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import functools
import os
from mpi4py import MPI
import numpy as np
from mpi4py_fft import PFFT, HDF5File, NCFile, newDistArray, generate_xdmf
N = (12, 13, 14, 15)
comm = MPI.COMM_WORLD
ex = {True: 'c', False: 'r'}
writer = {'hdf5': functools.partial(HDF5File, mode='w'),
'netcdf4': functools.partial(NCFile, mode='w')}
reader = {'hdf5': functools.partial(HDF5File, mode='r'),
'netcdf4': functools.partial(NCFile, mode='r')}
ending = {'hdf5': '.h5', 'netcdf4': '.nc'}
def remove_if_exists(filename):
try:
os.remove(filename)
except OSError:
pass
def cleanup():
import glob
files = glob.glob('*.h5')+glob.glob('*.xdmf')+glob.glob('*.nc')
for f in files:
remove_if_exists(f)
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_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()
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()
if __name__ == '__main__':
#pylint: disable=unused-import
cleanup()
skip = {'hdf5': False, 'netcdf4': True}
try:
import h5py
except ImportError:
skip['hdf5'] = True
try:
import netCDF4
except ImportError:
skip['netcdf4'] = True
for bnd in ('hdf5', 'netcdf4'):
if not skip[bnd]:
forw_output = [False]
if bnd == 'hdf5':
forw_output.append(True)
for kind in forw_output:
test_3D(bnd, kind)
test_2D(bnd, kind)
if bnd == 'hdf5':
test_4D(bnd, kind)
cleanup()
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