diff --git a/examples/multiresolution/scalar_advection.py b/examples/multiresolution/scalar_advection.py
index 54aa1ab554d326a4addb59bb4a3d64e5b0132b51..bf87e882ccc267e996bcd2f000ef4fe7af849d7a 100644
--- a/examples/multiresolution/scalar_advection.py
+++ b/examples/multiresolution/scalar_advection.py
@@ -36,7 +36,7 @@ def compute(args):
# Define domain
dim = args.ndim
npts = args.npts
- snpts = tuple(2*x for x in args.npts)
+ snpts = tuple(3*x for x in args.npts)
lboundaries = (BoxBoundaryCondition.PERIODIC,)*dim
rboundaries = (BoxBoundaryCondition.PERIODIC,)*dim
box = Box(origin=args.box_origin, length=args.box_length, dim=dim,
diff --git a/hysop/backend/device/opencl/operator/spatial_filtering.py b/hysop/backend/device/opencl/operator/spatial_filtering.py
index 615f993695274c11df1e0e0ca8374f66d7d989ab..7266b3a4b6f76c8cd3cf2cc7af9614e2d3d9dc06 100644
--- a/hysop/backend/device/opencl/operator/spatial_filtering.py
+++ b/hysop/backend/device/opencl/operator/spatial_filtering.py
@@ -47,22 +47,23 @@ class OpenClSpectralLowpassFilter(SpectralLowpassFilterBase, OpenClOperator):
# Here we get the coefficient
scaling = 1.0 / self.Bt.output_buffer[(0,)*self.FOUT.ndim].get()
- # Now we can finally build the filter scaling kernel and append
- # it to the kernel list
- fout, = kernel_generator.arrays_to_symbols(self.FOUT)
+ # Now we can finally build the filter scaling kernel
+ fout, = kernel_generator.arrays_to_symbols(self.Bt.output_buffer)
expr = Assignment(fout, scaling*fout)
scale, _ = kernel_generator.elementwise_kernel('scale', expr)
- kl += scale
+ self.scale = functools.partial(scale, queue=self.cl_env.default_queue)
# we store the filtering kernel list for the setup step
- self.kl = kl
+ self.filter = functools.partial(kl, queue=self.cl_env.default_queue)
+
+ # finally build ghost exchanger
+ exchange_ghosts = self.dFout.exchange_ghosts(build_launcher=True)
+ if (exchange_ghosts is not None):
+ exchange_ghosts = functools.partial(exchange_ghosts, queue=self.cl_env.default_queue)
+ self.exchange_ghosts = exchange_ghosts
return scaling
- def setup(self, work):
- super(OpenClSpectralLowpassFilter, self).setup(work=work)
- self.filter = functools.partial(self.kl, queue=self.cl_env.default_queue)
- self.exchange_ghosts = self.dFout.exchange_ghosts(build_launcher=True)
@op_apply
def apply(self, **kwds):
@@ -71,5 +72,6 @@ class OpenClSpectralLowpassFilter(SpectralLowpassFilterBase, OpenClOperator):
evt = self.Ft()
evt = self.filter()
evt = self.Bt()
+ evt = self.scale()
if (self.exchange_ghosts is not None):
evt = self.exchange_ghosts()
diff --git a/hysop/backend/host/python/operator/spatial_filtering.py b/hysop/backend/host/python/operator/spatial_filtering.py
index b02993d36e7682e0799af9557f4320c7a53c5dbc..18b449e403df5fad1ea694f8d737291070e2c894 100644
--- a/hysop/backend/host/python/operator/spatial_filtering.py
+++ b/hysop/backend/host/python/operator/spatial_filtering.py
@@ -61,5 +61,5 @@ class PythonSpectralLowpassFilter(SpectralLowpassFilterBase, HostOperator):
for i, (src_slc, dst_slc) in enumerate(zip(*self.fslices)):
self.FOUT[dst_slc] = self.FIN[src_slc]
self.Bt()
- scaling = 1.0 / self.Bt.output_buffer[(0,)*self.FOUT.ndim].get()
+ scaling = 1.0 / self.Bt.output_buffer[(0,)*self.FOUT.ndim]
return scaling
diff --git a/hysop/core/graph/computational_graph.py b/hysop/core/graph/computational_graph.py
index fe26837e0022157535e6d55c904ebbc57a50e9df..27ae81716ead3604f7b672b1dd36061da385fc22 100644
--- a/hysop/core/graph/computational_graph.py
+++ b/hysop/core/graph/computational_graph.py
@@ -24,7 +24,7 @@ class ComputationalGraph(ComputationalGraphNode):
__metaclass__ = ABCMeta
- __FORCE_REPORTS__ = True
+ __FORCE_REPORTS__ = False
@debug
def __init__(self, candidate_input_tensors=None,
diff --git a/hysop/core/graph/graph_builder.py b/hysop/core/graph/graph_builder.py
index eca3ae4ffa4acf19d52e74225e3248f300d19d18..d83c1f70860159a29c621a8314c4f2e00d3316e8 100644
--- a/hysop/core/graph/graph_builder.py
+++ b/hysop/core/graph/graph_builder.py
@@ -35,7 +35,6 @@ def gprint2(*args, **kwds):
kwds['level'] = 2
gprint(*args, **kwds)
-
def _op_info(op,
istates=None, ostates=None,
jmp=False):
diff --git a/hysop/fields/field_requirements.py b/hysop/fields/field_requirements.py
index 5cf0bf85449516df7a7606ba858a65668c75999b..2ace41f2f1cb165e41ef85d35e2ef97773458be1 100644
--- a/hysop/fields/field_requirements.py
+++ b/hysop/fields/field_requirements.py
@@ -15,7 +15,7 @@ from hysop.fields.discrete_field import DiscreteScalarField
# 0: no debug logs
# 1: topo creation summary for each field
# 2: topo creation details for all discrete field requirements
-TOPO_CREATION_DEBUG_LEVEL=1
+TOPO_CREATION_DEBUG_LEVEL=0
def gprint(*args, **kwds):
level = kwds.pop('level', 2)
diff --git a/hysop/operator/base/spatial_filtering.py b/hysop/operator/base/spatial_filtering.py
index 0814f52158afd404f252ae764b1c8822297bce53..ca812e4a68c6ff6f20ed4afd879b66db27606e82 100644
--- a/hysop/operator/base/spatial_filtering.py
+++ b/hysop/operator/base/spatial_filtering.py
@@ -113,7 +113,9 @@ class SpectralLowpassFilterBase(LowpassFilterBase, SpectralOperatorBase):
def _generate_filter_slices(self):
src_slices = [[]]
dst_slices = [[]]
- for (N,n,tr) in zip(self.FIN.shape, self.FOUT.shape, self.Ft.transforms[::-1]):
+
+ transforms = tuple(self.Ft.transforms[i] for i in self.Ft.output_axes)
+ for (N,n,tr) in zip(self.FIN.shape, self.FOUT.shape, transforms):
assert len(src_slices) == len(dst_slices)
assert n <= N
if SpectralTransformUtils.is_C2C(tr):
diff --git a/hysop/operator/spatial_filtering.py b/hysop/operator/spatial_filtering.py
index f6c87b542c99a9417e9400992eae58c52c935d31..c6470e07dda0edb46b1385eba2293b8651d4aead 100644
--- a/hysop/operator/spatial_filtering.py
+++ b/hysop/operator/spatial_filtering.py
@@ -89,7 +89,7 @@ class LowpassFilterFrontend(MultiComputationalGraphNodeFrontend):
check_instance(input_topo, CartesianTopologyDescriptors)
check_instance(output_topo, CartesianTopologyDescriptors)
check_instance(base_kwds, dict, keys=str, allow_none=True)
- assert (input_topo != output_topo), "Same topology for input and output."
+ #assert (input_topo != output_topo), "Same topology for input and output."
super(LowpassFilterFrontend, self).__init__(input_field=input_field, input_topo=input_topo,
output_field=output_field, output_topo=output_topo,
@@ -174,8 +174,9 @@ class LowpassFilter(ComputationalGraphNodeGenerator):
kwds = self._kwds.copy()
# if source topology is destination topology there is nothing to be done
- if (ttopo == stopo):
- continue
+ # TODO
+ #if (ttopo == stopo):
+ #continue
# else we build a lowpass filter operator
node = LowpassFilterFrontend(input_variable=(ifield,stopo),