial Balance",
+                     row=1, col=1)
+        
+        # Rewards as bar chart
+        if reward_history:
+            fig.add_trace(go.Bar(
+                x=list(range(len(reward_history))),
+                y=reward_history,
+                name='Reward',
+                marker_color=['green' if r >= 0 else 'red' for r in reward_history],
+                opacity=0.7
+            ), row=2, col=1)
+        
+        fig.update_layout(height=500, showlegend=False, template="plotly_white")
+        fig.update_yaxes(title_text="Value ($)", row=1, col=1)
+        fig.update_yaxes(title_text="Reward", row=2, col=1)
+        fig.update_xaxes(title_text="Step", row=2, col=1)
+        
+        return fig
+    
+    def create_action_distribution(self, actions):
+        """Create action distribution pie chart"""
+        fig = go.Figure()
+        
+        if not actions:
+            fig.update_layout(title="No Actions Available", height=300)
+            return fig
+        
+        action_names = ['Hold', 'Buy', 'Sell', 'Close']
+        action_counts = [actions.count(i) for i in range(4)]
+        
+        colors = ['blue', 'green', 'red', 'orange']
+        
+        fig = go.Figure(data=[go.Pie(
+            labels=action_names,
+            values=action_counts,
+            hole=.4,
+            marker_colors=colors,
+            textinfo='label+percent+value',
+            hoverinfo='label+percent+value'
+        )])
+        
+        fig.update_layout(
+            title="Action Distribution",
+            height=350,
+            annotations=[dict(text='Actions', x=0.5, y=0.5, font_size=16, showarrow=False)],
+            template="plotly_white"
+        )
+        
+        return fig
+    
+    def create_training_progress(self, training_history):
+        """Create training progress visualization"""
+        if not training_history:
+            fig = go.Figure()
+            fig.update_layout(title="No Training Data Available", height=500)
+            return fig
+        
+        episodes = [h['episode'] for h in training_history]
+        rewards = [h['reward'] for h in training_history]
+        net_worths = [h['net_worth'] for h in training_history]
+        losses = [h.get('loss', 0) for h in training_history]
+        
+        fig = make_subplots(
+            rows=2, cols=2,
+            subplot_titles=['Episode Rewards', 'Portfolio Value',
+                          'Training Loss', 'Moving Average Reward (5)'],
+            specs=[[{}, {}], [{}, {}]]
+        )
+        
+        # Rewards
+        fig.add_trace(go.Scatter(
+            x=episodes, y=rewards, mode='lines+markers',
+            name='Reward', line=dict(color='blue', width=2),
+            marker=dict(size=4)
+        ), row=1, col=1)
+        
+        # Portfolio value
+        fig.add_trace(go.Scatter(
+            x=episodes, y=net_worths, mode='lines+markers',
+            name='Net Worth', line=dict(color='green', width=2),
+            marker=dict(size=4)
+        ), row=1, col=2)
+        
+        # Loss
+        if any(loss > 0 for loss in losses):
+            fig.add_trace(go.Scatter(
+                x=episodes, y=losses, mode='lines+markers',
+                name='Loss', line=dict(color='red', width=2),
+                marker=dict(size=4)
+            ), row=2, col=1)
+        
+        # Moving average reward
+        if len(rewards) > 5:
+            ma_rewards = []
+            for i in range(len(rewards)):
+                start_idx = max(0, i - 4)
+                ma = np.mean(rewards[start_idx:i+1])
+                ma_rewards.append(ma)
+            
+            fig.add_trace(go.Scatter(
+                x=episodes, y=ma_rewards, mode='lines',
+                name='MA Reward (5)', line=dict(color='orange', width=3, dash='dash')
+            ), row=2, col=2)
+        
+        fig.update_layout(
+            height=600, 
+            showlegend=True, 
+            title_text="Training Progress Over Episodes",
+            template="plotly_white"
+        )
+        
+        return fig