refactor: remove unused should_profile and profile_log_likelihood_function

The profiling config option was always false and the method was never
overridden in any downstream project. Remove the dead code path from
SearchUpdater, NonLinearSearch, and Analysis.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

Author: 2 people

autofit/config/general.yaml

@@ -24,7 +24,6 @@ parallel:
   warn_environment_variables: true  # If True, a warning is displayed when the search's number of CPU > 1 and enviromment variables related to threading are also > 1.
 profiling:
   parallel_profile: false           # If True, the parallelization of the fit is profiled outputting a cPython graph.
-  should_profile: false             # If True, the ``profile_log_likelihood_function()`` function of an analysis class is called throughout a model-fit, profiling run times.
   repeats: 1                        # The number of repeat function calls used to measure run-times when profiling.
 test:
   check_likelihood_function: true   # if True, when a search is resumed the likelihood of a previous sample is recalculated to ensure it is consistent with the previous run.

autofit/non_linear/analysis/analysis.py

@@ -299,23 +299,6 @@ def make_result(
             analysis=analysis,
         )
 
-    def profile_log_likelihood_function(self, paths: AbstractPaths, instance):
-        """
-        Overwrite this function for profiling of the log likelihood function to be performed every update of a
-        non-linear search.
-
-        This behaves analogously to overwriting the `visualize` function of the `Analysis` class, whereby the user
-        fills in the project-specific behaviour of the profiling.
-
-        Parameters
-        ----------
-        paths
-            An object describing the paths for saving data (e.g. hard-disk directories or entries in sqlite database).
-        instance
-            The maximum likliehood instance of the model so far in the non-linear search.
-        """
-        pass
-
     def perform_quick_update(self, paths, instance):
         raise NotImplementedError
 

autofit/non_linear/search/abstract_search.py

@@ -224,8 +224,6 @@ def __init__(
 
         self.iterations = 0
 
-        self.should_profile = conf.instance["general"]["profiling"]["should_profile"]
-
         self.silence = silence
 
         if conf.instance["general"]["hpc"]["hpc_mode"]:
@@ -938,7 +936,6 @@ def _updater(self):
                 search_logger=self.logger,
                 plot_results_func=self.plot_results,
                 samples_from_func=self.samples_from,
-                should_profile=self.should_profile,
                 disable_output=self.disable_output,
                 iterations_per_full_update=self.iterations_per_full_update,
             )

autofit/non_linear/search/updater.py

@@ -44,7 +44,6 @@ def __init__(
         search_logger: logging.Logger,
         plot_results_func: Callable[[Samples], None],
         samples_from_func: Callable[[AbstractPriorModel, ...], Samples],
-        should_profile: bool,
         disable_output: bool,
         iterations_per_full_update: float,
     ):
@@ -53,7 +52,6 @@ def __init__(
         self._logger = search_logger
         self._plot_results = plot_results_func
         self._samples_from = samples_from_func
-        self._should_profile = should_profile
         self._disable_output = disable_output
         self._iterations_per_full_update = iterations_per_full_update
         self._iterations = 0
@@ -288,14 +286,7 @@ def _profile_and_summarize(
         latent_samples: Optional[Samples],
         visualization_time: float,
     ):
-        """Run profiling and write the search summary file."""
-        if self._should_profile:
-            self._logger.debug("Profiling Maximum Likelihood Model")
-            analysis.profile_log_likelihood_function(
-                paths=self._paths,
-                instance=instance,
-            )
-
+        """Write the search summary file."""
         self._logger.debug("Outputting model result")
 
         try:

test_autofit/config/general.yaml

@@ -21,7 +21,6 @@ parallel:
   warn_environment_variables: false # If True, a warning is displayed when the search's number of CPU > 1 and enviromment variables related to threading are also > 1.
 profiling:
   parallel_profile: false           # If True, the parallelization of the fit is profiled outputting a cPython graph.
-  should_profile: false             # If True, the ``profile_log_likelihood_function()`` function of an analysis class is called throughout a model-fit, profiling run times.
   repeats: 1                        # The number of repeat function calls used to measure run-times when profiling.
 test:
   check_likelihood_function: false  # if True, when a search is resumed the likelihood of a previous sample is recalculated to ensure it is consistent with the previous run.