Add optional parameter to store methods

src/f3dasm/_src/design/domain.py

@@ -268,22 +268,26 @@ def from_data(cls: Type[Domain],
 #                                                                        Export
 # =============================================================================
 
-    def store(self, filename: Path) -> None:
+    def store(self, filename: Path, create_tmp: bool = False) -> None:
         """Stores the Domain in a pickle file.
 
         Parameters
         ----------
         filename : str
             Name of the file.
         """
-        with open(filename.with_suffix('.tmp'), 'wb') as f:
-            pickle.dump(self, f)
+        if create_tmp:
+            with open(filename.with_suffix('.tmp'), 'wb') as f:
+                pickle.dump(self, f)
 
-        # remove old file if it exists
-        filename.with_suffix('.pkl').unlink(missing_ok=True)
+            # remove old file if it exists
+            filename.with_suffix('.pkl').unlink(missing_ok=True)
 
-        # rename the file to the correct extension
-        filename.with_suffix('.tmp').rename(filename.with_suffix('.pkl'))
+            # rename the file to the correct extension
+            filename.with_suffix('.tmp').rename(filename.with_suffix('.pkl'))
+        else:
+            with open(filename.with_suffix('.pkl'), 'wb') as f:
+                pickle.dump(self, f)
 
     def _cast_types_dataframe(self) -> dict:
         """Make a dictionary that provides the datatype of each parameter"""

src/f3dasm/_src/experimentdata/_data.py

@@ -251,7 +251,7 @@ def to_dataframe(self) -> pd.DataFrame:
         df.columns = self.names
         return df.astype(object)
 
-    def store(self, filename: Path) -> None:
+    def store(self, filename: Path, create_tmp: bool = False) -> None:
         """Stores the data to a file.
 
         Parameters
@@ -263,14 +263,19 @@ def store(self, filename: Path) -> None:
         ----
         The data is stored as a csv file.
         """
-        # TODO: The column information is not saved in the .csv!
-        self.to_dataframe().to_csv(filename.with_suffix('.tmp'))
 
-        # remove the old file if it exists
-        filename.with_suffix('.csv').unlink(missing_ok=True)
+        if create_tmp:
+            self.to_dataframe().to_csv(filename.with_suffix('.tmp'))
 
-        # rename the file to the correct extension
-        filename.with_suffix('.tmp').rename(filename.with_suffix('.csv'))
+            # remove the old file if it exists
+            filename.with_suffix('.csv').unlink(missing_ok=True)
+
+            # rename the file to the correct extension
+            filename.with_suffix('.tmp').rename(filename.with_suffix('.csv'))
+
+        else:
+            # TODO: The column information is not saved in the .csv!
+            self.to_dataframe().to_csv(filename.with_suffix('.csv'))
 
     def n_best_samples(self, nosamples: int,
                        column_name: List[str] | str) -> pd.DataFrame:

src/f3dasm/_src/experimentdata/_jobqueue.py

@@ -189,21 +189,24 @@ def select_all(self, status: str) -> _JobQueue:
     #                                                                    Export
     # =========================================================================
 
-    def store(self, filename: Path) -> None:
+    def store(self, filename: Path, create_tmp: bool = False) -> None:
         """Stores the jobs in a pickle file.
 
         Parameters
         ----------
         filename : Path
             Path of the file.
         """
-        self.jobs.to_pickle(filename.with_suffix('.tmp'))
+        if create_tmp:
+            self.jobs.to_pickle(filename.with_suffix('.tmp'))
 
-        # remove old file if it exists
-        filename.with_suffix('.pkl').unlink(missing_ok=True)
+            # remove old file if it exists
+            filename.with_suffix('.pkl').unlink(missing_ok=True)
 
-        # rename the file to the correct extension
-        filename.with_suffix('.tmp').rename(filename.with_suffix('.pkl'))
+            # rename the file to the correct extension
+            filename.with_suffix('.tmp').rename(filename.with_suffix('.pkl'))
+        else:
+            self.jobs.to_pickle(filename.with_suffix('.pkl'))
 
     def to_dataframe(self, name: str = "") -> pd.DataFrame:
         """Converts the job queue to a DataFrame.

src/f3dasm/_src/experimentdata/experimentdata.py

@@ -551,7 +551,8 @@ def get_output_data(self,
     #                                                                    Export
     # =========================================================================
 
-    def store(self, project_dir: Optional[Path | str] = None):
+    def store(self, project_dir: Optional[Path | str] = None,
+              create_tmp: bool = False):
         """Write the ExperimentData to disk in the project directory.
 
         Parameters
@@ -589,10 +590,18 @@ def store(self, project_dir: Optional[Path | str] = None):
         # Create the subdirectory if it does not exist
         subdirectory.mkdir(parents=True, exist_ok=True)
 
-        self._input_data.store(subdirectory / Path(INPUT_DATA_FILENAME))
-        self._output_data.store(subdirectory / Path(OUTPUT_DATA_FILENAME))
-        self._jobs.store(subdirectory / Path(JOBS_FILENAME))
-        self.domain.store(subdirectory / Path(DOMAIN_FILENAME))
+        self._input_data.store(
+            filename=subdirectory / Path(INPUT_DATA_FILENAME),
+            create_tmp=create_tmp)
+        self._output_data.store(
+            filename=subdirectory / Path(OUTPUT_DATA_FILENAME),
+            create_tmp=create_tmp)
+        self._jobs.store(
+            filename=subdirectory / Path(JOBS_FILENAME),
+            create_tmp=create_tmp)
+        self.domain.store(
+            filename=subdirectory / Path(DOMAIN_FILENAME),
+            create_tmp=create_tmp)
 
     def to_numpy(self) -> Tuple[np.ndarray, np.ndarray]:
         """