only do trS2_Q_R stats if the data is there

bfps/NavierStokes.py

@@ -554,6 +554,7 @@ class NavierStokes(bfps.fluid_base.fluid_particle_base):
                         data_file['statistics/spectra/vorticity_vorticity'][ii0:ii1+1, :, 2, 2])/2
                 data_file['postprocess/vel_max(t)'] = data_file['statistics/moments/velocity']  [ii0:ii1+1, 9, 3]
                 data_file['postprocess/renergy(t)'] = data_file['statistics/moments/velocity'][ii0:ii1+1, 2, 3]/2
+                if 'trS2_Q_R' in data_file['statistics/moments'].keys():
                     data_file['postprocess/mean_trS2(t)'] = data_file['statistics/moments/trS2_Q_R'][:, 1, 0]
             for k in ['t',
                       'energy(t, k)',
@@ -561,6 +562,7 @@ class NavierStokes(bfps.fluid_base.fluid_particle_base):
                       'vel_max(t)',
                       'renergy(t)',
                       'mean_trS2(t)']:
+                if key in data_file['postprocess'].keys():
                     self.statistics[k] = data_file['postprocess/' + k].value
             self.compute_time_averages()
         return None
@@ -568,6 +570,7 @@ class NavierStokes(bfps.fluid_base.fluid_particle_base):
         for key in ['energy', 'enstrophy']:
             self.statistics[key + '(t)'] = np.sum(self.statistics[key + '(t, k)'], axis = 1)
         for key in ['energy', 'enstrophy', 'vel_max', 'mean_trS2']:
+            if key + '(t)' in self.statistics.keys():
                 self.statistics[key] = np.average(self.statistics[key + '(t)'], axis = 0)
         for suffix in ['', '(t)']:
             self.statistics['diss'    + suffix] = (self.parameters['nu'] *