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__copyright__ = """
Copyright (C) 2021 University of Illinois Board of Trustees
"""
__license__ = """
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE.
"""
import numpy as np
from arraycontext import ( # noqa
thaw,
pytest_generate_tests_for_pyopencl_array_context
as pytest_generate_tests
)
from grudge import DiscretizationCollection
import grudge.op as op
from meshmode.dof_array import flatten
from pytools.obj_array import make_obj_array
import pytest
import logging
logger = logging.getLogger(__name__)
def test_nodal_reductions(actx_factory):
actx = actx_factory()
from mesh_data import BoxMeshBuilder
builder = BoxMeshBuilder(ambient_dim=1)
mesh = builder.get_mesh(4, builder.mesh_order)
dcoll = DiscretizationCollection(actx, mesh, order=builder.order)
x = thaw(dcoll.nodes(), actx)
def f(x):
return -actx.np.sin(10*x[0])
def g(x):
return actx.np.cos(2*x[0])
def h(x):
return -actx.np.tan(5*x[0])
fields = make_obj_array([f(x), g(x), h(x)])
f_ref = actx.to_numpy(flatten(fields[0]))
g_ref = actx.to_numpy(flatten(fields[1]))
h_ref = actx.to_numpy(flatten(fields[2]))
concat_fields = np.concatenate([f_ref, g_ref, h_ref])
for inner_grudge_op, np_op in [(op.nodal_sum, np.sum),
(op.nodal_max, np.max),
(op.nodal_min, np.min)]:
# FIXME: Remove this once all grudge reductions return device scalars
def grudge_op(dcoll, dd, vec):
res = inner_grudge_op(dcoll, dd, vec)
from numbers import Number
if not isinstance(res, Number):
return actx.to_numpy(res)
else:
return res
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# Componentwise reduction checks
assert np.isclose(grudge_op(dcoll, "vol", fields[0]),
np_op(f_ref), rtol=1e-13)
assert np.isclose(grudge_op(dcoll, "vol", fields[1]),
np_op(g_ref), rtol=1e-13)
assert np.isclose(grudge_op(dcoll, "vol", fields[2]),
np_op(h_ref), rtol=1e-13)
# Test nodal reductions work on object arrays
assert np.isclose(grudge_op(dcoll, "vol", fields),
np_op(concat_fields), rtol=1e-13)
def test_elementwise_reductions(actx_factory):
actx = actx_factory()
from mesh_data import BoxMeshBuilder
builder = BoxMeshBuilder(ambient_dim=1)
nelements = 4
mesh = builder.get_mesh(nelements, builder.mesh_order)
dcoll = DiscretizationCollection(actx, mesh, order=builder.order)
x = thaw(dcoll.nodes(), actx)
def f(x):
return actx.np.sin(x[0])
field = f(x)
mins = []
maxs = []
sums = []
for gidx, grp_f in enumerate(field):
min_res = np.empty(grp_f.shape)
max_res = np.empty(grp_f.shape)
sum_res = np.empty(grp_f.shape)
for eidx in range(dcoll._volume_discr.groups[gidx].nelements):
element_data = actx.to_numpy(grp_f[eidx])
min_res[eidx, :] = np.min(element_data)
max_res[eidx, :] = np.max(element_data)
sum_res[eidx, :] = np.sum(element_data)
mins.append(actx.from_numpy(min_res))
maxs.append(actx.from_numpy(max_res))
sums.append(actx.from_numpy(sum_res))
from meshmode.dof_array import DOFArray, flat_norm
ref_mins = DOFArray(actx, data=tuple(mins))
ref_maxs = DOFArray(actx, data=tuple(maxs))
ref_sums = DOFArray(actx, data=tuple(sums))
elem_mins = op.elementwise_min(dcoll, field)
elem_maxs = op.elementwise_max(dcoll, field)
elem_sums = op.elementwise_sum(dcoll, field)
assert flat_norm(elem_mins - ref_mins, ord=np.inf) < 1.e-15
assert flat_norm(elem_maxs - ref_maxs, ord=np.inf) < 1.e-15
assert flat_norm(elem_sums - ref_sums, ord=np.inf) < 1.e-15
# You can test individual routines by typing
# $ python test_grudge.py 'test_routine()'
if __name__ == "__main__":
import sys
if len(sys.argv) > 1:
exec(sys.argv[1])
else:
pytest.main([__file__])