Update file maxwell_integrate_to_h5.py

maxwell_integrate_to_h5.py

@@ -121,14 +121,27 @@ def integrate_ims_in_dir(path_im, path_int, dtype_im=".tif", dtype_int=".dat"):
             results_df = results_df.sort_values(by="filename", key=lambda col: col.str.lower())
             subdir_name = os.path.basename(os.path.normpath(subdir_path_int))
             results_df.to_csv(os.path.join(subdir_path_int, f"{subdir_name}.csv"), index=False)
-            results_df.to_hdf(os.path.join(subdir_path_int, f"{subdir_name}.h5"), key='data', mode='w')
+            results_df.to_hdf(os.path.join(subdir_path_int, f"{subdir_name}.h5"), key='entry/data', mode='w', format='table')
+
             with pd.HDFStore(os.path.join(subdir_path_int, f"{subdir_name}.h5"), mode='w') as hdf_store:
+                hdf_store.put("entry/definition", pd.Series(["NXdata"]), format='table')
+                hdf_store.put("entry/title", pd.Series([subdir_name]), format='table')
+                
+                # Create the NXdata group with Nexus conventions
+                nxdata_group = {
+                    "@axes": "q",
+                    "@signal": "I",
+                    "@errors": "dI"
+                }
+                hdf_store.put("entry/data/NXdata", pd.Series(nxdata_group), format='table')
+                
                 for result in results_data:
                     filename_key = os.path.basename(result["filename"])
-                    hdf_store.put(f"measurements/{filename_key}/q", pd.Series(result["q"]))
-                    hdf_store.put(f"measurements/{filename_key}/I", pd.Series(result["I"]))
-                    hdf_store.put(f"measurements/{filename_key}/dI", pd.Series(result["dI"]))
-            print(f"Results for subdirectory {subdir_name} saved to CSV and HDF5 files.")
+                    hdf_store.put(f"entry/data/{filename_key}/q", pd.Series(result["q"]), format='table')
+                    hdf_store.put(f"entry/data/{filename_key}/I", pd.Series(result["I"]), format='table')
+                    hdf_store.put(f"entry/data/{filename_key}/dI", pd.Series(result["dI"]), format='table')
+
+            print(f"Results for subdirectory {subdir_name} saved to CSV and HDF5 files using Nexus conventions.")
             del results_df
         else:
             print(f"No images were integrated in subdirectory {subdir}. No results DataFrame created.")