Upload app.py

app.py

@@ -56,10 +56,10 @@ for key, value in default_values.items():
 def calculate_absorption_area(volume, reverberation_time):
     return 0.161 * volume / reverberation_time if reverberation_time else float('inf')
 
-def generate_pdf(volume: float, current_rt: Dict[int, float], existing_materials: List[Dict[str, Any]],
-                 min_rt: Dict[int, float], max_rt: Dict[int, float], desired_rt: Dict[int, float],
-                 new_materials: List[Dict[str, Any]], fig1: go.Figure, fig2: go.Figure,
-                 sound_pressure: pd.DataFrame, updated_sound_pressure: pd.DataFrame, noise_reduction: float) -> bytes:
+def generate_pdf(volume, current_rt, existing_materials, min_rt, max_rt, desired_rt, new_materials, fig1, fig2, df_sound_pressure, updated_df):
+    from fpdf import FPDF
+    import tempfile
+    import kaleido
 
     pdf = FPDF()
     pdf.add_page()
@@ -97,20 +97,24 @@ def generate_pdf(volume: float, current_rt: Dict[int, float], existing_materials
             fig.write_image(tmpfile.name, engine='kaleido')
             pdf.image(tmpfile.name, x=10, y=None, w=180)
 
+    # Add sound pressure levels data
     pdf.add_page()
     pdf.cell(200, 10, txt="Current Sound Pressure Levels (dB):", ln=True)
-    for index, row in sound_pressure.iterrows():
-        pdf.cell(200, 10, txt=f"{index}: {', '.join([f'{val:.2f}' for val in row])}", ln=True)
-
-    pdf.cell(200, 10, txt="Noise Reduction (dB):", ln=True)
-    pdf.cell(200, 10, txt=f"{noise_reduction:.2f}", ln=True)
+    for index, row in df_sound_pressure.iterrows():
+        pdf.cell(200, 10, txt=f"{index}:", ln=True)
+        for col in df_sound_pressure.columns:
+            pdf.cell(200, 10, txt=f"{col} Hz: {row[col]:.2f}", ln=True)
 
+    # Add updated sound pressure levels data
     pdf.cell(200, 10, txt="Updated Sound Pressure Levels (dB):", ln=True)
-    for index, row in updated_sound_pressure.iterrows():
-        pdf.cell(200, 10, txt=f"{index}: {', '.join([f'{val:.2f}' for val in row])}", ln=True)
+    for index, row in updated_df.iterrows():
+        pdf.cell(200, 10, txt=f"{index}:", ln=True)
+        for col in updated_df.columns:
+            pdf.cell(200, 10, txt=f"{col} Hz: {row[col]:.2f}", ln=True)
 
     return pdf.output(dest='S').encode('latin1')
 
+
 def read_uploaded_file(uploaded_file, header=0, index_col=None):
     try:
         if uploaded_file.name.endswith('.csv'):
@@ -728,16 +732,23 @@ def display_intelligibility_noise_reduction():
     **IMPORTANT NOTE ABOUT PDF REPORT:** The purpose of the PDF report is to provide you detailed record of all
     your input data and the graphs generated. Graphs in PDF report are of low resolutions. Hence, remember to download 
     individual graphs and tables to include in your report. Hover your mouse over a graph and several icons would
-    appear at the top right corner of the graph, click the first icon to download the graph. Repeat the same process
+    appear at the top right corner of the graph, click the first icon to download the graph. Repeat the same process 
     to download tables.
     """)
     if st.button("Download PDF Report"):
-        pdf = generate_pdf(st.session_state.volume, st.session_state.current_rt,
-                           st.session_state.existing_materials, st.session_state.min_rt_val,
-                           st.session_state.max_rt_val, st.session_state.desired_rt,
-                           st.session_state.new_materials, st.session_state.fig1, st.session_state.fig2,
-                           st.session_state.df_sound_pressure, st.session_state.updated_sound_pressure,
-                           st.session_state.noise_reduction)
+        pdf = generate_pdf(
+            st.session_state.volume,
+            st.session_state.current_rt,
+            st.session_state.existing_materials,
+            {freq: st.session_state.min_rt_val for freq in st.session_state.frequencies},
+            {freq: st.session_state.max_rt_val for freq in st.session_state.frequencies},
+            st.session_state.desired_rt,
+            st.session_state.new_materials,
+            st.session_state.fig1,
+            st.session_state.fig2,
+            st.session_state.df_sound_pressure,
+            updated_df
+        )
         st.download_button(label="Download PDF", data=pdf, file_name="Room_Acoustics_Report.pdf",
                            mime="application/pdf")