Cleaner use of 'converged = opt.run()' in optimize and neb

Author: bernstei

wfl/generate/neb.py

@@ -89,11 +89,10 @@ def process_step():
 
         # preliminary value
         final_status = 'unconverged'
-        is_converged = False
+        converged = False
 
         try:
-            for is_converged in opt.irun(fmax=fmax, steps=steps):
-                pass
+            converged = opt.run(fmax=fmax, steps=steps)
         except Exception as exc:
             # label actual failed optimizations
             # when this happens, the atomic config somehow ends up with a 6-vector stress, which can't be
@@ -111,9 +110,9 @@ def process_step():
         for at in traj[0]:
             at.info['neb_config_type'] = 'neb_initial'
 
-        # from value returned by Optimizer.irun(), since Optimizer.converged requires
+        # from value returned by Optimizer.run(), since Optimizer.converged requires
         # a gradient as of ASE 3.26
-        if is_converged:
+        if converged:
             final_status = 'converged'
 
         for intermed_images in traj[1:-1]:

wfl/generate/optimize.py

@@ -159,9 +159,10 @@ def process_step():
 
         # preliminary value
         final_status = 'unconverged'
+        converged = False
 
         try:
-            opt.run(fmax=fmax, smax=smax, steps=steps)
+            converged = opt.run(fmax=fmax, smax=smax, steps=steps)
         except Exception as exc:
             # label actual failed optimizations
             # when this happens, the atomic config somehow ends up with a 6-vector stress, which can't be
@@ -184,9 +185,8 @@ def process_step():
 
         # as of 3.26 converged() requires a gradient, but for PreconLBFGS it's not used
         # See https://gitlab.com/ase/ase/-/issues/1744
-        # would like to use Optimizer.irun instead, since it returns converged status, but
-        # not supported for PreconLBFGS
-        if opt.converged(None):
+        # use value returned by Optimizer.run() instead
+        if converged:
             final_status = 'converged'
 
         traj[-1].info['optimize_config_type'] = f'optimize_last_{final_status}'