def verify(s, pt0, pt1):
print('pt0 = %s, pt1 = %s' % (pt0, pt1))
slidx = common.get_slice_index(pt0, pt1)
shape = common.get_shape(pt0, pt1)
for strf in s.strf_list:
# non-spatial
fset = SetFields(s.fdtd, strf, pt0, pt1)
values = np.random.rand(*shape).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields(strf)
assert np.linalg.norm(values - copy) == 0
if pt0 != pt1:
for strf in s.strf_list:
# spatial
fset = SetFields(s.fdtd, strf, pt0, pt1, np.ndarray)
values = np.random.rand(*shape).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields(strf)
assert np.linalg.norm(values - copy) == 0
def verify(s, pt0, pt1):
print('pt0 = %s, pt1 = %s' % (pt0, pt1))
slidx = common.get_slice_index(pt0, pt1)
shape = common.get_shape(pt0, pt1)
for strf in s.strf_list:
# non-spatial
fset = SetFields(s.fdtd, strf, pt0, pt1)
values = np.random.rand(*shape).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields(strf)
assert np.linalg.norm(values - copy) == 0
if pt0 != pt1:
for strf in s.strf_list:
# spatial
fset = SetFields(s.fdtd, strf, pt0, pt1, np.ndarray)
values = np.random.rand(*shape).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields(strf)
assert np.linalg.norm(values - copy) == 0
def test_boundary(s):
print('\n-- test boundary (two fields) --')
shape_dict = {
'x': (s.ny * 2, s.nz),
'y': (s.nx * 2, s.nz),
'z': (s.nx * 2, s.ny)
}
print('E fields')
str_fs_dict = {'x': ['ey', 'ez'], 'y': ['ex', 'ez'], 'z': ['ex', 'ey']}
pt0_dict = {
'x': (s.nx - 1, 0, 0),
'y': (0, s.ny - 1, 0),
'z': (0, 0, s.nz - 1)
}
pt1 = (s.nx - 1, s.ny - 1, s.nz - 1)
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt0 = pt0_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fset = SetFields(s.fdtd, str_fs, pt0, pt1, np.ndarray)
values = np.random.rand(*shape_dict[axis]).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields()
assert np.linalg.norm(values - copy) == 0
print('H fields')
str_fs_dict = {'x': ['hy', 'hz'], 'y': ['hx', 'hz'], 'z': ['hx', 'hy']}
pt0 = (0, 0, 0)
pt1_dict = {
'x': (0, s.ny - 1, s.nz - 1),
'y': (s.nx - 1, 0, s.nz - 1),
'z': (s.nx - 1, s.ny - 1, 0)
}
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt1 = pt1_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fset = SetFields(s.fdtd, str_fs, pt0, pt1, np.ndarray)
values = np.random.rand(*shape_dict[axis]).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields()
assert np.linalg.norm(values - copy) == 0
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 test_boundary(s):
print('\n-- test boundary (two fields) --')
print('E fields')
str_fs_dict = {'x': ['ey', 'ez'], 'y': ['ex', 'ez'], 'z': ['ex', 'ey']}
pt0 = (0, 0, 0)
pt1_dict = {
'x': (0, s.ny - 1, s.nz - 1),
'y': (s.nx - 1, 0, s.nz - 1),
'z': (s.nx - 1, s.ny - 1, 0)
}
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt1 = pt1_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
for strf in str_fs:
original = s.fhosts[strf][slidx]
copy = fget.get_fields(strf)
assert np.linalg.norm(original - copy) == 0
print('H fields')
str_fs_dict = {'x': ['hy', 'hz'], 'y': ['hx', 'hz'], 'z': ['hx', 'hy']}
pt0_dict = {
'x': (s.nx - 1, 0, 0),
'y': (0, s.ny - 1, 0),
'z': (0, 0, s.nz - 1)
}
pt1 = (s.nx - 1, s.ny - 1, s.nz - 1)
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt0 = pt0_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
for strf in str_fs:
original = s.fhosts[strf][slidx]
copy = fget.get_fields(strf)
assert np.linalg.norm(original - copy) == 0
def test_boundary(s):
print('\n-- test boundary (two fields) --')
shape_dict = {'x':(s.ny*2, s.nz), 'y':(s.nx*2, s.nz), 'z':(s.nx*2, s.ny)}
print('E fields')
str_fs_dict = {'x':['ey','ez'], 'y':['ex','ez'], 'z':['ex','ey']}
pt0_dict = {'x':(s.nx-1, 0, 0), 'y':(0, s.ny-1, 0), 'z':(0, 0, s.nz-1)}
pt1 = (s.nx-1, s.ny-1, s.nz-1)
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt0 = pt0_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fset = SetFields(s.fdtd, str_fs, pt0, pt1, np.ndarray)
values = np.random.rand(*shape_dict[axis]).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields()
assert np.linalg.norm(values - copy) == 0
print('H fields')
str_fs_dict = {'x':['hy','hz'], 'y':['hx','hz'], 'z':['hx','hy']}
pt0 = (0, 0, 0)
pt1_dict = {'x':(0, s.ny-1, s.nz-1), 'y':(s.nx-1, 0, s.nz-1), 'z':(s.nx-1, s.ny-1, 0)}
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt1 = pt1_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fset = SetFields(s.fdtd, str_fs, pt0, pt1, np.ndarray)
values = np.random.rand(*shape_dict[axis]).astype(s.fdtd.dtype)
fset.set_fields(values)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields()
assert np.linalg.norm(values - copy) == 0
def verify(s, pt0, pt1):
print('pt0 = %s, pt1 = %s' % (pt0, pt1))
slidx = common.get_slice_index(pt0, pt1)
for strf in s.strf_list:
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
original = s.fhosts[strf][slidx]
copy = fget.get_fields(strf)
#print original, copy
assert np.linalg.norm(original - copy) == 0
def verify(s, pt0, pt1):
print('pt0 = %s, pt1 = %s' % (pt0, pt1))
slidx = common.get_slice_index(pt0, pt1)
for strf in s.strf_list:
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
original = s.fhosts[strf][slidx]
copy = fget.get_fields(strf)
#print original, copy
assert np.linalg.norm(original - copy) == 0
def test_boundary(s):
print('\n-- test boundary (two fields) --')
print('E fields')
str_fs_dict = {'x':['ey','ez'], 'y':['ex','ez'], 'z':['ex','ey']}
pt0 = (0, 0, 0)
pt1_dict = {'x':(0, s.ny-1, s.nz-1), 'y':(s.nx-1, 0, s.nz-1), 'z':(s.nx-1, s.ny-1, 0)}
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt1 = pt1_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
for strf in str_fs:
original = s.fhosts[strf][slidx]
copy = fget.get_fields(strf)
assert np.linalg.norm(original - copy) == 0
print('H fields')
str_fs_dict = {'x':['hy','hz'], 'y':['hx','hz'], 'z':['hx','hy']}
pt0_dict = {'x':(s.nx-1, 0, 0), 'y':(0, s.ny-1, 0), 'z':(0, 0, s.nz-1)}
pt1 = (s.nx-1, s.ny-1, s.nz-1)
for axis in str_fs_dict.keys():
print('direction : %s' % axis)
str_fs = str_fs_dict[axis]
pt0 = pt0_dict[axis]
slidx = common.get_slice_index(pt0, pt1)
fget = GetFields(s.fdtd, str_fs, pt0, pt1)
fget.get_event().wait()
for strf in str_fs:
original = s.fhosts[strf][slidx]
copy = fget.get_fields(strf)
assert np.linalg.norm(original - copy) == 0
def runTest(self):
nx, ny, nz, str_f, pt0, pt1 = 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')
getf = GetFields(fields, str_f, pt0, pt1)
# host allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
eh_dict = dict(zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs))
fields.set_ehs(*ehs)
# verify
getf.get_event().wait()
for str_f in str_fs:
original = eh_dict[str_f][slice_xyz]
copy = getf.get_fields(str_f)
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 = 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')
getf = GetFields(fields, str_f, pt0, pt1)
# host allocations
ehs = common_update.generate_random_ehs(nx, ny, nz, fields.dtype)
eh_dict = dict( zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs) )
fields.set_ehs(*ehs)
# verify
getf.get_event().wait()
for str_f in str_fs:
original = eh_dict[str_f][slice_xyz]
copy = getf.get_fields(str_f)
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
import matplotlib.pyplot as plt
plt.ion()
imag = plt.imshow(fdtd.ez[:,:,nz/2].T, cmap=plt.cm.hot, origin='lower', vmin=0, vmax=0.05)
plt.colorbar()
# Main loop
from datetime import datetime
t0 = datetime.now()
for tstep in xrange(1, tmax+1):
qtask.enqueue(fdtd.update_e)
qtask.enqueue(src.update, [tstep])
qtask.enqueue(fdtd.update_h)
if tstep % tgap == 0:
with LockQueueTask(qtask):
f = output.get_fields()
print('[%s] %d/%d (%d %%)\r' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100)),
sys.stdout.flush()
imag.set_array(f.T**2)
plt.draw()
print('[%s] %d/%d (%d %%)' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100))
#imag.set_array(fdtd.ez[:,:,nz/5*4].T**2 )
#plt.savefig('./simple.png')
#plt.show()
print('')
plt.colorbar()
# Main loop
from datetime import datetime
t0 = datetime.now()
for tstep in xrange(1, tmax+1):
fdtd.update_e()
src.update(tstep)
fdtd.update_h()
if tstep % tgap == 0:
print('[%s] %d/%d (%d %%)\r' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100)),
sys.stdout.flush()
output.get_event().wait()
imag.set_array(output.get_fields().T**2 )
#plt.savefig('./single.png')
plt.draw()
print('[%s] %d/%d (%d %%)' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100))
'''
imag.set_array(fdtd.ez[:,:,nz/5*4].T**2 )
plt.savefig('./simple.png')
plt.show()
'''
print('')
print fields.instance_list
# plot
import matplotlib.pyplot as plt
plt.ion()
fig = plt.figure(figsize=(12,8))
imag = plt.imshow(np.zeros((nx, ny), fields.dtype).T, interpolation='nearest', origin='lower', vmin=-1.1, vmax=1.1)
plt.colorbar()
# main loop
from datetime import datetime
t0 = datetime.now()
for tstep in xrange(1, tmax+1):
fields.update_e()
fields.update_h()
if tstep % tgap == 0:
print('[%s] %d/%d (%d %%)\r' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100)),
sys.stdout.flush()
getf.get_event().wait()
imag.set_array( getf.get_fields().T )
#plt.savefig('./png/%.6d.png' % tstep)
plt.draw()
plt.show()
print('\n[%s] %d/%d (%d %%)' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100))
print('')
getf.get_event().wait()
imag.set_array( getf.get_fields().T )
#plt.savefig('./png/%.6d.png' % tstep)
plt.draw()
'''
getf.get_event().wait()
# plot
import matplotlib.pyplot as plt
#plt.ion()
fig = plt.figure(figsize=(12,8))
imag = plt.imshow(np.zeros((ny, nz), fields.dtype).T, interpolation='nearest', origin='lower', vmin=-1.1, vmax=1.1)
plt.xlabel('y')
plt.ylabel('z')
plt.colorbar()
from matplotlib.patches import Rectangle
rects = [Rectangle((ny-npml, 0), npml, nz, alpha=0.1), \
Rectangle((0, 0), npml, nz, alpha=0.1), \
Rectangle((0, nz-npml), ny, npml, alpha=0.1), \
Rectangle((0, 0), ny, npml, alpha=0.1)]
for rect in rects:
plt.gca().add_patch(rect)
imag.set_array( getf.get_fields().T )
plt.show()
#plt.savefig('cpml.png')
print('\n[%s] %d/%d (%d %%)' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100))
print('')
vmin=0,
vmax=0.05)
plt.colorbar()
# Main loop
from datetime import datetime
t0 = datetime.now()
for tstep in xrange(1, tmax + 1):
qtask.enqueue(fdtd.update_e)
qtask.enqueue(src.update, [tstep])
qtask.enqueue(fdtd.update_h)
if tstep % tgap == 0:
with LockQueueTask(qtask):
f = output.get_fields()
print('[%s] %d/%d (%d %%)\r' %
(datetime.now() - t0, tstep, tmax, float(tstep) / tmax * 100)),
sys.stdout.flush()
imag.set_array(f.T**2)
plt.draw()
print('[%s] %d/%d (%d %%)' %
(datetime.now() - t0, tstep, tmax, float(tstep) / tmax * 100))
#imag.set_array(fdtd.ez[:,:,nz/5*4].T**2 )
#plt.savefig('./simple.png')
#plt.show()
print('')
