def test_newDistArray():
N = (8, 8, 8)
pfft = PFFT(MPI.COMM_WORLD, N)
for forward_output in (True, False):
for view in (True, False):
for rank in (0, 1, 2):
a = newDistArray(pfft,
forward_output=forward_output,
rank=rank,
view=view)
if view is False:
assert isinstance(a, DistArray)
assert a.rank == rank
if rank == 0:
qfft = PFFT(MPI.COMM_WORLD, darray=a)
elif rank == 1:
qfft = PFFT(MPI.COMM_WORLD, darray=a[0])
else:
qfft = PFFT(MPI.COMM_WORLD, darray=a[0, 0])
qfft.destroy()
else:
assert isinstance(a, np.ndarray)
assert a.base.rank == rank
pfft.destroy()
def test_2D(backend, forward_output):
if backend == 'netcdf4':
assert forward_output is False
T = PFFT(comm, (N[0], N[1]))
for i, domain in enumerate([
None, ((0, np.pi), (0, 2 * np.pi)),
(np.arange(N[0], dtype=float) * 1 * np.pi / N[0],
np.arange(N[1], dtype=float) * 2 * np.pi / N[1])
]):
for rank in range(3):
filename = "".join(
('test2D_{}{}{}'.format(ex[i == 0], ex[forward_output],
rank), ending[backend]))
if backend == 'netcdf4':
remove_if_exists(filename)
u = newDistArray(T,
forward_output=forward_output,
val=1,
rank=rank)
hfile = writer[backend](filename, domain=domain)
assert hfile.backend() == backend
hfile.write(0, {'u': [u]})
hfile.write(1, {'u': [u]})
u.write(hfile, 'u', 2)
if rank > 0:
hfile.write(0, {'u': [u]}, as_scalar=True)
hfile.write(1, {'u': [u]}, as_scalar=True)
u.write(hfile, 'u', 2, as_scalar=True)
u.write('t' + filename, 'u', 0)
u.write('t' + filename, 'u', 0, [slice(None), 3])
if not forward_output and backend == 'hdf5' and comm.Get_rank(
) == 0:
generate_xdmf(filename)
generate_xdmf(filename, order='visit')
u0 = newDistArray(T, forward_output=forward_output, rank=rank)
read = reader[backend](filename)
read.read(u0, 'u', step=0)
u0.read(filename, 'u', 2)
u0.read(read, 'u', 2)
assert np.allclose(u0, u)
if backend == 'netcdf4': # Test opening file in mode 'a' when not existing
remove_if_exists('nctesta.nc')
_ = NCFile('nctesta.nc', domain=domain, mode='a')
T.destroy()
def test_4D(backend, forward_output):
if backend == 'netcdf4':
assert forward_output is False
T = PFFT(comm, (N[0], N[1], N[2], N[3]))
d0 = ((0, np.pi), (0, 2 * np.pi), (0, 3 * np.pi), (0, 4 * np.pi))
d1 = (np.arange(N[0], dtype=float) * 1 * np.pi / N[0],
np.arange(N[1], dtype=float) * 2 * np.pi / N[1],
np.arange(N[2], dtype=float) * 3 * np.pi / N[2],
np.arange(N[3], dtype=float) * 4 * np.pi / N[3])
for i, domain in enumerate([None, d0, d1]):
for rank in range(3):
filename = "".join(
('h5test4_{}{}{}'.format(ex[i == 0], ex[forward_output],
rank), ending[backend]))
if backend == 'netcdf4':
remove_if_exists('uv' + filename)
u = newDistArray(T, forward_output=forward_output, rank=rank)
v = newDistArray(T, forward_output=forward_output, rank=rank)
h0file = writer[backend]('uv' + filename, domain=domain)
u[:] = np.random.random(u.shape)
v[:] = 2
for k in range(3):
h0file.write(
k, {
'u':
[u, (u, [slice(None), 4,
slice(None),
slice(None)])],
'v': [v,
(v, [slice(None), slice(None), 5, 6])]
})
if not forward_output and backend == 'hdf5' and comm.Get_rank(
) == 0:
generate_xdmf('uv' + filename)
u0 = newDistArray(T, forward_output=forward_output, rank=rank)
read = reader[backend]('uv' + filename)
read.read(u0, 'u', step=0)
assert np.allclose(u0, u)
read.read(u0, 'v', step=0)
assert np.allclose(u0, v)
T.destroy()
def test_3D(backend, forward_output):
if backend == 'netcdf4':
assert forward_output is False
T = PFFT(comm, (N[0], N[1], N[2]))
d0 = ((0, np.pi), (0, 2 * np.pi), (0, 3 * np.pi))
d1 = (np.arange(N[0], dtype=float) * 1 * np.pi / N[0],
np.arange(N[1], dtype=float) * 2 * np.pi / N[1],
np.arange(N[2], dtype=float) * 3 * np.pi / N[2])
for i, domain in enumerate([None, d0, d1]):
for rank in range(3):
filename = ''.join(
('test_{}{}{}'.format(ex[i == 0], ex[forward_output],
rank), ending[backend]))
if backend == 'netcdf4':
remove_if_exists('uv' + filename)
remove_if_exists('v' + filename)
u = newDistArray(T, forward_output=forward_output, rank=rank)
v = newDistArray(T, forward_output=forward_output, rank=rank)
h0file = writer[backend]('uv' + filename, domain=domain)
h1file = writer[backend]('v' + filename, domain=domain)
u[:] = np.random.random(u.shape)
v[:] = 2
for k in range(3):
h0file.write(
k, {
'u': [
u, (u, [slice(None), slice(None), 4]),
(u, [5, 5, slice(None)])
],
'v': [v,
(v, [slice(None), 6, slice(None)])]
})
h1file.write(
k, {
'v': [
v,
(v, [slice(None), 6, slice(None)]),
(v, [6, 6, slice(None)])
]
})
# One more time with same k
h0file.write(
k, {
'u': [
u, (u, [slice(None), slice(None), 4]),
(u, [5, 5, slice(None)])
],
'v': [v, (v, [slice(None), 6, slice(None)])]
})
h1file.write(
k, {
'v': [
v, (v, [slice(None), 6, slice(None)]),
(v, [6, 6, slice(None)])
]
})
if rank > 0:
for k in range(3):
u.write('uv' + filename, 'u', k, as_scalar=True)
u.write('uv' + filename,
'u',
k, [slice(None), slice(None), 4],
as_scalar=True)
u.write('uv' + filename,
'u',
k, [5, 5, slice(None)],
as_scalar=True)
v.write('uv' + filename, 'v', k, as_scalar=True)
v.write('uv' + filename,
'v',
k, [slice(None), 6, slice(None)],
as_scalar=True)
if not forward_output and backend == 'hdf5' and comm.Get_rank(
) == 0:
generate_xdmf('uv' + filename)
generate_xdmf('v' + filename, periodic=False)
generate_xdmf('v' + filename, periodic=(True, True, True))
generate_xdmf('v' + filename, order='visit')
u0 = newDistArray(T, forward_output=forward_output, rank=rank)
read = reader[backend]('uv' + filename)
read.read(u0, 'u', step=0)
assert np.allclose(u0, u)
read.read(u0, 'v', step=0)
assert np.allclose(u0, v)
T.destroy()
