Update app.py

app.py

@@ -3,6 +3,7 @@ import streamlit as st
 import numpy as np
 import matplotlib.pyplot as plt
 from scipy.stats import norm
+import plotly.graph_objects as go
 
 # Define the functions from your code
 def Phi(z):
@@ -55,11 +56,25 @@ y1, y2 = np.meshgrid(np.linspace(-3, 3, 100), np.linspace(-3, 3, 100))
 pdf_values = f_BCNOLLN(y1, y2, mu1, sigma1, alpha1, beta1, mu2, sigma2, alpha2, beta2, lambd)
 
 # Plotting
-fig, ax = plt.subplots()
-cp = ax.contourf(y1, y2, pdf_values, cmap='viridis')
-fig.colorbar(cp)
-ax.set_title('BCNOLLN PDF Contour Plot')
-ax.set_xlabel('y1')
-ax.set_ylabel('y2')
+#fig, ax = plt.subplots()
+#cp = ax.contourf(y1, y2, pdf_values, cmap='viridis')
+#fig.colorbar(cp)
+#ax.set_title('BCNOLLN PDF Contour Plot')
+#ax.set_xlabel('y1')
+#ax.set_ylabel('y2')
 
-st.pyplot(fig)
+
+# Create a 3D contour plot with Plotly
+fig = go.Figure(data=[go.Surface(z=pdf_values, x=y1, y=y2, colorscale='Viridis')])
+fig.update_layout(title='BCNOLLN PDF 3D Contour Plot', autosize=True,
+                  scene=dict(
+                      xaxis_title='y1',
+                      yaxis_title='y2',
+                      zaxis_title='PDF'
+                  ))
+
+# Display the plot in Streamlit
+st.plotly_chart(fig)
+
+
+#st.pyplot(fig)