f!

arc/plotter.py

@@ -900,7 +900,7 @@ def save_conformers_file(project_directory: str,
                          ts_methods: Optional[List[str]] = None,
                          im_freqs: Optional[List[List[float]]] = None,
                          log_content: bool = False,
-                         before_optimization: Optional[bool] = None,
+                         before_optimization: bool = True,
                          ):
     """
     Save the conformers before or after optimization.
@@ -919,26 +919,24 @@ def save_conformers_file(project_directory: str,
         ts_methods (list, optional): Entries are method names used to generate the TS guess.
         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``.
     """
     spc_dir = 'rxns' if is_ts else 'Species'
     geo_dir = os.path.join(project_directory, 'output', spc_dir, label, 'geometry', 'conformers')
     if not os.path.exists(geo_dir):
         os.makedirs(geo_dir)
-    if before_optimization or energies is None or not any(e is not None for e in energies):
-        optimized = False
+    if before_optimization:
         conf_path = os.path.join(geo_dir, 'conformers_before_optimization.txt')
-        min_e = extremum_list(energies, return_min=True) if before_optimization else None
     else:
-        optimized = True
-        min_e = extremum_list(energies, return_min=True)
         conf_path = os.path.join(geo_dir, 'conformers_after_optimization.txt')
+    min_e = extremum_list(energies, return_min=True)
     with open(conf_path, 'w') as f:
         content = ''
-        if optimized:
-            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 before_optimization:
             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'
         for i, xyz in enumerate(xyzs):
             content += f'conformer {i}:\n'
             if xyz is not None:
@@ -954,7 +952,7 @@ def save_conformers_file(project_directory: str,
                     content += f'TS guess method: {ts_methods[i]}\n'
                 if im_freqs is not None and im_freqs[i] is not None:
                     content += f'Imaginary frequencies: {im_freqs[i]}\n'
-                if optimized or before_optimization:
+                if min_e is not None:
                     if energies[i] == min_e:
                         content += 'Relative Energy: 0 kJ/mol (lowest)'
                     elif energies[i] is not None:

arc/plotter_test.py

@@ -92,7 +92,8 @@ def test_save_conformers_file(self):
         plotter.save_conformers_file(project_directory=project_directory, label=spc1.label,
                                      xyzs=spc1.conformers, level_of_theory='APFD/def2tzvp',
                                      multiplicity=spc1.multiplicity, charge=spc1.charge, is_ts=False,
-                                     energies=spc1.conformer_energies)
+                                     energies=spc1.conformer_energies,
+                                     before_optimization=True,)
         conf_file_path = os.path.join(project_directory, 'output', 'Species', label, 'geometry', 'conformers',
                                       'conformers_before_optimization.txt')
         self.assertTrue(os.path.isfile(conf_file_path))

arc/scheduler.py

@@ -1139,6 +1139,7 @@ def run_ts_conformer_jobs(self, label: str):
                         f'{tsg.method_direction if tsg.method_direction is not None else ""} '
                         f'{tsg.method_index if tsg.method_index is not None else ""} '
                         for tsg in self.species_dict[label].ts_guesses],
+            before_optimization=True,
         )
         successful_tsgs = [tsg for tsg in self.species_dict[label].ts_guesses if tsg.success]
         if len(successful_tsgs) > 1:
@@ -2023,8 +2024,9 @@ def determine_most_stable_conformer(self, label):
                                          multiplicity=self.species_dict[label].multiplicity,
                                          charge=self.species_dict[label].charge,
                                          is_ts=False,
-                                         energies=self.species_dict[label].conformer_energies,  # after optimization
-                                         )
+                                         energies=self.species_dict[label].conformer_energies,
+                                         before_optimization=False,
+                                         )  # after optimization
             # Run isomorphism checks if a 2D representation is available
             if self.species_dict[label].mol is not None:
                 for i, xyz in enumerate(xyzs):
@@ -2239,6 +2241,7 @@ def determine_most_likely_ts_conformer(self, label: str):
                             for tsg in self.species_dict[label].ts_guesses],
                 im_freqs=[tsg.imaginary_freqs for tsg in self.species_dict[label].ts_guesses]
                     if any(tsg.imaginary_freqs is not None for tsg in self.species_dict[label].ts_guesses) else None,
+                before_optimization=False,
             )
 
     def parse_composite_geo(self,
@@ -2574,6 +2577,7 @@ def check_negative_freq(self,
                                 for tsg in self.species_dict[label].ts_guesses],
                     im_freqs=[tsg.imaginary_freqs for tsg in self.species_dict[label].ts_guesses]
                         if any(tsg.imaginary_freqs is not None for tsg in self.species_dict[label].ts_guesses) else None,
+                    before_optimization=False,
                 )
                 if not self.testing:
                     # Update restart dictionary and save the yaml restart file:

arc/scheduler_test.py

@@ -184,7 +184,8 @@ def test_conformers(self):
                              xyzs=self.sched1.species_dict['C2H6'].conformers,
                              level_of_theory=Level(method='CBS-QB3'),
                              multiplicity=1,
-                             charge=0)
+                             charge=0,
+                             before_optimization=True,)
         c2h6_conf_path = os.path.join(self.sched1.project_directory, 'output', 'Species', 'C2H6', 'geometry',
                                       'conformers', 'conformers_before_optimization.txt')
         self.assertTrue(os.path.isfile(c2h6_conf_path))

arc/species/species_test.py

@@ -1548,13 +1548,15 @@ def test_append_conformers(self):
 
         # test w/o energies
         save_conformers_file(project_directory=project_directory, label='vinoxy', xyzs=xyzs,
-                             level_of_theory=Level(repr='level1'), multiplicity=2, charge=0)
+                             level_of_theory=Level(repr='level1'), multiplicity=2, charge=0,
+                             before_optimization=True,)
         self.assertTrue(os.path.isfile(os.path.join(project_directory, 'output', 'Species', 'vinoxy', 'geometry',
                                                     'conformers', 'conformers_before_optimization.txt')))
 
         # test with energies
         save_conformers_file(project_directory=project_directory, label='vinoxy', xyzs=xyzs,
-                             level_of_theory=Level(repr='level1'), multiplicity=2, charge=0, energies=energies)
+                             level_of_theory=Level(repr='level1'), multiplicity=2, charge=0, 
+                             energies=energies, before_optimization=False,)
         self.assertTrue(os.path.isfile(os.path.join(project_directory, 'output', 'Species', 'vinoxy', 'geometry',
                                                     'conformers', 'conformers_after_optimization.txt')))