Update app.py

app.py

@@ -35,7 +35,6 @@ def calculate_percentiles(simulations):
     percentiles = np.percentile(simulations, [2.5, 16, 50, 84, 97.5], axis=0)
     return percentiles
 
-# Plot distributions
 def plot_distributions(bootstrap_simulations, data, thresholds, bootstrap_probabilities):
     final_bootstrap_prices = bootstrap_simulations[:, -1]
 
@@ -50,37 +49,54 @@ def plot_distributions(bootstrap_simulations, data, thresholds, bootstrap_probab
     # Plot for Bootstrapping
     fig.add_trace(go.Histogram(x=final_bootstrap_prices, nbinsx=50, name='Simulated Final Prices',
                                marker_color='blue', opacity=0.7))
-    fig.add_vline(x=mean_bootstrap_price, line=dict(color='red', dash='dash'), name=f'Mean: {mean_bootstrap_price:.2f}')
-    fig.add_vline(x=median_bootstrap_price, line=dict(color='orange', dash='dash'), name=f'Median: {median_bootstrap_price:.2f}')
-    fig.add_vline(x=latest_price, line=dict(color='green', dash='dash'), name=f'Latest Price: {latest_price:.2f}')
-    fig.add_vrect(x0=ci_68_bootstrap[0], x1=ci_68_bootstrap[1], fillcolor='yellow', opacity=0.2, layer="below", line_width=0, annotation_text="68% CI", annotation_position="top left")
-    fig.add_vrect(x0=ci_95_bootstrap[0], x1=ci_95_bootstrap[1], fillcolor='grey', opacity=0.2, layer="below", line_width=0, annotation_text="95% CI", annotation_position="top left")
-
-    max_freq = np.histogram(final_bootstrap_prices, bins=50)[0].max()
-
-    # Calculate positions based on a fraction of the max frequency
-    mean_y_pos = max_freq * 0.9
-    median_y_pos = max_freq * 0.7
-    latest_y_pos = max_freq * 0.5
-
-    # Annotations for the vertical lines
-    fig.add_annotation(x=mean_bootstrap_price, y=mean_y_pos, text=f'Mean: {mean_bootstrap_price:.2f}', showarrow=False)
-    fig.add_annotation(x=median_bootstrap_price, y=median_y_pos, text=f'Median: {median_bootstrap_price:.2f}', showarrow=False)
-    fig.add_annotation(x=latest_price, y=latest_y_pos, text=f'Latest: {latest_price:.2f}', showarrow=False)
-
-    fig.add_vline(x=mean_bootstrap_price, line=dict(color='red', dash='dash'), name='Mean', showlegend=True)
-    fig.add_vline(x=median_bootstrap_price, line=dict(color='orange', dash='dash'), name='Median', showlegend=True)
-    fig.add_vline(x=latest_price, line=dict(color='green', dash='dash'), name='Latest Price', showlegend=True)
 
+    # Replace add_vline with add_trace for vertical lines with legends
+    fig.add_trace(go.Scatter(
+        x=[mean_bootstrap_price, mean_bootstrap_price],
+        y=[0, np.histogram(final_bootstrap_prices, bins=50)[0].max()],
+        mode='lines',
+        line=dict(color='red', dash='dash'),
+        name=f'Mean: {mean_bootstrap_price:.2f}'
+    ))
+
+    fig.add_trace(go.Scatter(
+        x=[median_bootstrap_price, median_bootstrap_price],
+        y=[0, np.histogram(final_bootstrap_prices, bins=50)[0].max()],
+        mode='lines',
+        line=dict(color='orange', dash='dash'),
+        name=f'Median: {median_bootstrap_price:.2f}'
+    ))
+
+    fig.add_trace(go.Scatter(
+        x=[latest_price, latest_price],
+        y=[0, np.histogram(final_bootstrap_prices, bins=50)[0].max()],
+        mode='lines',
+        line=dict(color='green', dash='dash'),
+        name=f'Latest Price: {latest_price:.2f}'
+    ))
+
+    # Add confidence intervals as vertical shaded regions
+    fig.add_vrect(x0=ci_68_bootstrap[0], x1=ci_68_bootstrap[1], fillcolor='yellow', opacity=0.2, layer="below", line_width=0)
+    fig.add_vrect(x0=ci_95_bootstrap[0], x1=ci_95_bootstrap[1], fillcolor='grey', opacity=0.2, layer="below", line_width=0)
+
+    # Annotations for probabilities
     textstr = f'P(>{thresholds[1]:.2f}): {bootstrap_probabilities["above"]:.2%}<br>' + \
               f'P(<{thresholds[0]:.2f}): {bootstrap_probabilities["below"]:.2%}<br>' + \
               f'P({thresholds[0]:.2f} - {thresholds[1]:.2f}): {bootstrap_probabilities["between"]:.2%}'
-    fig.add_annotation(xref='paper', yref='paper', x=0.98, y=0.02, text=textstr, showarrow=False, 
+    fig.add_annotation(xref='paper', yref='paper', x=0.98, y=0.02, text=textstr, showarrow=False,
                        bordercolor="black", borderwidth=1, borderpad=4, bgcolor="white", opacity=0.4, font=dict(color="black"))
 
-    fig.update_layout(title='Bootstrapping Simulation', xaxis_title='Final Price', yaxis_title='Frequency', showlegend=True)
+    # Update layout
+    fig.update_layout(
+        title='Bootstrapping Simulation',
+        xaxis_title='Final Price',
+        yaxis_title='Frequency',
+        showlegend=True
+    )
+
     return fig, mean_bootstrap_price, median_bootstrap_price, ci_68_bootstrap, ci_95_bootstrap, latest_price
 
+
 # Plot price data with simulation cones
 def plot_price_with_cones(data, bootstrap_percentiles, days, thresholds, bootstrap_probabilities):
     last_date = data.index[-1]