Consider conf_sp job_type in the output folder txt files

Author: JintaoWu98

arc/plotter.py

@@ -901,6 +901,7 @@ def save_conformers_file(project_directory: str,
                          im_freqs: Optional[List[List[float]]] = None,
                          log_content: bool = False,
                          before_optimization: bool = True,
+                         sp_flag = False,
                          ):
     """
     Save the conformers before or after optimization.
@@ -920,6 +921,7 @@ def save_conformers_file(project_directory: str,
         im_freqs (list, optional): Entries lists of imaginary frequencies.
         log_content (bool): Whether to log the content of the conformers file. ``True`` to log, default is ``False``.
         before_optimization (bool): Whether the conformers are before DFT optimization. ``True`` for before, default is ``True``.
+        sp_flag (bool): Whether the conformers are single point calculations. ``True`` for single point, default is ``False``.
     """
     spc_dir = 'rxns' if is_ts else 'Species'
     geo_dir = os.path.join(project_directory, 'output', spc_dir, label, 'geometry', 'conformers')
@@ -936,7 +938,10 @@ def save_conformers_file(project_directory: str,
             content += f'Conformers for {label}, computed using a force field:\n\n'
         else:
             level_of_theory = level_of_theory.simple() if isinstance(level_of_theory, Level) else level_of_theory
-            content += f'Conformers for {label}, optimized at the {level_of_theory} level:\n\n'
+            if not sp_flag:
+                content += f'Conformers for {label}, optimized at the {level_of_theory} level:\n\n'
+            else:
+                content += f'Conformers for {label}, single point calculation at the {level_of_theory} level:\n\n'
         for i, xyz in enumerate(xyzs):
             content += f'conformer {i}:\n'
             if xyz is not None:

arc/scheduler.py

@@ -569,7 +569,7 @@ def schedule_jobs(self):
                                 if self.species_dict[label].is_ts:
                                     self.determine_most_likely_ts_conformer(label)
                                 else:
-                                    self.determine_most_stable_conformer(label)  # also checks isomorphism
+                                    self.determine_most_stable_conformer(label, sp_flag=True if self.job_types['conf_sp'] else False)  # also checks isomorphism
                                 if self.species_dict[label].initial_xyz is not None:
                                     # if initial_xyz is None, then we're probably troubleshooting conformers, don't opt
                                     if not self.composite_method:
@@ -2002,14 +2002,15 @@ def parse_conformer(self,
                 return True
         return False
 
-    def determine_most_stable_conformer(self, label):
+    def determine_most_stable_conformer(self, label, sp_flag=False):
         """
         Determine the most stable conformer for a species (which is not a TS).
         Also run an isomorphism check.
         Save the resulting xyz as `initial_xyz`.
 
         Args:
             label (str): The species label.
+            sp_flag (bool): Whether this is a single point calculation job.
         """
         if self.species_dict[label].is_ts:
             raise SchedulerError('The determine_most_stable_conformer() method does not deal with transition '
@@ -2031,12 +2032,13 @@ def determine_most_stable_conformer(self, label):
             plotter.save_conformers_file(project_directory=self.project_directory,
                                          label=label,
                                          xyzs=self.species_dict[label].conformers,
-                                         level_of_theory=self.conformer_opt_level,
+                                         level_of_theory=self.conformer_opt_level if not sp_flag else self.conformer_sp_level,
                                          multiplicity=self.species_dict[label].multiplicity,
                                          charge=self.species_dict[label].charge,
                                          is_ts=False,
                                          energies=self.species_dict[label].conformer_energies,
                                          before_optimization=False,
+                                         sp_flag=sp_flag,
                                          )  # after optimization
             # Run isomorphism checks if a 2D representation is available
             if self.species_dict[label].mol is not None: