Sensible error if nan in objective evaluation from trust-region step

dfols/controller.py

@@ -41,7 +41,7 @@
 
 __all__ = ['Controller', 'ExitInformation', 'EXIT_SLOW_WARNING', 'EXIT_MAXFUN_WARNING', 'EXIT_SUCCESS',
            'EXIT_INPUT_ERROR', 'EXIT_TR_INCREASE_ERROR', 'EXIT_LINALG_ERROR', 'EXIT_FALSE_SUCCESS_WARNING',
-           'EXIT_AUTO_DETECT_RESTART_WARNING']
+           'EXIT_AUTO_DETECT_RESTART_WARNING', 'EXIT_EVAL_ERROR']
 
 module_logger = logging.getLogger(__name__) 
 
@@ -54,6 +54,7 @@
 EXIT_INPUT_ERROR = -1  # error, bad inputs
 EXIT_TR_INCREASE_ERROR = -2  # error, trust region step increased model value
 EXIT_LINALG_ERROR = -3  # error, linalg error (singular matrix encountered)
+EXIT_EVAL_ERROR = -4  # error, objective evaluation error (e.g. nan result received)
 
 
 class ExitInformation(object):
@@ -83,11 +84,13 @@ def message(self, with_stem=True):
             return "Error (linear algebra): " + self.msg
         elif self.flag == EXIT_FALSE_SUCCESS_WARNING:
             return "Warning (max false good steps): " + self.msg
+        elif self.flag == EXIT_EVAL_ERROR:
+            return "Error (function evaluation): " + self.msg
         else:
             return "Unknown exit flag: " + self.msg
 
     def able_to_do_restart(self):
-        if self.flag in [EXIT_TR_INCREASE_ERROR, EXIT_TR_INCREASE_WARNING, EXIT_LINALG_ERROR, EXIT_SLOW_WARNING, EXIT_AUTO_DETECT_RESTART_WARNING]:
+        if self.flag in [EXIT_TR_INCREASE_ERROR, EXIT_TR_INCREASE_WARNING, EXIT_LINALG_ERROR, EXIT_SLOW_WARNING, EXIT_AUTO_DETECT_RESTART_WARNING, EXIT_EVAL_ERROR]:
             return True
         elif self.flag in [EXIT_MAXFUN_WARNING, EXIT_INPUT_ERROR]:
             return False

dfols/solver.py

@@ -516,6 +516,17 @@ def solve_main(objfun, x0, args, xl, xu, projections, npt, rhobeg, rhoend, maxfu
             x = control.model.as_absolute_coordinates(xnew)
             number_of_samples = max(nsamples(control.delta, control.rho, current_iter, nruns_so_far), 1)
             rvec_list, f_list, num_samples_run, exit_info = control.evaluate_objective(x, number_of_samples, params)
+            if np.any(np.isnan(rvec_list)):
+                # Just exit without saving the current point
+                # We should be able to do a hard restart though, because it's unlikely 
+                # that we will get the same trust-region step after expanding the radius/re-initialising
+                module_logger.warning("NaN encountered in evaluation of trust-region step")
+                if params("interpolation.throw_error_on_nans"):
+                    raise np.linalg.LinAlgError("NaN encountered in objective evaluations")
+
+                exit_info = ExitInformation(EXIT_EVAL_ERROR, "NaN received from objective function evaluation")
+                nruns_so_far += 1
+                break  # quit
             if exit_info is not None:
                 if num_samples_run > 0:
                     control.model.save_point(x, np.mean(rvec_list[:num_samples_run, :], axis=0), num_samples_run,