Update app.py

app.py

@@ -61,8 +61,6 @@ def PDF_Preparation(Your_PDF_Name, Qmin, Qmax, Qdamp, rmax, nyquist):
     # Create a new figure object
     fig, ax = plt.subplots()
 
-    st.write(r)
-    st.write(Gr[0,3:])
     # Plot the transformation to make sure everything is alright
     ax.plot(PDF[:,0], PDF[:,1], label="Original Data")
     ax.plot(r, Gr[0,3:], label="Gr ready for ML")
@@ -80,7 +78,8 @@ def POMPredicter(POMFinder, Gr, y_onehotenc_cat):
     y_pred_proba = y_pred_proba[:,1];
     res = sorted(range(len(y_pred_proba)), key = lambda sub: y_pred_proba[sub]);
     res.reverse();
-    st.write("The 1st guess from the model is: ", str(y_onehotenc_cat.categories_[0][res[0]])[2:-2]+"cale.xyz")
+    st.markdown(f'<span style="font-size: 24px; color: green;">The 1st guess from the model is: <b>{str(y_onehotenc_cat.categories_[0][res[0]])[2:-2]+"cale.xyz"}</b></span> <hr/>',unsafe_allow_html=True,)
+    #st.write("The 1st guess from the model is: ", str(y_onehotenc_cat.categories_[0][res[0]])[2:-2]+"cale.xyz")
     st.write("The 2nd guess from the model is: ", str(y_onehotenc_cat.categories_[0][res[1]])[2:-2]+"cale.xyz")
     st.write("The 3rd guess from the model is: ", str(y_onehotenc_cat.categories_[0][res[2]])[2:-2]+"cale.xyz")
     st.write("The 4th guess from the model is: ", str(y_onehotenc_cat.categories_[0][res[3]])[2:-2]+"cale.xyz")