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):
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):
ufunc, nx, ny, nz, coeff_use, precision_float, tmax = self.args
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, coeff_use, precision_float)
core = Core(fields)
# allocations
ns = fields.ns
dtype = fields.dtype
strf_list = ["ex", "ey", "ez", "hx", "hy", "hz"]
ehs = common_update.generate_random_ehs(nx, ny, nz, dtype, ufunc)
fields.set_eh_bufs(*ehs)
ces, chs = common_update.generate_random_cs(coeff_use, nx, ny, nz, dtype)
if "e" in coeff_use:
fields.set_ce_bufs(*ces)
if "h" in coeff_use:
fields.set_ch_bufs(*chs)
tmpf = np.zeros(fields.ns_pitch, dtype=dtype)
# update
if ufunc == "e":
for tstep in xrange(0, tmax):
fields.update_e()
common_update.update_e(ehs, ces)
for strf, eh in zip(strf_list, ehs)[:3]:
cl.enqueue_copy(fields.queue, tmpf, fields.get_buf(strf))
norm = np.linalg.norm(eh - tmpf[:, :, fields.slice_z])
max_diff = np.abs(eh - tmpf[:, :, fields.slice_z]).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(tmpf[:, :, -fields.pad :])
else:
norm2 = np.linalg.norm(tmpf[:, :, -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)
for strf, eh in zip(strf_list, ehs)[3:]:
cl.enqueue_copy(fields.queue, tmpf, fields.get_buf(strf))
norm = np.linalg.norm(eh - tmpf[:, :, fields.slice_z])
max_diff = np.abs(eh - tmpf[:, :, fields.slice_z]).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(tmpf[:, :, -fields.pad :])
else:
norm2 = np.linalg.norm(tmpf[:, :, -fields.pad :])
self.assertEqual(norm2, 0, "%s, %s, %g, padding" % (self.args, strf, norm2))
def runTest(self):
ufunc, nx, ny, nz, coeff_use, precision_float, tmax = self.args
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, coeff_use,
precision_float)
core = Core(fields)
# allocations
ns = fields.ns
dtype = fields.dtype
strf_list = ['ex', 'ey', 'ez', 'hx', 'hy', 'hz']
ehs = common_update.generate_random_ehs(nx, ny, nz, dtype, ufunc)
fields.set_eh_bufs(*ehs)
ces, chs = common_update.generate_random_cs(coeff_use, nx, ny, nz,
dtype)
if 'e' in coeff_use:
fields.set_ce_bufs(*ces)
if 'h' in coeff_use:
fields.set_ch_bufs(*chs)
tmpf = np.zeros(fields.ns_pitch, dtype=dtype)
# update
if ufunc == 'e':
for tstep in xrange(0, tmax):
fields.update_e()
common_update.update_e(ehs, ces)
for strf, eh in zip(strf_list, ehs)[:3]:
cl.enqueue_copy(fields.queue, tmpf, fields.get_buf(strf))
norm = np.linalg.norm(eh - tmpf[:, :, fields.slice_z])
max_diff = np.abs(eh - tmpf[:, :, fields.slice_z]).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(tmpf[:, :, -fields.pad:])
else:
norm2 = np.linalg.norm(tmpf[:, :, -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)
for strf, eh in zip(strf_list, ehs)[3:]:
cl.enqueue_copy(fields.queue, tmpf, fields.get_buf(strf))
norm = np.linalg.norm(eh - tmpf[:, :, fields.slice_z])
max_diff = np.abs(eh - tmpf[:, :, fields.slice_z]).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(tmpf[:, :, -fields.pad:])
else:
norm2 = np.linalg.norm(tmpf[:, :, -fields.pad:])
self.assertEqual(
norm2, 0,
'%s, %s, %g, padding' % (self.args, strf, norm2))