better output, bugfixes for controllers

Author: pancetta

pySDC/implementations/controller_classes/controller_MPI.py

@@ -77,6 +77,10 @@ def run(self, u0, t0, Tend):
         all_time = [t0 + sum(all_dt[0:i]) for i in range(num_procs)]
         time = all_time[rank]
         all_active = all_time < Tend - 10 * np.finfo(float).eps
+
+        if not any(all_active):
+            raise ControllerError('Nothing to do, check t0, dt and Tend')
+
         active = all_active[rank]
         if not all(all_active):
             comm_active = self.comm.Split(active)

pySDC/implementations/controller_classes/controller_nonMPI.py

@@ -101,6 +101,9 @@ def run(self, u0, t0, Tend):
         # determine which steps are still active (time < Tend)
         active = [time[p] < Tend - 10 * np.finfo(float).eps for p in slots]
 
+        if not any(active):
+            raise ControllerError('Nothing to do, check t0, dt and Tend.')
+
         # compress slots according to active steps, i.e. remove all steps which have times above Tend
         active_slots = list(itertools.compress(slots, active))
 

pySDC/playgrounds/parallel/AllenCahn_contracting_circle_FFT.py

@@ -97,7 +97,7 @@ def run_SDC_variant(variant=None):
         raise NotImplemented('Wrong variant specified, got %s' % variant)
 
     # setup parameters "in time"
-    t0 = 0
+    t0 = 0.0
     Tend = 0.032
 
     # set MPI communicator
@@ -141,29 +141,20 @@ def run_SDC_variant(variant=None):
 
     rank = comm.Get_rank()
 
-    if rank == 0:
-
-        # filter statistics by variant (number of iterations)
-        filtered_stats = filter_stats(stats, type='niter')
+    # filter statistics by variant (number of iterations)
+    filtered_stats = filter_stats(stats, type='niter')
 
-        # convert filtered statistics to list of iterations count, sorted by process
-        iter_counts = sort_stats(filtered_stats, sortby='time')
+    # convert filtered statistics to list of iterations count, sorted by process
+    iter_counts = sort_stats(filtered_stats, sortby='time')
 
-        # compute and print statistics
-        niters = np.array([item[1] for item in iter_counts])
-        out = '   Mean number of iterations: %4.2f' % np.mean(niters)
-        print(out)
-        out = '   Range of values for number of iterations: %2i ' % np.ptp(niters)
-        print(out)
-        out = '   Position of max/min number of iterations: %2i -- %2i' % \
-              (int(np.argmax(niters)), int(np.argmin(niters)))
-        print(out)
-        out = '   Std and var for number of iterations: %4.2f -- %4.2f' % (float(np.std(niters)), float(np.var(niters)))
-        print(out)
+    # compute and print statistics
+    niters = np.array([item[1] for item in iter_counts])
+    print(f'Mean number of iterations on rank {rank}: {np.mean(niters):.4f}')
 
+    if rank == 0:
         timing = sort_stats(filter_stats(stats, type='timing_run'), sortby='time')
 
-        print('Time to solution: %6.4f sec.' % timing[0][1])
+        print(f'---> Time to solution: {timing[0][1]:.4f} sec.')
         print()
 
     return stats