def verify(s, pt0, pt1):
print('pt0 = %s, pt1 = %s' % (pt0, pt1))
slidx = s.get_slidx(pt0, pt1)
for strf in s.strf_list:
# non-spatial
fset = SetFields(s.fdtd, strf, pt0, pt1)
value = np.random.rand()
fset.set_fields(value)
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields(strf)
assert np.linalg.norm(value - 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(*fset.rplist['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 = s.get_slidx(pt0, pt1)
for strf in s.strf_list:
# non-spatial
fset = SetFields(s.fdtd, strf, pt0, pt1)
value = np.random.rand()
fset.set_fields(value)
fget = GetFields(s.fdtd, strf, pt0, pt1)
fget.get_event().wait()
copy = fget.get_fields(strf)
assert np.linalg.norm(value - 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(*fset.rplist['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 = s.get_slidx(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 = s.get_slidx(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 = self.args
slidx = common.slices_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
fields = Fields(0, nx, ny, nz, '', 'single')
getf = GetFields(fields, str_f, pt0, pt1)
# host allocations
ehs = common_random.generate_ehs(nx, ny, nz, fields.dtype)
eh_dict = dict( zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs) )
fields.set_eh_bufs(*ehs)
# verify
getf.wait()
for str_f in str_fs:
original = eh_dict[str_f][slidx]
copy = getf.get_fields(str_f)
norm = np.linalg.norm(original - copy)
self.assertEqual(norm, 0, '%s, %g' % (self.args, norm))
fields.context_pop()
def runTest(self):
nx, ny, nz, str_f, pt0, pt1 = self.args
slidx = common.slices_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
gpu_devices = common_gpu.gpu_device_list(print_info=False)
context = cl.Context(gpu_devices)
device = gpu_devices[0]
fields = Fields(context, device, nx, ny, nz, '', 'single')
getf = GetFields(fields, str_f, pt0, pt1)
# host allocations
ehs = common_random.generate_ehs(nx, ny, nz, fields.dtype)
eh_dict = dict( zip(['ex', 'ey', 'ez', 'hx', 'hy', 'hz'], ehs) )
fields.set_eh_bufs(*ehs)
# verify
getf.get_event().wait()
for str_f in str_fs:
original = eh_dict[str_f][slidx]
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
slidx = common.slice_index_two_points(pt0, pt1)
str_fs = common.convert_to_tuple(str_f)
# instance
gpu_devices = common_gpu.gpu_device_list(print_info=False)
context = cl.Context(gpu_devices)
device = gpu_devices[0]
fields = Fields(context, device, 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_eh_bufs(*ehs)
# verify
getf.get_event().wait()
for str_f in str_fs:
original = eh_dict[str_f][slidx]
copy = getf.get_fields(str_f)
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 = s.get_slidx(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 = s.get_slidx(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 = s.get_slidx(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 = s.get_slidx(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 = s.get_slidx(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 = s.get_slidx(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 = s.get_slidx(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 = s.get_slidx(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
# z-axis
nx, ny, nz = 180, 160, 2
fields = Fields(context, device, 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()
ax1 = fig.add_subplot(2, 3, 1)
getf = GetFields(fields, 'ey', (0, 0, nz/2), (nx-1, ny-1, nz/2))
getf.get_event().wait()
ax1.imshow(getf.get_fields().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)
getf = GetFields(fields, 'ex', (0, 0, nz/2), (nx-1, ny-1, nz/2))
getf.get_event().wait()
ax2.imshow(getf.get_fields().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
fields = Fields(context, device, nx, ny, nz)
gpu_id = 0
gpu_devices = common_gpu.get_gpu_devices()
context = cl.Context(gpu_devices)
device = gpu_devices[gpu_id]
fdtd = Fields(context, device, nx, ny, nz, coeff_use='')
src = DirectSrc(fdtd, 'ex', (1, ny / 5 * 4, nz / 5 * 3),
(1, ny / 5 * 4, nz / 5 * 3), lambda tstep: np.sin(0.1 * tstep))
pbc = PbcInt(fdtd, 'x')
output = GetFields(fdtd, 'ex', (1, 0, 0), (1, ny - 1, nz - 1))
# Plot
import matplotlib.pyplot as plt
plt.ion()
imag = plt.imshow(output.get_fields().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):
fdtd.update_e()
src.update(tstep)
pbc.update_e()
import pyopencl as cl
from kemp.fdtd3d import common_gpu
from kemp.fdtd3d.gpu import Fields, GetFields, Npml
nx, ny, nz = 100, 110, 128
gpu_id = 0
gpu_devices = common_gpu.get_gpu_devices()
context = cl.Context(gpu_devices)
device = gpu_devices[gpu_id]
fdtd = Fields(context, device, nx, ny, nz, coeff_use='')
fhosts = {}
pml = Npml(fdtd, -0.428571428571, 0.714285714286, 0.6, 0.2, 0.6, 0.2)
fhost = np.random.rand(nx, nz).astype(fdtd.dtype)
cl.enqueue_write_buffer(fdtd.queue, pml.pex, fhost)
pml.update_h()
fget = GetFields(fdtd, ['hz', 'hx'], (0, ny - 1, 0), (nx - 1, ny - 1, nz - 1))
fget.get_event().wait()
hz = fget.get_fields('hz')
hx = fget.get_fields('hx')
print fhost
print hz
print fhost.shape
print hz.shape
assert np.linalg.norm(fhost - hz) == 0
from datetime import datetime
from time import time, sleep
t0 = datetime.now()
t00 = time()
# main loop
for tstep in xrange(1, tmax + 1):
fields.update_e()
exch.update_e()
fields.update_h()
exch.update_h()
if tstep % 10 == 0 and is_plot:
getf.get_event().wait()
np.save('rank%d_%d' % (rank, tstep), getf.get_fields())
if is_master:
print(
'[%s] %d/%d (%d %%)\r' %
(datetime.now() - t0, tstep, tmax, float(tstep) / tmax * 100)),
sys.stdout.flush()
for i in range(size):
load_fail = True
while load_fail:
try:
arr[i * nx:(i + 1) * nx, :] = np.load('rank%d_%d.npy' %
(i, tstep))
load_fail = False
except:
tmax, tgap = 200, 10
gpu_id = 0
gpu_devices = common_gpu.get_gpu_devices()
context = cl.Context(gpu_devices)
device = gpu_devices[gpu_id]
fdtd = Fdtd(context, device, nx, ny, nz, coeff_use='')
src = DirectSrc(fdtd, 'ez', (nx/3*2, ny/2, 0), (nx/3*2, ny/2, nz-1), lambda tstep: np.sin(0.1 * tstep))
output = GetFields(fdtd, 'ez', (0, 0, nz/2), (nx-1, ny-1, nz/2))
# Plot
import matplotlib.pyplot as plt
plt.ion()
imag = plt.imshow(output.get_fields('ez').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):
fdtd.update_h()
fdtd.update_e()
src.update(tstep)
if tstep % tgap == 0:
print('[%s] %d/%d (%d %%)\r' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100)),
sys.stdout.flush()
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('')
import pyopencl as cl
from kemp.fdtd3d import common_gpu
from kemp.fdtd3d.gpu import Fields, GetFields, Npml
nx, ny, nz = 100, 110, 128
gpu_id = 0
gpu_devices = common_gpu.get_gpu_devices()
context = cl.Context(gpu_devices)
device = gpu_devices[gpu_id]
fdtd = Fields(context, device, nx, ny, nz, coeff_use='')
fhosts = {}
pml = Npml(fdtd, -0.428571428571, 0.714285714286, 0.6, 0.2, 0.6, 0.2)
fhost = np.random.rand(nx, nz).astype(fdtd.dtype)
cl.enqueue_write_buffer(fdtd.queue, pml.pex, fhost)
pml.update_h()
fget = GetFields(fdtd, ['hz','hx'], (0, ny-1, 0), (nx-1, ny-1, nz-1))
fget.get_event().wait()
hz = fget.get_fields('hz')
hx = fget.get_fields('hx')
print fhost
print hz
print fhost.shape
print hz.shape
assert np.linalg.norm(fhost - hz) == 0
gpu_devices = common_gpu.get_gpu_devices() context = cl.Context(gpu_devices) device = gpu_devices[gpu_id] fdtd = Fields(context, device, nx, ny, nz, coeff_use='') src_e = DirectSrc(fdtd, 'ex', (1, ny/5*4, nz/5*1), (1, ny/5*4, nz/5*1), lambda tstep: np.sin(0.1 * tstep)) pbc = PbcInt(fdtd, 'x') pml = Npml(fdtd, -0.428571428571, 0.714285714286, 0.6, 0.2, 0.6, 0.2) output = GetFields(fdtd, 'ex', (1, 0, 0), (1, ny-1, nz-1)) # Plot import matplotlib.pyplot as plt plt.ion() imag = plt.imshow(output.get_fields().T, cmap=plt.cm.hot, origin='lower', vmin=0, vmax=0.01) plt.colorbar() # Main loop from datetime import datetime t0 = datetime.now() for tstep in xrange(1, tmax+1): fdtd.update_e() src_e.update(tstep) pml.update_e() pbc.update_e() fdtd.update_h() pml.update_h()
# z-axis
nx, ny, nz = 180, 160, 2
fields = Fields(context, device, nx, ny, nz)
Pbc(fields, 'xyz')
Core(fields)
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()
ax1 = fig.add_subplot(2, 3, 1)
getf = GetFields(fields, 'ey', (0, 0, nz / 2), (nx - 1, ny - 1, nz / 2))
getf.get_event().wait()
ax1.imshow(getf.get_fields().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)
getf = GetFields(fields, 'ex', (0, 0, nz / 2), (nx - 1, ny - 1, nz / 2))
getf.get_event().wait()
ax2.imshow(getf.get_fields().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
fields = Fields(context, device, nx, ny, nz)
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('')
from datetime import datetime
from time import time, sleep
t0 = datetime.now()
t00 = time()
# main loop
for tstep in xrange(1, tmax+1):
fields.update_e()
exch.update_e()
fields.update_h()
exch.update_h()
if tstep % 10 == 0 and is_plot:
getf.get_event().wait()
np.save('rank%d_%d' % (rank, tstep), getf.get_fields())
if is_master:
print('[%s] %d/%d (%d %%)\r' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100)),
sys.stdout.flush()
for i in range(size):
load_fail = True
while load_fail:
try:
arr[i*nx:(i+1)*nx,:] = np.load('rank%d_%d.npy' % (i, tstep))
load_fail = False
except:
sleep(0.1)
imag.set_array(arr.T)
fig = plt.figure(figsize=(12,8))
#fig.add_subplot(1, 3, 1)
#imag = plt.imshow(np.zeros((nx, ny), fields.dtype).T, cmap=plt.cm.hot, origin='lower', vmin=0, vmax=0.05)
imag = plt.imshow(np.zeros((nx, ny), fields.dtype).T, interpolation='nearest', origin='lower', vmin=0, vmax=1.1)
plt.colorbar()
# main loop
from datetime import datetime
t0 = datetime.now()
for tstep in xrange(1, tmax+1):
fields.update_e()
vpbc.verify_e()
fields.update_h()
vpbc.verify_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( np.abs(getf.get_fields().T) )
#plt.savefig('./png/%.6d.png' % tstep)
plt.draw()
plt.show()
#getf.wait()
#print('\n[%s] %d/%d (%d %%)' % (datetime.now() - t0, tstep, tmax, float(tstep)/tmax*100))
print('')
