def test_pickle(self):
s = pickle.dumps(self.matrix)
mat = pickle.loads(s)
self.assertIsInstance(mat, type(self.matrix))
numpy.testing.assert_equal(mat.export('dense'), self.exact)
with self.subTest('cross-pickle'), matrix.Numpy():
mat = pickle.loads(s)
self.assertIsInstance(mat, matrix.NumpyMatrix)
numpy.testing.assert_equal(mat.export('dense'), self.exact)
def project(self, projection):
ns = fn.Namespace()
for name, func in self._kwargs.items():
setattr(ns, name, func)
for p, (name, func) in zip(projection, self._defaults.items()):
if p is not None:
func = fn.matmat(p, func)
setattr(ns, name, func)
integrand = getattr(ns, self._evaluator)(self._code)
domain, geom, ischeme = self.prop('domain', 'geometry', 'ischeme')
with matrix.Numpy():
retval = domain.integrate(integrand * fn.J(geom), ischeme=ischeme)
return NumpyArrayIntegrand(retval)
def project(self, projection):
obj = self.obj
s = slice(None)
for i, p in enumerate(projection):
if p is None:
continue
obj = obj[(s,)*i + (_,s,Ellipsis)]
obj = obj * p[(_,)*i + (s,s) + (_,) * (self.ndim - i - 1)]
obj = obj.sum(i+1)
domain, geom, ischeme = self.prop('domain', 'geometry', 'ischeme')
with matrix.Numpy():
retval = domain.integrate(obj * fn.J(geom), ischeme=ischeme)
return NumpyArrayIntegrand(retval)
def test_matrix_numpy(self):
self._test_matrix(matrix.Numpy())
def assemble(self, data, index, shape):
if len(shape) > 2:
return matrix.Numpy().assemble(data, index, shape)
return super().assemble(data, index, shape)
def test_deprecated_context(self):
with self.assertWarns(warnings.NutilsDeprecationWarning):
with matrix.Numpy():
pass
def test_pickle(self):
s = pickle.dumps(self.matrix)
mat = pickle.loads(s)
self.assertIsInstance(mat, type(self.matrix))
numpy.testing.assert_equal(mat.export('dense'), self.exact)
with self.subTest('cross-pickle'), matrix.Numpy():
mat = pickle.loads(s)
self.assertIsInstance(mat, matrix.NumpyMatrix)
numpy.testing.assert_equal(mat.export('dense'), self.exact)
@ifsupported
def test_diagonal(self):
self.assertAllEqual(self.matrix.diagonal(), numpy.diag(self.exact))
solver('numpy', backend=matrix.Numpy(), args=[{}])
solver('scipy',
backend=matrix.Scipy(),
args=[{},
dict(solver='gmres', atol=1e-5, restart=100, precon='spilu'),
dict(solver='gmres', atol=1e-5, precon='splu'),
dict(solver='cg', atol=1e-5, precon='diag')] + [
dict(solver=s, atol=1e-5)
for s in ('bicg', 'bicgstab', 'cg', 'cgs', 'lgmres', 'minres')
])
for threading in matrix.MKL.Threading.SEQUENTIAL, matrix.MKL.Threading.TBB:
solver('mkl:{}'.format(threading.name.lower()),
backend=matrix.MKL(threading=threading),
args=[{},
dict(solver='fgmres', atol=1e-8),
dict(solver='fgmres', atol=1e-8, precon='diag')])