def __call__( self, diff_var = None, chunk_size = None, **kwargs ):
force, virtual = self.get_args( **kwargs )
ap, vg = virtual.get_approximation( self.get_current_group(), 'Volume' )
n_el, n_qp, dim, n_ep = ap.get_v_data_shape( self.integral_name )
vdim = virtual.field.dim[0]
if diff_var is None:
shape = (chunk_size, 1, vdim * n_ep, 1)
mode = 0
else:
raise StopIteration
cache = self.get_cache( 'mat_in_qp', 0 )
mat = fix_scalar_constant( force, nm.float64 )
if mat is None:
mat = nm.asarray( force, dtype = nm.float64 )
if mat.ndim == 1:
mat = nm.ascontiguousarray( mat[...,nm.newaxis] )
else:
try:
mat = mat[...,nm.newaxis,nm.newaxis]
except TypeError: # Old numpy...
mat = nm.array( mat, ndmin = 2 )
mat_qp = cache( 'matqp', self.get_current_group(), 0,
mat = mat, ap = ap,
assumed_shapes = [(n_el, n_qp, vdim, 1)],
mode_in = None )
# print mat_qp
bf = ap.get_base( 'v', 0, self.integral_name )
for out, chunk in self.char_fun( chunk_size, shape ):
status = self.function( out, bf, mat_qp, vg, chunk )
yield out, chunk, status
def get_fargs( self, diff_var = None, chunk_size = None, **kwargs ):
mat, virtual, state = self.get_args( **kwargs )
ap, vg = virtual.get_approximation( self.get_current_group(), 'Volume' )
self.set_data_shape( ap )
shape, mode = self.get_shape( diff_var, chunk_size )
vec = self.get_vector( state )
mat_arg = fix_scalar_constant( mat, nm.float64 )
if mat_arg is None:
mat_arg = fix_scalar_in_el( mat, self.data_shape[0], nm.float64 )
self.function = terms.dw_st_pspg_p
else:
self.function = terms.dw_laplace
if state.is_real():
fargs = vec, 0, mat_arg, vg, ap.econn
else:
ac = nm.ascontiguousarray
fargs = [(ac( vec.real ), 0, mat_arg, vg, ap.econn),
(ac( vec.imag ), 0, mat_arg, vg, ap.econn)]
mode += 1j
return fargs, shape, mode