Update app.py

app.py

@@ -12,6 +12,16 @@ def Phi(z):
 def phi(z):
     return norm.pdf(z)
 
+
+def F_BCNOLLN(y1, y2, params):
+    z1 = (y1 - mu_1) / sigma_1
+    z2 = (y2 - mu_2) / sigma_2
+    term = (Phi(z1)*params["alpha_1"] / H(z1, params["alpha_1"], params["beta_1"]))*(-params["lambda_val"]) + \
+           (Phi(z2)*params["alpha_2"] / H(z2, params["alpha_2"], params["beta_2"]))*(-params["lambda_val"]) - 1
+    return term**(-1/params["lambda_val"])
+
+
+
 def f_BCNOLLN(y1, y2, mu1, sigma1, alpha1, beta1, mu2, sigma2, alpha2, beta2, lambd):
     z1 = (y1 - mu1) / sigma1
     z2 = (y2 - mu2) / sigma2
@@ -55,6 +65,10 @@ y1, y2 = np.meshgrid(np.linspace(-3, 3, 100), np.linspace(-3, 3, 100))
 # Calculate PDF values
 pdf_values = f_BCNOLLN(y1, y2, mu1, sigma1, alpha1, beta1, mu2, sigma2, alpha2, beta2, lambd)
 
+# Calculate CDF values
+cdf_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')
@@ -76,5 +90,16 @@ fig.update_layout(title='BCNOLLN PDF 3D Contour Plot', autosize=True,
 # Display the plot in Streamlit
 st.plotly_chart(fig)
 
+# Create a 3D contour plot with Plotly
+fig = go.Figure(data=[go.Surface(z=cdf_values, x=y1, y=y2, colorscale='Viridis')])
+fig.update_layout(title='BCNOLLN CDF 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)