git checkout fea0;10;1cMerge branch 'main' of github.com:rhayes777/PyAutoFit

Author: Jammy2211

autofit/non_linear/search/abstract_search.py

@@ -683,6 +683,7 @@ def start_resume_fit(self, analysis: Analysis, model: AbstractPriorModel) -> Res
             model=model,
             analysis=analysis,
         )
+
         samples = self.perform_update(
             model=model,
             analysis=analysis,

autofit/non_linear/search/nest/dynesty/search/static.py

@@ -6,6 +6,8 @@
 from dynesty import NestedSampler as StaticSampler
 
 from autofit.database.sqlalchemy_ import sa
+from autofit import jax_wrapper
+
 from autofit.mapper.prior_model.abstract import AbstractPriorModel
 
 from .abstract import AbstractDynesty, prior_transform
@@ -109,6 +111,8 @@ def search_internal_from(
             in the dynesty queue for samples.
         """
 
+        gradient = fitness.grad if self.use_gradient else None
+
         if checkpoint_exists:
             search_internal = StaticSampler.restore(
                 fname=self.checkpoint_file, pool=pool
@@ -127,7 +131,7 @@ def search_internal_from(
                 self.write_uses_pool(uses_pool=True)
                 return StaticSampler(
                     loglikelihood=pool.loglike,
-                    gradient=fitness.grad,
+                    gradient=gradient,
                     prior_transform=pool.prior_transform,
                     ndim=model.prior_count,
                     live_points=live_points,
@@ -139,7 +143,7 @@ def search_internal_from(
             self.write_uses_pool(uses_pool=False)
             return StaticSampler(
                 loglikelihood=fitness,
-                gradient=fitness.grad,
+                gradient=gradient,
                 prior_transform=prior_transform,
                 ndim=model.prior_count,
                 logl_args=[model, fitness],

autofit/non_linear/search/nest/nautilus/search.py

@@ -338,7 +338,7 @@ def call_search(self, search_internal, model, analysis, fitness):
                     search_internal=search_internal
                 )
 
-        return search_internal, fitness
+        return search_internal
 
     def fit_mpi(self, fitness, model, analysis, checkpoint_exists: bool):
         """
@@ -396,7 +396,7 @@ def fit_mpi(self, fitness, model, analysis, checkpoint_exists: bool):
                 **self.config_dict_run,
             )
 
-        return search_internal, fitness
+        return search_internal
 
     def iterations_from(
         self, search_internal