minor

python/tffpy/experiments/exp_approx.py

@@ -21,17 +21,29 @@ class ApproxExperiment(SolveTffExperiment):
         res = self.load_results(array_type='xarray')
         res = res.squeeze()
         tff_list = res.to_dict()['coords']['solver_tol_subregions']['data']
+        tol_list = res.to_dict()['coords']['solver_tolerance_arrf']['data']
         for measure in ['sdr_tff', 'sdr_tffo', 'sdr_tffe',
                         'is_tff', 'is_tffo', 'is_tffe']:
             for solver_tol_subregions in tff_list:
+                for tol in tol_list:
+                    mean_res = float(res.sel(
+                        solver_tolerance_arrf=tol,
+                        solver_tol_subregions=solver_tol_subregions,
+                        measure=measure).mean())
                     std_res = float(res.sel(
-                    measure=measure,
-                    solver_tol_subregions=solver_tol_subregions).std())
+                        solver_tolerance_arrf=tol,
+                        solver_tol_subregions=solver_tol_subregions,
+                        measure=measure).std())
+                    t_res = float(res.sel(
+                        solver_tolerance_arrf=tol,
+                        solver_tol_subregions=solver_tol_subregions,
+                        measure='t_arrf').mean())
                     if solver_tol_subregions is None:
                         measure_name = measure + '-1'
                     else:
                         measure_name = measure + '-P'
-                print('std({}): {}'.format(measure_name, std_res))
+                    print('{}: mean={:.2f} std={:.2g} tol={}, t={}'
+                          .format(measure_name, mean_res, std_res, tol, t_res))
 
     def plot_results(self):
         # No more need for this method