Download Button for Reduced Space

app.py

@@ -16,7 +16,8 @@ import json
 import itertools
 import matplotlib.pyplot as plt
 import matplotlib.colors as mcolors
-
+import zipfile
+import tempfile
 
 
 N_COMPONENTS = 3
@@ -1286,6 +1287,30 @@ def run_model(model_name):
                     # Mostrar el heatmap en la app
                     st.bokeh_chart(heatmap_fig)
 
+        # Botón para descargar df_all (Embeddings in PCA Space)
+        if st.button("Download Embeddings in PCA Space", key=f"click_download_pca_coordinates_{model_name}"):
+            # Crear un nuevo diccionario con solo las columnas que comienzan con "PC"
+            df_all_pca = {}
+            for key, df in df_all.items():
+                pca_cols = [col for col in df.columns if col.startswith("PC")]
+                df_all_pca[key] = df[pca_cols].copy()
+
+            # Crear un buffer en memoria para el archivo Excel
+            excel_buffer = io.BytesIO()
+            # Escribir cada DataFrame (solo con columnas PCA) en una hoja separada
+            with pd.ExcelWriter(excel_buffer, engine='openpyxl') as writer:
+                for key_name, df in df_all_pca.items():
+                    df.to_excel(writer, sheet_name=key_name, index=False)
+            excel_buffer.seek(0)
+            
+            st.download_button(
+                label="Download Embeddings in PCA Space",
+                data=excel_buffer,
+                file_name=f"df_all_pca_{model_name.lower()}.xlsx",
+                mime="application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
+                key=f"download_pca_coordinates_{model_name}"
+            )
+            
 
 def main():
     config_style()