def __init__(self, **kwargs):
fn_in = kwargs['fn_model']
fn_out = kwargs['fn_out']
restart = kwargs['restart']
self.__draw_graph = kwargs.pop('draw_graph', False)
self.__rooted = kwargs.pop('rooted', False)
self.__pullback = kwargs.pop('pullback', False)
if self.__pullback:
self.__pullback_radius = kwargs['pullback_radius']
self.__pullback_r = np.zeros((3, ))
if fn_in is not None:
config = yamlio.read(fn_in)
self.create_mbs(config['bodies'], config['joints'])
if restart:
self.__fh_out = h5py.File(fn_out, 'a')
if 'ts' in self.__fh_out:
self.__h5cntr = len(self.__fh_out['ts'])
else:
self.__h5cntr = 0
else:
self.__fh_out = h5py.File(fn_out, 'w')
self.__h5cntr = 0
self.tofile(kwargs['time_start'])
def from_file(cls, fn):
'''
Read options from a file.
'''
raise NotImplementedError
options = yamlio.read(fn)
sop = cls()
sop.options.update(options)
return sop
def modeltraj_from_mbstraj(fn_mbstraj, fn_modeltraj, fn_model):
fh_traj = open(fn_modeltraj, 'wb')
modelspec = yamlio.read(fn_model)
mbstraj = MbsTrajectory(fn_mbstraj, fn_model)
nframes = len(mbstraj)
for k in range(nframes):
df_mbs = mbstraj.get_frame(k)
ec = EllipsoidChain.from_df_mbs(df_mbs, modelspec)
df_traj = ec.to_df_traj()
fh_traj.write(df_traj.tobytes())
mbstraj.close()
fh_traj.close()
def run(fn_options):
'''
options : dict
'''
options = yamlio.read(fn_options)
model = mbs.Mbs(**options['model'])
ffield = flowfield.create(**options['flowfield'])
hydrodyn = hydrodynamics.create(model, ffield, options['hydrodynamics'])
ts = timestepper.Timestepper(model, hydrodyn, ffield,
**options['timestepper'])
ts.run()
def create(cls, fn_traj, fn_model):
modelspec = yamlio.read(fn_model)
fh_traj = h5py.File(fn_traj, 'r+')
for key in fh_traj['ts']:
grp = fh_traj['ts/' + key]
if 'vertices' not in grp:
body_coms = grp['body_coms'][...]
body_oris = grp['body_orientations'][...]
df_mbs = {
'body_coms': body_coms,
'body_orientations': body_oris
}
ms = MiuraSheet.from_df_mbs(df_mbs, modelspec)
verts = grp.create_dataset('vertices', data=ms.verts)
grid_shape = np.array([ms.nverts_x, 1, ms.nverts_z],
dtype=np.int32)
verts.attrs['grid_shape'] = grid_shape
com = grp.create_dataset('com', data=ms.com)
fh_traj.close()
mst = cls(fn_traj, fn_model)
return mst
def __init__(self, fn_traj, fn_model):
self._modelspec = yamlio.read(fn_model)
self.nel = len(self._modelspec['bodies'])
dtype = np.dtype([('time', 'f8'), ('com', 'f8', (self.nel, 3)),
('ori', 'f8', (self.nel, 4))])
super(EllipsoidChainTrajectory, self).__init__(fn_traj, dtype)
def __init__(self, fn_traj, fn_model):
self._fh_traj = h5py.File(fn_traj, 'r')
self._modelspec = yamlio.read(fn_model)