def _monitor_cpu_gpu(self, monitor1, monitor2, bunch1, bunch2):
'''
Test whether monitor.dump(bunch1/bunch2) works. Read the resulting
h5 files and compare (some) results
'''
params_to_check = [
'mean_x', 'sigma_dp', 'macroparticlenumber',
'n_macroparticles_per_slice'
]
for i in range(monitor2.n_steps):
bunch2.x += 1
bunch2.xp -= 0.1
bunch2.dp *= 0.97
monitor2.dump(bunch2)
res1 = self.read_h5_file(monitor2.filename + '.h5', params_to_check)
with GPU(bunch1) as device:
for i in range(monitor1.n_steps):
bunch1.x += 1
bunch1.xp -= 0.1
bunch1.dp *= 0.97
monitor1.dump(bunch1)
res2 = self.read_h5_file(monitor1.filename + '.h5', params_to_check)
for i in range(len(res1)):
self.assertTrue(
np.allclose(res1[i], res2[i]),
msg='.h5 file generated by monitor of CPU/GPU differ' +
str(params_to_check))
def _track_cpu_gpu(self, list_of_maps, bunch1, bunch2, nturns=1):
'''
Tracks both bunches through the list of maps (once GPU, once CPU)
and checks whether it yields the same result. Returns True/False.
Make sure bunch1, bunch2 are two identical objects (not one!)
Change the actual implementation of the GPU interface/strategy here
'''
# GPU
with GPU(bunch1) as device:
for n in range(nturns):
for m in list_of_maps:
m.track(bunch1)
# CPU
for n in range(nturns):
for m in list_of_maps:
m.track(bunch2)
#print bunch1.x
#print bunch2.x
# make sure the beam is sorted according to it's id to be able to compare them
# this is required since argsort for the slices is not unique
# (particles within slices can be permuted, gpu/cpu might be different!)
bunch1.sort_for('id')
bunch2.sort_for('id')
for att in bunch1.coords_n_momenta | set(['id']):
if not np.allclose(getattr(bunch1, att),
getattr(bunch2, att),
rtol=1.e-5,
atol=1.e-8):
return False
return True
def test_if_beam_is_numpy(self):
'''
Check if beam.x is a numpy array before and after the with statement
'''
bunch = self.create_all1_bunch()
self.assertTrue(self.check_if_npndarray(bunch),
msg='beam.x is not of type np.ndarray')
with GPU(bunch) as device:
foo = 1
self.assertTrue(self.check_if_npndarray(bunch),
msg='beam.x is not of type np.ndarray')