def engine_iterate(self):
"""
Compute one iteration.
"""
error_dct={}
#fourier update
for name,di_view in self.di.V.iteritems():
ma_view = di_view.pods.values()[0].ma_view # a bit ugly
error_dct[name] = basic_fourier_update(di_view,ma_view,pbound=self.pbound,alpha=self.p.alpha)
# make a sorted error array for MPI reduction
error = np.array([error_dct[k] for k in np.sort(error_dct.keys())])
#print error.shape
error[error<0]=0.
parallel.allreduce(error)
# store error. maybe better in runtime?
self.error = error
#self.pty.runtime.error.append(error)
# probe update
self.probe_update(self.pr_nrm,self.pr_buf)
# object update
self.object_update(self.ob_nrm,self.ob_buf)
return error
def engine_iterate(self):
"""
Compute one iteration.
"""
error_dct = {}
# fourier update
for name, di_view in self.di.V.iteritems():
ma_view = di_view.pods.values()[0].ma_view # a bit ugly
error_dct[name] = basic_fourier_update(di_view, ma_view, pbound=self.pbound, alpha=self.p.alpha)
# make a sorted error array for MPI reduction
error = np.array([error_dct[k] for k in np.sort(error_dct.keys())])
# print error.shape
error[error < 0] = 0.0
parallel.allreduce(error)
# store error. maybe better in runtime?
self.error = error
# self.pty.runtime.error.append(error)
# probe update
self.probe_update(self.pr_nrm, self.pr_buf)
# object update
self.object_update(self.ob_nrm, self.ob_buf)
return error
def engine_iterate(self):
"""
Compute one iteration.
"""
error_dct={}
t = time.time()
# Fourier update
for name,di_view in self.di.V.iteritems():
ma_view = di_view.pod.ma_view
error_dct[name] = basic_fourier_update(di_view, ma_view, pbound=self.pbound)
logger.info('Time spent in Fourier update: %.2f' % (time.time()-t))
## make a sorted error array for MPI reduction
## error is sorted after the di_view IDs. This is needed for local error analysis later.
error = np.array([error_dct[k] for k in np.sort(error_dct.keys())])
error[error<0]=0.
parallel.allreduce(error)
# store error. maybe better in runtime?
self.error = error
self.overlap_update()
return error
