def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array, mpi_type = self.args
slices = common.slice_index_two_points(pt0, pt1)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1)
value = np.random.rand(*shape).astype(np.float32)
else:
value = np.random.ranf()
# instance
fields = Fields(nx, ny, nz, '', 'single', 0, mpi_type=mpi_type)
tfunc = lambda tstep: np.sin(0.03 * tstep)
incident = DirectIncident(fields, str_f, pt0, pt1, tfunc, value)
# host allocations
eh = np.zeros(fields.ns_pitch, dtype=fields.dtype)
getf = GetFields(fields, str_f, pt0, pt1)
# verify
eh[slices] = fields.dtype(value) * fields.dtype(tfunc(1))
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
original = eh[slices]
getf.get_event().wait()
copy = getf.get_fields()
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array, mpi_type = self.args
slices = common.slice_index_two_points(pt0, pt1)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1)
value = np.random.rand(*shape).astype(np.float32)
else:
value = np.random.ranf()
# instance
fields = Fields(nx, ny, nz, '', 'single', 0, mpi_type=mpi_type)
tfunc = lambda tstep: np.sin(0.03*tstep)
incident = DirectIncident(fields, str_f, pt0, pt1, tfunc, value)
# host allocations
eh = np.zeros(fields.ns_pitch, dtype=fields.dtype)
getf = GetFields(fields, str_f, pt0, pt1)
# verify
eh[slices] = fields.dtype(value) * fields.dtype(tfunc(1))
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
original = eh[slices]
getf.get_event().wait()
copy = getf.get_fields()
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
ufunc, nx, ny, nz, coeff_use, precision_float, use_cpu_core, split, tmax = self.args
fields = Fields(nx, ny, nz, coeff_use, precision_float, use_cpu_core)
core = Core(fields)
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
slice_xyz = [slice(None, None), slice(None, None), fields.slice_z]
# allocations
ns = fields.ns
dtype = fields.dtype
ehs = common_update.generate_random_ehs(nx, ny, nz, dtype, ufunc)
fields.set_ehs(*ehs)
ces, chs = common_update.generate_random_cs(coeff_use, nx, ny, nz, dtype)
if 'e' in coeff_use:
fields.set_ces(*ces)
if 'h' in coeff_use:
fields.set_chs(*chs)
# update
if ufunc == 'e':
for tstep in xrange(0, tmax):
fields.update_e()
common_update.update_e(ehs, ces)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[:3]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(norm, 0, '%s, %s, %g, %g' % (self.args, strf, norm, max_diff) )
if fields.pad != 0:
if strf == 'ez':
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad:])
else:
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad-1:])
self.assertEqual(norm2, 0, '%s, %s, %g, padding' % (self.args, strf, norm2) )
elif ufunc == 'h':
for tstep in xrange(0, tmax):
fields.update_h()
common_update.update_h(ehs, chs)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[3:]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(norm, 0, '%s, %s, %g, %g' % \
(self.args, strf, norm, max_diff) )
if fields.pad != 0:
if strf == 'hz':
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad:])
else:
norm2 = np.linalg.norm(fields.get(strf)[:,:,-fields.pad:])
self.assertEqual(norm2, 0, '%s, %s, %g, padding' % (self.args, strf, norm2) )
def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array = self.args
slice_xyz = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(nx, ny, nz, '', 'single')
setf = SetFields(fields, str_f, pt0, pt1, is_array)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1, len(str_fs))
value = np.random.rand(*shape).astype(fields.dtype)
split_value = np.split(value, len(str_fs))
split_value_dict = dict( zip(str_fs, split_value) )
else:
value = np.random.ranf()
# host allocations
ehs = [np.zeros(fields.ns, dtype=fields.dtype) for i in range(6)]
eh_dict = dict( zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs) )
# verify
for str_f in str_fs:
if is_array:
eh_dict[str_f][slice_xyz] = split_value_dict[str_f]
else:
eh_dict[str_f][slice_xyz] = value
setf.set_fields(value)
fields.enqueue_barrier()
for str_f in str_fs:
original = eh_dict[str_f]
copy = fields.get(str_f)[:,:,fields.slice_z]
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
nx, ny, nz, str_f, pt0, pt1, is_array = self.args
slice_xyz = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(nx, ny, nz, '', 'single')
setf = SetFields(fields, str_f, pt0, pt1, is_array)
# generate random source
if is_array:
shape = common.shape_two_points(pt0, pt1, len(str_fs))
value = np.random.rand(*shape).astype(fields.dtype)
split_value = np.split(value, len(str_fs))
split_value_dict = dict(zip(str_fs, split_value))
else:
value = np.random.ranf()
# host allocations
ehs = [np.zeros(fields.ns, dtype=fields.dtype) for i in range(6)]
eh_dict = dict(zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs))
# verify
for str_f in str_fs:
if is_array:
eh_dict[str_f][slice_xyz] = split_value_dict[str_f]
else:
eh_dict[str_f][slice_xyz] = value
setf.set_fields(value)
fields.enqueue_barrier()
for str_f in str_fs:
original = eh_dict[str_f]
copy = fields.get(str_f)[:, :, fields.slice_z]
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
def runTest(self):
ufunc, nx, ny, nz, coeff_use, precision_float, use_cpu_core, split, tmax = self.args
fields = Fields(nx, ny, nz, coeff_use, precision_float, use_cpu_core)
core = Core(fields)
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
slice_xyz = [slice(None, None), slice(None, None), fields.slice_z]
# allocations
ns = fields.ns
dtype = fields.dtype
ehs = common_update.generate_random_ehs(nx, ny, nz, dtype, ufunc)
fields.set_ehs(*ehs)
ces, chs = common_update.generate_random_cs(coeff_use, nx, ny, nz,
dtype)
if 'e' in coeff_use:
fields.set_ces(*ces)
if 'h' in coeff_use:
fields.set_chs(*chs)
# update
if ufunc == 'e':
for tstep in xrange(0, tmax):
fields.update_e()
common_update.update_e(ehs, ces)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[:3]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(
norm, 0,
'%s, %s, %g, %g' % (self.args, strf, norm, max_diff))
if fields.pad != 0:
if strf == 'ez':
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad:])
else:
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad - 1:])
self.assertEqual(
norm2, 0,
'%s, %s, %g, padding' % (self.args, strf, norm2))
elif ufunc == 'h':
for tstep in xrange(0, tmax):
fields.update_h()
common_update.update_h(ehs, chs)
fields.enqueue_barrier()
for strf, eh in zip(strf_list, ehs)[3:]:
norm = np.linalg.norm(eh - fields.get(strf)[slice_xyz])
max_diff = np.abs(eh - fields.get(strf)[slice_xyz]).max()
self.assertEqual(norm, 0, '%s, %s, %g, %g' % \
(self.args, strf, norm, max_diff) )
if fields.pad != 0:
if strf == 'hz':
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad:])
else:
norm2 = np.linalg.norm(
fields.get(strf)[:, :, -fields.pad:])
self.assertEqual(
norm2, 0,
'%s, %s, %g, padding' % (self.args, strf, norm2))
mpl.rc('image', interpolation='nearest', origin='lower')
fig = plt.figure(figsize=(14, 8))
# z-axis
nx, ny, nz = 180, 160, 2
fields = Fields(QueueTask(), nx, ny, nz)
Core(fields)
Pbc(fields, 'xyz')
IncidentDirect(fields, 'ey', (20, 0, 0), (20, -1, -1), tfunc)
IncidentDirect(fields, 'ex', (0, 20, 0), (-1, 20, -1), tfunc)
for tstep in xrange(1, tmax + 1):
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
ax1 = fig.add_subplot(2, 3, 1)
ax1.imshow(fields.get('ey')[:, :, nz / 2].T, vmin=-1.1, vmax=1.1)
ax1.set_title('%s, ey[20,:,:]' % repr(fields.ns))
ax1.set_xlabel('x')
ax1.set_ylabel('y')
ax2 = fig.add_subplot(2, 3, 4)
ax2.imshow(fields.get('ex')[:, :, nz / 2].T, vmin=-1.1, vmax=1.1)
ax2.set_title('%s, ex[:,20,:]' % repr(fields.ns))
ax2.set_xlabel('x')
ax2.set_ylabel('y')
# y-axis
nx, ny, nz = 180, 2, 160
plt.ion()
fig = plt.figure(figsize=(14,8))
# z-axis
nx, ny, nz = 180, 160, 2
fields = Fields(nx, ny, nz)
Core(fields)
Pbc(fields, 'xyz')
IncidentDirect(fields, 'ey', (20, 0, 0), (20, ny-1, nz-1), tfunc)
IncidentDirect(fields, 'ex', (0, 20, 0), (nx-1, 20, nz-1), tfunc)
for tstep in xrange(1, tmax+1):
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
ax1 = fig.add_subplot(2, 3, 1)
ax1.imshow(fields.get('ey')[:,:,nz/2].T, vmin=-1.1, vmax=1.1)
ax1.set_title('%s, ey[20,:,:]' % repr(fields.ns))
ax1.set_xlabel('x')
ax1.set_ylabel('y')
ax2 = fig.add_subplot(2, 3, 4)
ax2.imshow(fields.get('ex')[:,:,nz/2].T, vmin=-1.1, vmax=1.1)
ax2.set_title('%s, ex[:,20,:]' % repr(fields.ns))
ax2.set_xlabel('x')
ax2.set_ylabel('y')
# y-axis
nx, ny, nz = 180, 2, 160
def runTest(self):
axis, nx, ny, nz, mpi_type = self.args
fields = Fields(nx, ny, nz, mpi_type=mpi_type)
core = Core(fields)
pbc = Pbc(fields, axis)
# allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
fields.set_ehs(*ehs)
# update
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
# verify
getf0, getf1 = {}, {}
strfs_e = {'x':['ey', 'ez'], 'y':['ex', 'ez'], 'z':['ex', 'ey']}[axis]
strfs_h = {'x':['hy', 'hz'], 'y':['hx', 'hz'], 'z':['hx', 'hy']}[axis]
pt0 = (0, 0, 0)
pt1 = { 'x': (0, ny-2, nz-2), \
'y': (nx-2, 0, nz-2), \
'z': (nx-2, ny-2, 0) }[axis]
getf0['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (nx-1, 0, 0), \
'y': (0, ny-1, 0), \
'z': (0, 0, nz-1) }[axis]
pt1 = { 'x': (nx-1, ny-2, nz-2), \
'y': (nx-2, ny-1, nz-2), \
'z': (nx-2, ny-2, nz-1) }[axis]
getf1['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (0, 1, 1), \
'y': (1, 0, 1), \
'z': (1, 1, 0) }[axis]
pt1 = { 'x': (0, ny-1, nz-1), \
'y': (nx-1, 0, nz-1), \
'z': (nx-1, ny-1, 0) }[axis]
getf0['h'] = GetFields(fields, strfs_h, pt0, pt1)
pt0 = { 'x': (nx-1, 1, 1), \
'y': (1, ny-1, 1), \
'z': (1, 1, nz-1) }[axis]
pt1 = (nx-1, ny-1, nz-1)
getf1['h'] = GetFields(fields, strfs_h, pt0, pt1)
for getf in getf0.values() + getf1.values():
getf.get_event().wait()
for eh in ['e', 'h']:
g0 = getf0[eh].get_fields()
g1 = getf1[eh].get_fields()
norm = np.linalg.norm(g0 - g1)
'''
print eh
print g0
print g1
'''
self.assertEqual(norm, 0, '%g, %s, %s' % (norm, self.args, eh))
def runTest(self):
axis, nx, ny, nz, mpi_type = self.args
fields = Fields(nx, ny, nz, mpi_type=mpi_type)
core = Core(fields)
pbc = Pbc(fields, axis)
# allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
fields.set_ehs(*ehs)
# update
fields.update_e()
fields.update_h()
fields.enqueue_barrier()
# verify
getf0, getf1 = {}, {}
strfs_e = {
'x': ['ey', 'ez'],
'y': ['ex', 'ez'],
'z': ['ex', 'ey']
}[axis]
strfs_h = {
'x': ['hy', 'hz'],
'y': ['hx', 'hz'],
'z': ['hx', 'hy']
}[axis]
pt0 = (0, 0, 0)
pt1 = { 'x': (0, ny-2, nz-2), \
'y': (nx-2, 0, nz-2), \
'z': (nx-2, ny-2, 0) }[axis]
getf0['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (nx-1, 0, 0), \
'y': (0, ny-1, 0), \
'z': (0, 0, nz-1) }[axis]
pt1 = { 'x': (nx-1, ny-2, nz-2), \
'y': (nx-2, ny-1, nz-2), \
'z': (nx-2, ny-2, nz-1) }[axis]
getf1['e'] = GetFields(fields, strfs_e, pt0, pt1)
pt0 = { 'x': (0, 1, 1), \
'y': (1, 0, 1), \
'z': (1, 1, 0) }[axis]
pt1 = { 'x': (0, ny-1, nz-1), \
'y': (nx-1, 0, nz-1), \
'z': (nx-1, ny-1, 0) }[axis]
getf0['h'] = GetFields(fields, strfs_h, pt0, pt1)
pt0 = { 'x': (nx-1, 1, 1), \
'y': (1, ny-1, 1), \
'z': (1, 1, nz-1) }[axis]
pt1 = (nx - 1, ny - 1, nz - 1)
getf1['h'] = GetFields(fields, strfs_h, pt0, pt1)
for getf in getf0.values() + getf1.values():
getf.get_event().wait()
for eh in ['e', 'h']:
g0 = getf0[eh].get_fields()
g1 = getf1[eh].get_fields()
norm = np.linalg.norm(g0 - g1)
'''
print eh
print g0
print g1
'''
self.assertEqual(norm, 0, '%g, %s, %s' % (norm, self.args, eh))
