From 7ff04dc9bd7b96806ba8791d261758c5d6fa54ae Mon Sep 17 00:00:00 2001
From: Jean-Baptiste Keck <Jean-Baptiste.Keck@imag.fr>
Date: Wed, 22 May 2019 18:44:35 +0200
Subject: [PATCH] fixed everything for ci
---
examples/analytic/analytic.py | 20 ++--
examples/scalar_advection/levelset.py | 21 ++--
examples/taylor_green/taylor_green.py | 2 +-
.../device/opencl/operator/analytic.py | 6 +-
.../backend/host/python/operator/analytic.py | 15 +--
.../operator/directional/advection_dir.py | 7 +-
hysop/core/graph/computational_node.py | 6 ++
hysop/fields/cartesian_discrete_field.py | 17 ++--
hysop/fields/tests/test_cartesian.py | 22 ++---
hysop/methods.py | 2 +-
hysop/numerics/tests/test_fft.py | 5 +-
hysop/operator/analytic.py | 99 ++++++++++++++++++-
hysop/operator/base/spatial_filtering.py | 13 ++-
hysop/operator/spatial_filtering.py | 17 ++--
hysop/operator/tests/test_absorption.py | 13 +--
hysop/operator/tests/test_analytic.py | 26 +++--
hysop/operator/tests/test_diffusion.py | 20 ++--
.../tests/test_directional_advection.py | 2 +-
.../tests/test_directional_diffusion.py | 19 ++--
.../tests/test_directional_stretching.py | 12 +--
hysop/operator/tests/test_fd_derivative.py | 13 +--
hysop/operator/tests/test_poisson.py | 22 ++---
hysop/operator/tests/test_poisson_curl.py | 23 ++---
.../operator/tests/test_restriction_filter.py | 19 ++--
.../tests/test_solenoidal_projection.py | 28 +++---
hysop/operator/tests/test_spectral_curl.py | 26 ++---
.../tests/test_spectral_derivative.py | 22 ++---
hysop/operator/tests/test_transpose.py | 21 ++--
hysop/testsenv.py | 18 ++--
hysop/topology/cartesian_descriptor.py | 18 +++-
30 files changed, 315 insertions(+), 239 deletions(-)
diff --git a/examples/analytic/analytic.py b/examples/analytic/analytic.py
index 09f01a5cd..569583479 100755
--- a/examples/analytic/analytic.py
+++ b/examples/analytic/analytic.py
@@ -6,10 +6,10 @@ def compute(args):
'''
HySoP Analytic Example: Initialize a field with a space and time dependent analytic formula.
'''
- from hysop import Field, Box, MPIParams, \
+ from hysop import Field, Box, IOParams, MPIParams, \
Simulation, Problem, ScalarParameter
from hysop.constants import Implementation
- from hysop.operators import AnalyticField
+ from hysop.operators import AnalyticField, HDF_Writer
# Define domain
npts = args.npts
@@ -57,10 +57,10 @@ def compute(args):
# tuple 'data'. Coordinates will be passed as a tuple as a second
# argument. Finally extra arguments (here t) are passed last.
# Note that t is a ScalarParameter, so we evaluate it to get its value.
- def compute_scalar(data, coords, t):
- data[0][...] = (1.0/(1.0+0.1*t()))
- for x in coords[0]:
- data[0][...] *= np.cos(x-t())
+ def compute_scalar(data, coords, component, t):
+ data[...] = (1.0/(1.0+0.1*t()))
+ for x in coords:
+ data[...] *= np.cos(x-t())
elif (impl is Implementation.OPENCL):
# With the opencl codegen implementation we use a symbolic expression
# generated using sympy. OpenCL code will be automatically generated,
@@ -83,11 +83,15 @@ def compute(args):
**op_kwds)
# Write output field at given frequency
- analytic.dump_outputs(fields=scalar, frequency=args.dump_freq, filename='F', **op_kwds)
+ io_params = IOParams(filename='analytic', frequency=args.dump_freq)
+ df = HDF_Writer(name='S',
+ io_params=io_params,
+ variables={scalar: npts},
+ **op_kwds)
# Create the problem we want to solve and insert our operator
problem = Problem()
- problem.insert(analytic)
+ problem.insert(analytic, df)
problem.build(args)
# If a visu_rank was provided, and show_graph was set,
diff --git a/examples/scalar_advection/levelset.py b/examples/scalar_advection/levelset.py
index 287974551..1681b1b13 100644
--- a/examples/scalar_advection/levelset.py
+++ b/examples/scalar_advection/levelset.py
@@ -91,17 +91,16 @@ def compute(args):
# Setup implementation specific variables
if (impl is Implementation.PYTHON) or (impl is Implementation.FORTRAN):
sin, cos = np.sin, np.cos
- def compute_velocity(data, coords, t):
- (x,y,z) = coords[0]
- data[0][...] = 2.*sin(pi*x)**2*sin(2*pi*y)*sin(2.*pi*z)*cos(t()*pi/3.)
- (x,y,z) = coords[1]
- data[1][...] = -sin(2.*pi*x)*sin(pi*y)**2*sin(2.*pi*z)*cos(t()*pi/3.)
- (x,y,z) = coords[2]
- data[2][...] = -sin(2.*pi*x)*sin(2.*pi*y)*sin(pi*z)**2*cos(t()*pi/3.)
- def compute_norm(data, coords):
- data[0][...] = np.sqrt(data[0]**2 + data[1]**2 + data[2]**2)
- def compute_volume(data, coords, S):
- data[0][...] = (S[0] <= 0.5)
+ def compute_velocity(data, coords, component, t):
+ (x,y,z) = coords
+ fn = [ +2.*sin(pi*x)**2*sin(2*pi*y)*sin(2.*pi*z)*cos(t()*pi/3.),
+ -sin(2.*pi*x)*sin(pi*y)**2*sin(2.*pi*z)*cos(t()*pi/3.),
+ -sin(2.*pi*x)*sin(2.*pi*y)*sin(pi*z)**2*cos(t()*pi/3.)]
+ data[...] = fn[component]
+ def compute_norm(data, coords, component):
+ data[...] = np.sqrt(data[0]**2 + data[1]**2 + data[2]**2)
+ def compute_volume(data, coords, component, S):
+ data[...] = (S[0] <= 0.5)
elif (impl is Implementation.OPENCL):
from hysop.symbolic.relational import LogicalLE
sin, cos = sm.sin, sm.cos
diff --git a/examples/taylor_green/taylor_green.py b/examples/taylor_green/taylor_green.py
index b470807c0..c00e88b98 100644
--- a/examples/taylor_green/taylor_green.py
+++ b/examples/taylor_green/taylor_green.py
@@ -10,7 +10,7 @@ cos = np.cos
sin = np.sin
## Function to compute initial vorticity
-def init_vorticity(data, coords, component=None):
+def init_vorticity(data, coords, component):
# Ux = sin(x) * cos(y) * cos(z)
# Uy = - cos(x) * sin(y) * cos(z)
# Uz = 0
diff --git a/hysop/backend/device/opencl/operator/analytic.py b/hysop/backend/device/opencl/operator/analytic.py
index d490f3654..916ea10ae 100644
--- a/hysop/backend/device/opencl/operator/analytic.py
+++ b/hysop/backend/device/opencl/operator/analytic.py
@@ -2,7 +2,7 @@
from hysop.deps import sm
from hysop.tools.types import check_instance, first_not_None, to_tuple
from hysop.tools.decorators import debug
-from hysop.fields.continuous_field import Field
+from hysop.fields.continuous_field import ScalarField, Field
from hysop.topology.cartesian_descriptor import CartesianTopologyDescriptors
from hysop.backend.device.opencl.operator.custom_symbolic import OpenClCustomSymbolicOperator
from hysop.symbolic.relational import Assignment
@@ -23,7 +23,7 @@ class OpenClAnalyticField(OpenClCustomSymbolicOperator):
Parameters
----------
- field: hysop.field.continuous_field.Field
+ field: hysop.field.continuous_field.ScalarField
Continuous field to be modified.
formula : sm.Basic or array-like of sm.Basic
field.nb_components symbolic expressions as a tuple.
@@ -33,7 +33,7 @@ class OpenClAnalyticField(OpenClCustomSymbolicOperator):
Base class arguments.
"""
formula = to_tuple(formula)
- check_instance(field, Field)
+ check_instance(field, ScalarField)
check_instance(formula, tuple, values=(type(None),sm.Basic), size=field.nb_components)
check_instance(variables, dict, keys=Field, values=CartesianTopologyDescriptors)
diff --git a/hysop/backend/host/python/operator/analytic.py b/hysop/backend/host/python/operator/analytic.py
index e2969cfe0..7d9dd1a93 100644
--- a/hysop/backend/host/python/operator/analytic.py
+++ b/hysop/backend/host/python/operator/analytic.py
@@ -3,7 +3,7 @@ from hysop.tools.types import check_instance, first_not_None
from hysop.tools.decorators import debug
from hysop.backend.host.host_operator import HostOperator
from hysop.core.graph.graph import op_apply
-from hysop.fields.continuous_field import Field
+from hysop.fields.continuous_field import Field, ScalarField
from hysop.parameters.parameter import Parameter
from hysop.topology.cartesian_descriptor import CartesianTopologyDescriptors
@@ -24,7 +24,7 @@ class PythonAnalyticField(HostOperator):
Parameters
----------
- field: hysop.field.continuous_field.Field
+ field: hysop.field.continuous_field.ScalarField
Continuous field to be modified.
formula : callable
The formula to be applied onto the field.
@@ -44,20 +44,20 @@ class PythonAnalyticField(HostOperator):
"""
extra_input_kwds = first_not_None(extra_input_kwds, {})
- check_instance(field, Field)
+ check_instance(field, ScalarField)
assert callable(formula), type(formula)
check_instance(variables, dict, keys=Field, values=CartesianTopologyDescriptors)
check_instance(extra_input_kwds, dict, keys=str)
input_fields = {}
- output_fields = { field: variables[field] }
+ output_fields = { field: self.get_topo_descriptor(variables, field) }
input_params = {}
extra_kwds = {}
map_fields = {}
for (k,v) in extra_input_kwds.iteritems():
if isinstance(v, Field):
- input_fields[v] = variables[v]
+ input_fields[v] = self.get_topo_descriptor(variables, v)
map_fields[v] = k
elif isinstance(v, Parameter):
input_params[k] = v
@@ -68,6 +68,7 @@ class PythonAnalyticField(HostOperator):
super(PythonAnalyticField, self).__init__(input_fields=input_fields,
output_fields=output_fields,
input_params=input_params, **kwds)
+
self.field = field
self.formula = formula
self.extra_kwds = extra_kwds
@@ -83,8 +84,8 @@ class PythonAnalyticField(HostOperator):
map_fields = self.map_fields
assert 'data' not in extra_kwds
assert 'coords' not in extra_kwds
- extra_kwds['data'] = dfield.compute_data
- extra_kwds['coords'] = dfield.get_attributes('compute_mesh_coords')
+ extra_kwds['data'] = dfield.compute_data[0]
+ extra_kwds['coords'] = dfield.compute_mesh_coords
for (field, dfield) in self.input_discrete_fields.iteritems():
assert field.name not in extra_kwds, field.name
extra_kwds[map_fields[field]] = dfield.compute_data
diff --git a/hysop/backend/host/python/operator/directional/advection_dir.py b/hysop/backend/host/python/operator/directional/advection_dir.py
index c5f969119..9501cf429 100644
--- a/hysop/backend/host/python/operator/directional/advection_dir.py
+++ b/hysop/backend/host/python/operator/directional/advection_dir.py
@@ -9,7 +9,7 @@ from hysop.constants import BoundaryCondition
from hysop.backend.host.host_operator import ComputeGranularity
from hysop.backend.host.host_directional_operator import HostDirectionalOperator
from hysop.operator.base.advection_dir import DirectionalAdvectionBase
-from hysop.methods import Interpolation
+from hysop.methods import Interpolation, PolynomialInterpolation
from hysop.numerics.odesolvers.runge_kutta import ExplicitRungeKutta, Euler, RK2, RK3, RK4
DEBUG = False
@@ -187,7 +187,6 @@ class PythonDirectionalAdvection(DirectionalAdvectionBase, HostDirectionalOperat
lidx: int32 empty input buffer, destroyed
ridx: int32 empty input buffer, destroyed
"""
- assert self.interp is Interpolation.LINEAR # legacy linear interpolator
N = dX.shape[-1]
Iy = I[:-1]
@@ -431,7 +430,9 @@ class PythonDirectionalAdvection(DirectionalAdvectionBase, HostDirectionalOperat
super(PythonDirectionalAdvection, self).handle_method(method)
cr = method.pop(ComputeGranularity)
assert 0 <= cr <= self.velocity.dim-1
- assert self.interp == Interpolation.LINEAR
+ msg='Interpolation {}.{} is not supported for operator {}.'.format(
+ self.interp.__class__.__name__, self.interp, self.__class__.__name__)
+ assert self.interp in (Interpolation.LINEAR, PolynomialInterpolation.LINEAR), msg
self.compute_granularity = cr
@classmethod
diff --git a/hysop/core/graph/computational_node.py b/hysop/core/graph/computational_node.py
index e7b0c86b5..c20dba7c9 100644
--- a/hysop/core/graph/computational_node.py
+++ b/hysop/core/graph/computational_node.py
@@ -18,6 +18,7 @@ from hysop.core.graph.continuous import OperatorBase
from hysop.topology.topology import Topology, TopologyView
from hysop.tools.decorators import debug
from hysop.tools.warning import HysopWarning
+from hysop.topology.cartesian_descriptor import get_topo_descriptor_discretization
def base_initialized(f):
@@ -686,6 +687,11 @@ class ComputationalGraphNode(OperatorBase):
msg=msg.format(field.short_description())
raise KeyError(msg)
+ @classmethod
+ def get_topo_discretization(cls, variables, field):
+ topo = cls.get_topo_descriptor(variables=variables, field=field)
+ return get_topo_descriptor_discretization(topo)
+
@classmethod
def supports_multiple_topologies(cls):
"""
diff --git a/hysop/fields/cartesian_discrete_field.py b/hysop/fields/cartesian_discrete_field.py
index 7330ae255..5749e83f8 100644
--- a/hysop/fields/cartesian_discrete_field.py
+++ b/hysop/fields/cartesian_discrete_field.py
@@ -28,7 +28,7 @@ from hysop.core.mpi.topo_tools import TopoTools
class CartesianDiscreteScalarFieldViewContainerI(object):
def initialize(self, formula, vectorize=False,
- without_ghosts=False, exchange_ghosts=True,
+ without_ghosts=True, exchange_ghosts=True,
exchange_kwds=None, only_finite=True,
reorder=None, quiet=False, components=None, **kwds):
"""
@@ -43,22 +43,23 @@ class CartesianDiscreteScalarFieldViewContainerI(object):
vectorize : bool, optional
True if formula must be vectorized
(i.e. is of type 'user_func_2', see :ref:`fields` for details)
- only_finite: bool, optional
- Check that initialized values are not +inf, -inf or NaN.
- Defaults to True.
+ without_ghosts: boolean, optional, defaults to False
+ Do not initialize ghosts using formula.
+ In this case, ghosts may be initialized by ghost exchange (see next parameter).
exchange_ghosts: bool, optional, defaults to True
Should we exchange ghosts after initialization ?
- without_ghosts: boolean, optional, defaults to False
- Do not initialize ghosts (only for formula init).
exchange_kwds: dict, optional,
Extra exchange keyword arguments passed to ghost exchange.
Only used if exchange_ghosts is set to True.
+ only_finite: bool, optional
+ Check that initialized values are not +inf, -inf or NaN.
+ Defaults to True.
reorder: str or tuple of str, optional
Reorder all kwd according to current topology state.
ie. kwd should be contained in kwds and kwds[kwd] should
be of length self.domain.dim.
kwds : dict
- Extra keyword arguments passed to formula, optional, depends on formula.
+ Extra keyword arguments passed to formula, optional, depends on passed formula.
"""
if (not self.has_unique_backend()):
msg='Cannot initialize a tensor field defined on multiple backends at a time.'
@@ -185,7 +186,7 @@ class CartesianDiscreteScalarFieldViewContainerI(object):
if (ddst is None):
continue
src_slices = all_src_slices[i]
- dst_slices = kwds.pop('dst_slices', dfields[i].compute_slices)
+ dst_slices = kwds.pop('dst_slices', Ellipsis)
check_instance(dsrc, (np.ndarray, HostArray))
check_instance(ddst, (np.ndarray, HostArray))
src_shape = dsrc[src_slices].shape
diff --git a/hysop/fields/tests/test_cartesian.py b/hysop/fields/tests/test_cartesian.py
index 6bac6d6af..7b178728b 100644
--- a/hysop/fields/tests/test_cartesian.py
+++ b/hysop/fields/tests/test_cartesian.py
@@ -12,27 +12,23 @@ from hysop.topology.cartesian_topology import CartesianTopology, CartesianTopolo
from hysop.testsenv import iter_clenv, test_context, domain_boundary_iterator
from hysop.tools.numerics import is_fp, is_integer
-def __random_init(data, coords):
- shape = data[0].shape
- dtype = data[0].dtype
+def __random_init(data, coords, component):
+ shape = data.shape
+ dtype = data.dtype
if is_integer(dtype):
- for d in data:
- d[...] = npw.random.random_integers(low=0, high=255, size=shape)
+ data[...] = npw.random.random_integers(low=0, high=255, size=shape)
elif is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape)
+ data[...] = npw.random.random(size=shape)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
-def __zero_init(data, coords):
- for d in data:
- d[...] = 0
+def __zero_init(data, coords, component):
+ data[...] = 0
def __cst_init(cst):
- def __init(data,coords):
- for d in data:
- d[...] = cst
+ def __init(data,coords,component):
+ data[...] = cst
return __init
def test_serial_initialization_1d():
diff --git a/hysop/methods.py b/hysop/methods.py
index c122b82af..741c3f020 100644
--- a/hysop/methods.py
+++ b/hysop/methods.py
@@ -33,7 +33,7 @@ from hysop.constants import Backend, Precision, BoundaryCondition, \
from hysop.operator.spatial_filtering import FilteringMethod
from hysop.numerics.interpolation.interpolation import Interpolation, MultiScaleInterpolation
-from hysop.numerics.interpolation.polynomial import PolynomialInterpolator
+from hysop.numerics.interpolation.polynomial import PolynomialInterpolator, PolynomialInterpolation
from hysop.numerics.odesolvers.runge_kutta import TimeIntegrator
from hysop.numerics.remesh.remesh import Remesh
from hysop.numerics.splitting.strang import StrangOrder
diff --git a/hysop/numerics/tests/test_fft.py b/hysop/numerics/tests/test_fft.py
index c08d154d5..763f455bf 100644
--- a/hysop/numerics/tests/test_fft.py
+++ b/hysop/numerics/tests/test_fft.py
@@ -19,9 +19,10 @@ from hysop.numerics.fft.fft import mk_shape, HysopFFTDataLayoutError
from hysop.numerics.fft.numpy_fft import NumpyFFT
from hysop.numerics.fft.scipy_fft import ScipyFFT
from hysop.numerics.fft.fftw_fft import FftwFFT
-from hysop.numerics.fft._mkl_fft import MklFFT
from hysop.numerics.fft.gpyfft_fft import GpyFFT
+# For now Intel has a bug in their MKL FFTW-like interface so we do not test it
+# from hysop.numerics.fft._mkl_fft import MklFFT
class TestFFT(object):
@@ -29,9 +30,9 @@ class TestFFT(object):
Implementation.PYTHON: {
'numpy': NumpyFFT(warn_on_allocation=False),
'scipy': ScipyFFT(warn_on_allocation=False),
- 'mkl': MklFFT(warn_on_allocation=False),
'fftw': FftwFFT(warn_on_allocation=False,
warn_on_misalignment=False)
+ #'mkl': MklFFT(warn_on_allocation=False),
},
Implementation.OPENCL: {}
}
diff --git a/hysop/operator/analytic.py b/hysop/operator/analytic.py
index d1f4a38ce..cff14829f 100644
--- a/hysop/operator/analytic.py
+++ b/hysop/operator/analytic.py
@@ -2,12 +2,105 @@
"""
from hysop.constants import Backend, Implementation
from hysop.fields.continuous_field import Field
-from hysop.tools.types import check_instance
+from hysop.tools.types import check_instance, first_not_None, to_tuple
from hysop.tools.decorators import debug
from hysop.topology.cartesian_descriptor import CartesianTopologyDescriptors
from hysop.core.graph.computational_node_frontend import ComputationalGraphNodeFrontend
+from hysop.core.graph.node_generator import ComputationalGraphNodeGenerator
-class AnalyticField(ComputationalGraphNodeFrontend):
+class AnalyticField(ComputationalGraphNodeGenerator):
+ """
+ Applies an analytic formula, given by user, on all contained scalar fields.
+ Formula may be given in different formats depending on the
+ chosen implementation backend.
+ """
+
+ @debug
+ def __init__(self, field, formula, variables, extra_input_kwds=None,
+ implementation=None, base_kwds=None, **kwds):
+ """
+ AnalyticField operator frontend.
+
+ Apply a user-defined formula onto a field, possibly
+ dependent on space variables and external fields/parameters.
+
+ Parameters
+ ----------
+ field: hysop.field.continuous_field.Field
+ Continuous field to be modified.
+ formula : python function or sympy expression or tupe
+ The formula to be applied onto the scalar fields.
+ If the formula is a tuple of the length of the number of scalar fields,
+ fomula[component] is used instead.
+ variables: dict
+ Dictionary of fields as keys and topology descriptors as values.
+ implementation: Implementation, optional, defaults to None
+ target implementation, should be contained in available_implementations().
+ If None, implementation will be set to default_implementation().
+ extra_input_kwds: dict, optional
+ Extra inputs that will be forwarded to the formula.
+ Fields and Parameters are handled correctly as input requirements.
+ Only used for Implementation.PYTHON, discarded for other implementations.
+ base_kwds: dict, optional
+ Base class keyword arguments.
+ kwds: dict, optional
+ Extra parameters passed towards operator implementation.
+ """
+ check_instance(field, Field)
+ check_instance(variables, dict, keys=Field, values=CartesianTopologyDescriptors)
+ extra_input_kwds = first_not_None(extra_input_kwds, {})
+ base_kwds = first_not_None(base_kwds, {})
+
+ assert 'extra_input_kwds' not in kwds
+ assert 'component' not in kwds
+ assert 'coords' not in kwds
+
+ if (implementation is Implementation.PYTHON) and (extra_input_kwds is not None):
+ candidate_input_tensors = filter(lambda f: isinstance(f, Field), extra_input_kwds.values())
+ else:
+ extra_input_kwds = {}
+ candidate_input_tensors = ()
+ candidate_output_tensors = (field,)
+
+ formula = to_tuple(formula)
+ if len(formula) == 1:
+ formula = formula*field.nb_components
+ check_instance(formula, tuple, size=field.nb_components)
+
+ super(AnalyticField, self).__init__(
+ candidate_input_tensors=candidate_input_tensors,
+ candidate_output_tensors=candidate_output_tensors,
+ **base_kwds)
+
+ self._fields = field.fields
+ self._formula = formula
+ self._variables = variables
+ self._extra_input_kwds = extra_input_kwds
+ self._implementation = implementation
+ self._kwds = kwds
+
+ @debug
+ def _generate(self):
+ nodes = []
+ impl = self._implementation
+ variables = self._variables
+ assert len(self._formula)==len(self._fields)
+ for component, (formula, field) in enumerate(zip(self._formula, self._fields)):
+ kwds = self._kwds.copy()
+ extra_input_kwds = self._extra_input_kwds.copy()
+ extra_input_kwds['component'] = component
+ node = AnalyticScalarField(
+ field=field,
+ formula=formula,
+ variables=variables,
+ implementation=impl,
+ extra_input_kwds=extra_input_kwds,
+ **kwds)
+ nodes.append(node)
+ return nodes
+
+
+class AnalyticScalarField(ComputationalGraphNodeFrontend):
"""
Applies an analytic formula, given by user, on its field.
Formula may be given in different formats depending on the
@@ -63,6 +156,6 @@ class AnalyticField(ComputationalGraphNodeFrontend):
if (implementation is Implementation.PYTHON):
kwds['extra_input_kwds'] = extra_input_kwds
- super(AnalyticField, self).__init__(field=field, formula=formula,
+ super(AnalyticScalarField, self).__init__(field=field, formula=formula,
variables=variables, implementation=implementation,
base_kwds=base_kwds, **kwds)
diff --git a/hysop/operator/base/spatial_filtering.py b/hysop/operator/base/spatial_filtering.py
index 30db42947..cb23b75f5 100644
--- a/hysop/operator/base/spatial_filtering.py
+++ b/hysop/operator/base/spatial_filtering.py
@@ -332,7 +332,6 @@ class RemeshRestrictionFilterBase(RestrictionFilterBase):
assert abs(weights.sum() - 1.0) < 1e-8, weights.sum()
assert abs(npw.sum(nz_weights.values()) - 1.0) < 1e-8, npw.sum(nz_weights.values())
- self.iratio = iratio
self.weights = weights
self.nz_weights = nz_weights
@@ -342,12 +341,12 @@ class RemeshRestrictionFilterBase(RestrictionFilterBase):
return
super(RemeshRestrictionFilterBase, self).discretize()
dFin, dFout = self.dFin, self.dFout
-
- iratio = dFin.compute_resolution / dFout.compute_resolution
- self.compute_weights(iratio)
+
+ grid_ratio = self.grid_ratio
+ self.compute_weights(grid_ratio)
remesh_ghosts = self.remesh_ghosts
- fine_grid_ghosts = iratio*remesh_ghosts - 1
+ fine_grid_ghosts = grid_ratio*remesh_ghosts - 1
fin = dFin.sdata[dFin.local_slices(ghosts=fine_grid_ghosts)]
fout = dFout.compute_buffers[0]
@@ -368,7 +367,7 @@ class SubgridRestrictionFilterBase(RestrictionFilterBase):
dFin, dFout = self.dFin, self.dFout
grid_ratio = self.grid_ratio
- view = tuple(slice(None,None,r) for r in iratio)
+ view = tuple(slice(None,None,r) for r in grid_ratio)
fin = dFin.compute_buffers[0][view]
fout = dFout.compute_buffers[0]
@@ -376,7 +375,7 @@ class SubgridRestrictionFilterBase(RestrictionFilterBase):
msg='Something went wrong during slicing: fin.shape={}, fout.shape={}'
msg=msg.format(fin.shape, fout.shape)
assert (fin.shape == fout.shape), msg
- assert npw.prod(iratio) == npw.prod(self.iratio), msg
+ assert npw.prod(grid_ratio) == npw.prod(self.iratio), msg
self.fin, self.fout = fin, fout
diff --git a/hysop/operator/spatial_filtering.py b/hysop/operator/spatial_filtering.py
index f485aec69..7facb047c 100644
--- a/hysop/operator/spatial_filtering.py
+++ b/hysop/operator/spatial_filtering.py
@@ -22,7 +22,7 @@ class SpatialFilterFrontend(MultiComputationalGraphNodeFrontend):
base_kwds=None,
**kwds):
"""
- Initialize a RestrictionFilter operator.
+ Initialize a SpatialFilter operator.
Parameters
----------
@@ -43,7 +43,7 @@ class SpatialFilterFrontend(MultiComputationalGraphNodeFrontend):
Notes
-----
- An implementation should at least support the RestrictionFilterBase interface.
+ An implementation should at least support the SpatialFilterBase interface.
"""
check_instance(input_variable, tuple, size=2)
check_instance(output_variable, tuple, size=2)
@@ -209,16 +209,15 @@ class SpatialFilter(ComputationalGraphNodeGenerator):
def _generate(self):
nodes = []
for (ifield, ofield) in zip(self._input_fields, self._output_fields):
- stopo = ComputationalGraphNode.get_topo_descriptor(self._input_variables, ifield)
- ttopo = ComputationalGraphNode.get_topo_descriptor(self._output_variables, ofield)
- fm = self._fm
- impl = self._impl
- kwds = self._kwds.copy()
-
- # TODO handle other topology descriptors
+ stopo = ComputationalGraphNode.get_topo_discretization(self._input_variables, ifield)
+ ttopo = ComputationalGraphNode.get_topo_discretization(self._output_variables, ofield)
check_instance(stopo, tuple, values=(int,long))
check_instance(ttopo, tuple, values=(int,long))
assert len(stopo)==len(ttopo)
+
+ fm = self._fm
+ impl = self._impl
+ kwds = self._kwds.copy()
# if source topology is destination topology there is nothing to be done
if (ttopo == stopo):
diff --git a/hysop/operator/tests/test_absorption.py b/hysop/operator/tests/test_absorption.py
index 8da2141d2..c3a8354de 100644
--- a/hysop/operator/tests/test_absorption.py
+++ b/hysop/operator/tests/test_absorption.py
@@ -47,20 +47,17 @@ class TestVorticityAbsorption(object):
pass
@staticmethod
- def __random_init(data, coords):
- dtype = data[0].dtype
+ def __random_init(data, coords, component):
+ dtype = data.dtype
if is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape).astype(dtype=dtype)
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
@staticmethod
- def __velo_init(data, coords):
- data[0][...] = 1.
- data[1][...] = 0.
- data[2][...] = 0.
+ def __velo_init(data, coords, component):
+ data[...] = [1,0,0][component]
def _test(self, dim, dtype,
size_min=None, size_max=None):
diff --git a/hysop/operator/tests/test_analytic.py b/hysop/operator/tests/test_analytic.py
index 47b66cd7e..83e397047 100644
--- a/hysop/operator/tests/test_analytic.py
+++ b/hysop/operator/tests/test_analytic.py
@@ -12,7 +12,7 @@ from hysop.tools.types import check_instance, first_not_None
from hysop.tools.io_utils import IO
from hysop.tools.numpywrappers import npw
from hysop.parameters.scalar_parameter import ScalarParameter
-from hysop.operator.analytic import AnalyticField, Implementation
+from hysop.operator.analytic import AnalyticField, AnalyticScalarField, Implementation
from hysop import Field, Box
@@ -87,20 +87,18 @@ class TestAnalyticField(object):
pass
@staticmethod
- def __random_init(data, coords):
- dtype = data[0].dtype
+ def __random_init(data, coords, component):
+ dtype = data.dtype
if is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape).astype(dtype=dtype)
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
- @classmethod
- def __analytic_init(cls, data, coords, fns, t):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- d[...] = npw.asarray(fn(*(coord+(t(),)))).astype(d.dtype)
+ @staticmethod
+ def __analytic_init(data, coords, fns, t, component):
+ fn = fns[component]
+ data[...] = npw.asarray(fn(*(coords+(t(),)))).astype(data.dtype)
def _test(self, dim, dtype,
size_min=None, size_max=None):
@@ -131,7 +129,7 @@ class TestAnalyticField(object):
print ' >Parameter t has been set to {}.'.format(self.t())
print ' >Testing all implementations:'
- implementations = AnalyticField.implementations()
+ implementations = AnalyticScalarField.implementations()
variables = { F:shape }
fns = self.analytic_functions[dim]['F']
@@ -177,7 +175,7 @@ class TestAnalyticField(object):
dF.initialize(self.__random_init)
op.apply()
- Fout = tuple( data.get().handle.copy() for data in dF.data )
+ Fout = tuple( data.get().handle.copy() for data in dF.data )
self._check_output(impl, op, Fref, Fout)
@classmethod
@@ -215,7 +213,7 @@ class TestAnalyticField(object):
print
print
- print 'Test output comparisson for {} failed for component {}:'.format(name, i)
+ print 'Test output comparisson for {} failed for component {}:'.format(iname, i)
print ' *has_nan: {}'.format(has_nan)
print ' *has_inf: {}'.format(has_inf)
print ' *dinf={} ({} eps)'.format(dinf, deps)
@@ -247,7 +245,7 @@ class TestAnalyticField(object):
print
print
- msg = 'Test failed for {} on component {} for implementation {}.'.format(name, i, impl)
+ msg = 'Test failed for {} on component {} for implementation {}.'.format(iname, i, impl)
raise RuntimeError(msg)
diff --git a/hysop/operator/tests/test_diffusion.py b/hysop/operator/tests/test_diffusion.py
index a0e95366a..d326ddbb3 100644
--- a/hysop/operator/tests/test_diffusion.py
+++ b/hysop/operator/tests/test_diffusion.py
@@ -60,26 +60,24 @@ class TestDiffusionOperator(object):
self._test_one(shape=shape, dim=dim, dtype=dtype,
is_inplace=is_inplace, domain=domain,
Fin=Fin, Fout=Fout, nu=nu)
-
+
@staticmethod
- def __random_init(data, coords, dtype):
+ def __random_init(data, coords, dtype, component):
+ shape = data.shape
if is_integer(dtype):
- for d in data:
- d[...] = npw.random.random_integers(low=0, high=255, size=shape)
+ data[...] = npw.random.random_integers(low=0, high=255, size=shape)
elif is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape)
+ data[...] = npw.random.random(size=data.shape)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
@staticmethod
- def __scalar_init(data, coords, dtype):
+ def __scalar_init(data, coords, dtype, component):
if is_fp(dtype):
- for i,(d,c) in enumerate(zip(data,coords)):
- d[...] = 1
- for xi in c:
- d[...] *= npw.cos(xi*(i+1))
+ data[...] = 1
+ for xi in coords:
+ data[...] *= npw.cos(xi*(component+1))
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
diff --git a/hysop/operator/tests/test_directional_advection.py b/hysop/operator/tests/test_directional_advection.py
index b424ab569..c1e4f89bb 100644
--- a/hysop/operator/tests/test_directional_advection.py
+++ b/hysop/operator/tests/test_directional_advection.py
@@ -236,7 +236,7 @@ class TestDirectionalAdvectionOperator(object):
for i in xrange(dsout.nb_components):
di = npw.abs(reference[i] - output[i])
max_di = npw.max(di)
- neps = 500
+ neps = 1000
max_tol = neps*npw.finfo(dsout.dtype).eps
if (max_di>max_tol):
print 'FATAL ERROR: Could not match other implementation results.'
diff --git a/hysop/operator/tests/test_directional_diffusion.py b/hysop/operator/tests/test_directional_diffusion.py
index 4949daad9..626192604 100644
--- a/hysop/operator/tests/test_directional_diffusion.py
+++ b/hysop/operator/tests/test_directional_diffusion.py
@@ -77,25 +77,22 @@ class TestDirectionalDiffusionOperator(object):
Fin=Fin, Fout=Fout, coeffs=coeffs)
@staticmethod
- def __random_init(data, coords, dtype):
- shape = data[0].shape
+ def __random_init(data, coords, dtype, component):
+ shape = data.shape
if is_integer(dtype):
- for d in data:
- d[...] = npw.random.random_integers(low=0, high=255, size=shape)
+ data[...] = npw.random.random_integers(low=0, high=255, size=shape)
elif is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape)
+ data[...] = npw.random.random(size=data.shape)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
@staticmethod
- def __scalar_init(data, coords, dtype):
+ def __scalar_init(data, coords, dtype, component):
if is_fp(dtype):
- for i,(d,coord) in enumerate(zip(data,coords)):
- d[...] = 1
- for xi in coord:
- d[...] *= npw.cos(xi*(i+1))
+ data[...] = 1
+ for xi in coords:
+ data[...] *= npw.cos(xi*(component+1))
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
diff --git a/hysop/operator/tests/test_directional_stretching.py b/hysop/operator/tests/test_directional_stretching.py
index 326327d3a..48e40dcf9 100644
--- a/hysop/operator/tests/test_directional_stretching.py
+++ b/hysop/operator/tests/test_directional_stretching.py
@@ -85,15 +85,13 @@ class TestDirectionalStretchingOperator(object):
C=C, A=A, formulation=formulation)
@staticmethod
- def __random_init(data, coords):
- shape = data[0].shape
- dtype = data[0].dtype
+ def __random_init(data, coords, component):
+ shape = data.shape
+ dtype = data.dtype
if is_integer(dtype):
- for d in data:
- d[...] = npw.random.random_integers(low=0, high=255, size=shape)
+ data[...] = npw.random.random_integers(low=0, high=255, size=shape)
elif is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape)
+ data[...] = npw.random.random(size=shape)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
diff --git a/hysop/operator/tests/test_fd_derivative.py b/hysop/operator/tests/test_fd_derivative.py
index 6bca7fbe3..12f7f188d 100644
--- a/hysop/operator/tests/test_fd_derivative.py
+++ b/hysop/operator/tests/test_fd_derivative.py
@@ -93,20 +93,17 @@ class TestFiniteDifferencesDerivative(object):
pass
@staticmethod
- def __random_init(data, coords):
- dtype = data[0].dtype
+ def __random_init(data, coords, component):
+ dtype = data.dtype
if is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape).astype(dtype=dtype)
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
@classmethod
- def __analytic_init(cls, data, coords, fns, t):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- d[...] = fn(*(coord+(t(),))).astype(d.dtype)
+ def __analytic_init(cls, data, coords, component, fns, t):
+ data[...] = fns[component](*(coords+(t(),))).astype(data.dtype)
def _test(self, dim, dtype,
size_min=None, size_max=None):
diff --git a/hysop/operator/tests/test_poisson.py b/hysop/operator/tests/test_poisson.py
index 4a5a04d71..693ed2040 100644
--- a/hysop/operator/tests/test_poisson.py
+++ b/hysop/operator/tests/test_poisson.py
@@ -75,21 +75,17 @@ class TestPoissonOperator(object):
return (analytic_expressions, analytic_functions)
@staticmethod
- def __random_init(data, coords, dtype):
- for d in data:
- if is_fp(d.dtype):
- d[...] = npw.random.random(size=d.shape).astype(dtype=d.dtype)
- else:
- msg = 'Unknown dtype {}.'.format(d.dtype)
- raise NotImplementedError(msg)
+ def __random_init(data, coords, component, dtype):
+ if is_fp(dtype):
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
+ else:
+ msg = 'Unknown dtype {}.'.format(dtype)
+ raise NotImplementedError(msg)
@staticmethod
- def __analytic_init(data, coords, dtype, fns):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- coord = tuple(c.astype(d.dtype) for c in coord)
- d[...] = fn(*coord).astype(d.dtype)
-
+ def __analytic_init(data, coords, fns, component, dtype):
+ fn = fns[component]
+ data[...] = fn(*coords).astype(data.dtype)
def _test(self, dim, dtype, max_runs=5,
polynomial=False, size_min=None, size_max=None):
diff --git a/hysop/operator/tests/test_poisson_curl.py b/hysop/operator/tests/test_poisson_curl.py
index 82d7bdd3d..30ec59dae 100644
--- a/hysop/operator/tests/test_poisson_curl.py
+++ b/hysop/operator/tests/test_poisson_curl.py
@@ -84,22 +84,17 @@ class TestPoissonCurlOperator(object):
@staticmethod
- def __random_init(data, coords, dtype):
- for d in data:
- if is_fp(d.dtype):
- d[...] = npw.random.random(size=d.shape).astype(dtype=d.dtype)
- else:
- msg = 'Unknown dtype {}.'.format(d.dtype)
- raise NotImplementedError(msg)
+ def __random_init(data, coords, component, dtype):
+ if is_fp(dtype):
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
+ else:
+ msg = 'Unknown dtype {}.'.format(dtype)
+ raise NotImplementedError(msg)
@staticmethod
- def __analytic_init(data, coords, dtype, fns):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- coord = tuple(c.astype(d.dtype) for c in coord)
- d[...] = fn(*coord).astype(d.dtype)
-
-
+ def __analytic_init(data, coords, fns, component, dtype):
+ fn = fns[component]
+ data[...] = fn(*coords).astype(data.dtype)
def _test(self, dim, dtype, max_runs=5,
polynomial=False, size_min=None, size_max=None):
diff --git a/hysop/operator/tests/test_restriction_filter.py b/hysop/operator/tests/test_restriction_filter.py
index dcf464c3b..744351cc9 100755
--- a/hysop/operator/tests/test_restriction_filter.py
+++ b/hysop/operator/tests/test_restriction_filter.py
@@ -5,7 +5,7 @@ from hysop.testsenv import __ENABLE_LONG_TESTS__
from hysop.tools.io_utils import IO
from hysop.tools.numpywrappers import npw
from hysop.tools.types import first_not_None
-from hysop.operator.spatial_filtering import RestrictionFilter
+from hysop.operator.spatial_filtering import SpatialFilter
from hysop.methods import FilteringMethod
from hysop.topology.cartesian_topology import CartesianTopology
from hysop.constants import implementation_to_backend, Implementation, HYSOP_REAL
@@ -18,17 +18,16 @@ from hysop import Field, Box, MPIParams
class TestMultiresolutionFilter(object):
@staticmethod
- def __f_init(data, coords):
+ def __f_init(data, coords, component):
from numpy import sin, cos
- (x, y, z) = coords[0]
- data[0][...] = - cos(x) * sin(y) * sin(z)
+ (x, y, z) = coords
+ data[...] = - cos(x) * sin(y) * sin(z)
@staticmethod
- def __random_init(data, coords):
- dtype = data[0].dtype
+ def __random_init(data, coords, component):
+ dtype = data.dtype
if is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape).astype(dtype=dtype)
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
@@ -93,7 +92,9 @@ class TestMultiresolutionFilter(object):
if impl is Implementation.PYTHON:
msg=' *Python: '
print msg,
- yield RestrictionFilter(input_variables={f: topo_f}, output_variables={f: topo_c}, **base_kwds)
+ yield SpatialFilter(input_variables={f: topo_f},
+ output_variables={f: topo_c},
+ **base_kwds)
print
else:
msg='Unknown implementation to test {}.'.format(impl)
diff --git a/hysop/operator/tests/test_solenoidal_projection.py b/hysop/operator/tests/test_solenoidal_projection.py
index 234a1e845..e9eed1747 100644
--- a/hysop/operator/tests/test_solenoidal_projection.py
+++ b/hysop/operator/tests/test_solenoidal_projection.py
@@ -149,28 +149,24 @@ class TestSolenoidalProjectionOperator(object):
print '>> TESTED ALL {}D BOUNDARY CONDITIONS <<'.format(dim)
print
print
-
- @classmethod
- def __analytic_init(cls, data, coords, dtype, fns):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- d[...] = npw.asarray(fn(*coord)).astype(dtype)
-
- @classmethod
- def __zero_init(cls, data, coords, dtype):
- for d in data:
- d[...] = 0
-
+
@staticmethod
- def __random_init(data, coords, dtype):
- shape = data[0].shape
+ def __random_init(data, coords, component, dtype):
if is_fp(dtype):
- for d in data:
- d[...] = npw.random.random(size=d.shape).astype(dtype=dtype)
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
else:
msg = 'Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
+ @staticmethod
+ def __analytic_init(data, coords, fns, component, dtype):
+ fn = fns[component]
+ data[...] = npw.asarray(fn(*coords)).astype(dtype)
+
+ @classmethod
+ def __zero_init(cls, data, coords, dtype, component):
+ data[...] = 0
+
def _test_one(self, shape, dtype, polynomial,
domain, U, U0, U1, divU, divU0, divU1):
diff --git a/hysop/operator/tests/test_spectral_curl.py b/hysop/operator/tests/test_spectral_curl.py
index 3407397bd..273719db8 100644
--- a/hysop/operator/tests/test_spectral_curl.py
+++ b/hysop/operator/tests/test_spectral_curl.py
@@ -79,24 +79,18 @@ class TestSpectralCurl(object):
analytic_functions = {'Fin':fFins, 'Fout':fFouts}
return (analytic_expressions, analytic_functions)
-
- @staticmethod
- def __random_init(data, coords, dtype):
- for d in data:
- if is_fp(d.dtype):
- d[...] = npw.random.random(size=d.shape).astype(dtype=d.dtype)
- else:
- msg = 'Unknown dtype {}.'.format(d.dtype)
- raise NotImplementedError(msg)
-
@staticmethod
- def __analytic_init(data, coords, dtype, fns):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- coord = tuple(c.astype(d.dtype) for c in coord)
- d[...] = fn(*coord).astype(d.dtype)
-
+ def __random_init(data, coords, component, dtype):
+ if is_fp(dtype):
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
+ else:
+ msg = 'Unknown dtype {}.'.format(dtype)
+ raise NotImplementedError(msg)
+ @staticmethod
+ def __analytic_init(data, coords, fns, component, dtype):
+ fn = fns[component]
+ data[...] = npw.asarray(fn(*coords)).astype(dtype)
def _test(self, dim, dtype, nb_components, max_runs=5,
polynomial=False, size_min=None, size_max=None):
diff --git a/hysop/operator/tests/test_spectral_derivative.py b/hysop/operator/tests/test_spectral_derivative.py
index 6a5b2b96e..b8f3cb7f0 100644
--- a/hysop/operator/tests/test_spectral_derivative.py
+++ b/hysop/operator/tests/test_spectral_derivative.py
@@ -92,20 +92,18 @@ class TestSpectralDerivative(object):
pass
@staticmethod
- def __random_init(data, coords):
- for d in data:
- if is_fp(d.dtype):
- d[...] = npw.random.random(size=d.shape).astype(dtype=d.dtype)
- else:
- msg = 'Unknown dtype {}.'.format(d.dtype)
- raise NotImplementedError(msg)
+ def __random_init(data, coords, component):
+ dtype = data.dtype
+ if is_fp(dtype):
+ data[...] = npw.random.random(size=data.shape).astype(dtype=dtype)
+ else:
+ msg = 'Unknown dtype {}.'.format(dtype)
+ raise NotImplementedError(msg)
@staticmethod
- def __analytic_init(data, coords, fns, t):
- assert len(fns) == len(data)
- for (d,fn,coord) in zip(data,fns,coords):
- coord = tuple(c.astype(d.dtype) for c in coord)
- d[...] = fn(*(coord+(t(),))).astype(d.dtype)
+ def __analytic_init(data, coords, fns, t, component):
+ fn = fns[component]
+ data[...] = npw.asarray(fn(*(coords+(t(),)))).astype(data.dtype)
def _test(self, dim, dtype, polynomial, max_derivative=2,
size_min=None, size_max=None, max_runs=None):
diff --git a/hysop/operator/tests/test_transpose.py b/hysop/operator/tests/test_transpose.py
index 6ebe79df3..655f2a73b 100644
--- a/hysop/operator/tests/test_transpose.py
+++ b/hysop/operator/tests/test_transpose.py
@@ -80,19 +80,16 @@ class TestTransposeOperator(object):
domain=domain, Fin=Fin, Fout=Fout)
@classmethod
- def __field_init(cls, data, coords, dtype):
- shape = data[0].shape
+ def __field_init(cls, data, coords, component, dtype):
+ shape = data.shape
if is_integer(dtype):
- for d in data:
- d[...] = np.random.random_integers(low=0, high=255, size=shape)
+ data[...] = np.random.random_integers(low=0, high=255, size=shape)
elif is_fp(dtype):
- for d in data:
- d[...] = np.random.random(size=shape)
+ data[...] = np.random.random(size=shape)
elif is_complex(dtype):
- for d in data:
- real = np.random.random(size=shape)
- imag = np.random.random(size=shape)
- d[...] = real + 1j*imag
+ real = np.random.random(size=shape)
+ imag = np.random.random(size=shape)
+ data[...] = real + 1j*imag
else:
msg='Unknown dtype {}.'.format(dtype)
raise NotImplementedError(msg)
@@ -223,14 +220,14 @@ class TestTransposeOperator(object):
def perform_tests(self):
self.test_2d_out_of_place()
+ self.test_3d_out_of_place()
if __ENABLE_LONG_TESTS__:
- self.test_3d_out_of_place()
self.test_4d_out_of_place()
self.test_upper_dimensions_out_of_place()
self.test_2d_inplace()
+ self.test_3d_inplace()
if __ENABLE_LONG_TESTS__:
- self.test_3d_inplace()
self.test_4d_inplace()
self.test_upper_dimensions_inplace()
diff --git a/hysop/testsenv.py b/hysop/testsenv.py
index 8e1b7e1ec..046f2b4d3 100644
--- a/hysop/testsenv.py
+++ b/hysop/testsenv.py
@@ -93,17 +93,14 @@ if __HAS_OPENCL_BACKEND__:
cl_environments[cl_device_type] = []
if (cl_device_type is None):
mpi_params = default_mpi_params()
- if all_platforms:
- for i,plat in enumerate(cl.get_platforms()):
- for j,dev in enumerate(plat.get_devices()):
- cl_env = get_or_create_opencl_env(platform_id=i, device_id=j,
- mpi_params=mpi_params, **kwds)
+ for i,plat in enumerate(cl.get_platforms()):
+ for j,dev in enumerate(plat.get_devices()):
+ cl_env = get_or_create_opencl_env(platform_id=i, device_id=j,
+ mpi_params=mpi_params, **kwds)
+ if (i==__DEFAULT_PLATFORM_ID__) and (j==__DEFAULT_DEVICE_ID__):
+ cl_environments[None].insert(0, cl_env)
+ else:
cl_environments[None].append(cl_env)
- else:
- cl_env = get_or_create_opencl_env(platform_id=__DEFAULT_PLATFORM_ID__,
- device_id=__DEFAULT_DEVICE_ID__,
- mpi_params=mpi_params, **kwds)
- cl_environments[None].append(cl_env)
else:
for cl_env in iter_clenv(cl_device_type=None, all_platforms=True):
if (cl_env.device.type & cl_device_type):
@@ -120,6 +117,7 @@ if __HAS_OPENCL_BACKEND__:
yield cl_env
if not all_platforms:
return
+
else:
opencl_failed = pytest.mark.xfail
iter_clenv = None
diff --git a/hysop/topology/cartesian_descriptor.py b/hysop/topology/cartesian_descriptor.py
index 80a3315d3..344a44dba 100644
--- a/hysop/topology/cartesian_descriptor.py
+++ b/hysop/topology/cartesian_descriptor.py
@@ -1,5 +1,5 @@
-from hysop.tools.types import check_instance
+from hysop.tools.types import check_instance, to_tuple
from hysop.topology.topology_descriptor import TopologyDescriptor
from hysop.topology.cartesian_topology import CartesianTopology
from hysop.tools.parameters import CartesianDiscretization
@@ -209,3 +209,19 @@ Instance of those types can be used to create a CartesianTopologyDescriptor.
Thus they can be passed in the variables of each operator supporting
CartesianTopology topologies.
"""
+
+def get_topo_descriptor_discretization(td):
+ """
+ Get grid resolution from any type of CartesianTopologyDescriptor.
+ """
+ check_instance(td, CartesianTopologyDescriptors, allow_none=True)
+ if (td is None):
+ return None
+ elif isinstance(td, CartesianTopology):
+ td = td.grid_resolution
+ elif isinstance(td, CartesianTopologyDescriptor):
+ td = td.grid_resolution
+ elif isinstance(td, CartesianDiscretization):
+ td = td.grid_resolution
+ return to_tuple(td)
+
--
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