Merge pull request #229 from bees4ever/PADDS-fix-status

update PADDS status
thouska · Aug 30, 2019 · 6f880ad · 6f880ad
2 parents b622b57 + f774baf
commit 6f880ad
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Showing 4 changed files with 7 additions and 5 deletions.
diff --git a/spotpy/algorithms/padds.py b/spotpy/algorithms/padds.py
@@ -218,6 +218,8 @@ def sample(self, repetitions, trials=1, initial_objs=np.array([]), initial_param
                     if self.dominance_flag != -1:  # means, that new parameter set is a new non-dominated solution
                         self.metric = self.calc_metric(metric)
                 self.parameter_current = x_curr
+                # update the new status structure
+                self.status.params_max, self.status.params_min = self.parameter_current, self.parameter_current
 
             print('Best solution found has obj function value of ' + str(self.best_value.best_obj_val) + ' at '
                   + str(repitionno_best) + '\n\n')

diff --git a/spotpy/examples/spot_setup_hymod_python_pareto.py b/spotpy/examples/spot_setup_hymod_python_pareto.py
@@ -62,12 +62,12 @@ def evaluation(self):
         return self.trueObs[366:]
 
     def objectivefunction(self,simulation,evaluation, params=None):
-        return [
+        return np.array([
             spotpy.likelihoods.gaussianLikelihoodMeasErrorOut(evaluation, simulation),
             -spotpy.objectivefunctions.rmse(evaluation, simulation),
             -spotpy.objectivefunctions.mse(evaluation, simulation),
             -spotpy.objectivefunctions.pbias(evaluation, simulation),
             spotpy.likelihoods.NashSutcliffeEfficiencyShapingFactor(evaluation, simulation),
             spotpy.likelihoods.ABCBoxcarLikelihood(evaluation, simulation),
             spotpy.likelihoods.LikelihoodAR1NoC(evaluation, simulation)
-        ]
+        ])
diff --git a/spotpy/examples/tutorial_padds.py b/spotpy/examples/tutorial_padds.py
@@ -83,5 +83,5 @@ def objectivefunction(self, simulation, evaluation, params):
 
 spot_setup = padds_spot_setup()
 
-#sampler = spotpy.algorithms.padds(spot_setup, dbname='padds_hymod', dbformat='csv', alt_objfun=None)
-#res = sampler.sample(10000,trials=1)
+sampler = spotpy.algorithms.padds(spot_setup, dbname='padds_hymod', dbformat='csv')
+res = sampler.sample(10000,trials=1)
diff --git a/spotpy/examples/tutorial_padds_hymod.py b/spotpy/examples/tutorial_padds_hymod.py
@@ -35,7 +35,7 @@
     # Create the SCE-UA sampler of spotpy, alt_objfun is set to None to force SPOTPY
     # to jump into the def objectivefunction in the spot_setup class (default is
     # spotpy.objectivefunctions.rmse) 
-    sampler=spotpy.algorithms.padds(spot_setup, dbname='padds_hymod', dbformat='csv', alt_objfun=None)
+    sampler=spotpy.algorithms.padds(spot_setup, dbname='padds_hymod', dbformat='csv')
 
     #Start the sampler, one can specify ngs, kstop, peps and pcento id desired
     print(sampler.sample(rep, metric="crowd_distance"))