def set_current_group(self, ig):
"""
Set current group for the term and all variables in its
arguments.
"""
self.char_fun.set_current_group(ig)
shape_kind = get_shape_kind(self.integration)
for var in self.get_variables():
geo, geo_key, geo_ig = self.get_geometry(var)
var.setup_bases(geo_key, geo_ig, geo, self.integral, shape_kind)
var.set_current_group(geo_key, geo_ig)
def set_current_group(self, ig):
"""
Set current group for the term and all variables in its
arguments.
"""
self.char_fun.set_current_group(ig)
shape_kind = get_shape_kind(self.integration)
for var in self.get_variables():
geo, geo_key, geo_ig = self.get_geometry(var)
var.setup_bases(geo_key, geo_ig, geo, self.integral, shape_kind)
var.set_current_group(geo_key, geo_ig)
def integrate(self, val_qp, variable):
shape_kind = get_shape_kind(self.integration)
geo, _, _ = self.get_geometry(variable)
sh = val_qp.shape
val = nm.zeros((sh[0], 1, sh[2], sh[3]), dtype=val_qp.dtype)
if shape_kind == 'volume':
geo.integrate(val, val_qp)
else:
geo.integrate(val, val_qp)
return val
def integrate(self, val_qp, variable):
shape_kind = get_shape_kind(self.integration)
geo, _, _ = self.get_geometry(variable)
sh = val_qp.shape
val = nm.zeros((sh[0], 1, sh[2], sh[3]), dtype=val_qp.dtype)
if shape_kind == 'volume':
geo.integrate(val, val_qp)
else:
geo.integrate(val, val_qp)
return val
def integrate(self, val_qp, variable):
shape_kind = get_shape_kind(self.integration)
geo, _, _ = self.get_geometry(variable)
sh = val_qp.shape
val = nm.zeros((sh[0], 1, sh[2], sh[3]), dtype=val_qp.dtype)
if shape_kind == 'volume':
chunk = self.region.cells[self.char_fun.ig]
chunk = nm.arange(sh[0], dtype=nm.int32)
geo.integrate_chunk(val, val_qp, chunk)
else:
lchunk = nm.arange(sh[0], dtype=nm.int32)
geo.integrate_chunk(val, val_qp, lchunk)
return val
def evaluate(self, mode='eval', diff_var=None, **kwargs):
shape_kind = get_shape_kind(self.integration)
if mode == 'eval':
var = self.get_variables()[0]
val = 0.0
for ig in self.iter_groups():
args = self.get_args(**kwargs)
val_qp = self(*args, **kwargs)
_val = self.integrate(val_qp, var)
val += self.sign * _val.sum()
elif mode in ('el_avg', 'qp'):
raise NotImplementedError()
elif mode == 'weak':
varr = self.get_virtual_variable()
vals = []
iels = []
if diff_var is None:
for ig in self.iter_groups():
args = self.get_args(**kwargs)
aux = varr.get_data_shape(ig, self.integral, shape_kind,
self.region.name)
n_elr, n_qpr, dim, n_enr, n_cr = aux
n_row = n_cr * n_enr
shape = (n_elr, 1, n_row, 1)
val = nm.zeros(shape, dtype=varr.dtype)
for ir in varr.iter_dofs():
irs = slice(ir, ir + 1)
try:
val_qp = self(*args, **kwargs)
except ValueError:
output('%s term evaluation failed!' % self.name)
raise
_val = self.integrate(val_qp, varr)
val[..., irs, :] = _val
vals.append(self.sign * val)
iels.append((ig, nm.arange(n_elr, dtype=nm.int32)))
else:
varc = self.get_variables(as_list=False)[diff_var]
for ig in self.iter_groups():
args = self.get_args(**kwargs)
aux = varr.get_data_shape(ig, self.integral, shape_kind,
self.region.name)
n_elr, n_qpr, dim, n_enr, n_cr = aux
n_row = n_cr * n_enr
aux = varc.get_data_shape(ig, self.integral, shape_kind,
self.region.name)
n_elc, n_qpc, dim, n_enc, n_cc = aux
n_col = n_cc * n_enc
shape = (n_elr, 1, n_row, n_col)
val = nm.zeros(shape, dtype=varr.dtype)
for ir in varr.iter_dofs():
irs = slice(ir, ir + 1)
for ic in varc.iter_dofs():
ics = slice(ic, ic + 1)
try:
val_qp = self(*args, **kwargs)
except ValueError:
output('%s term evaluation failed!' %
self.name)
raise
_val = self.integrate(val_qp, varr)
val[..., irs, ics] = _val
vals.append(self.sign * val)
iels.append((ig, nm.arange(n_elr, dtype=nm.int32)))
# Setup return value.
if mode == 'eval':
out = (val, )
else:
out = (vals, iels)
# Hack: add zero status.
out = out + (0, )
if len(out) == 1:
out = out[0]
return out
def evaluate(self, mode='eval', diff_var=None, **kwargs):
shape_kind = get_shape_kind(self.integration)
if mode == 'eval':
var = self.get_variables()[0]
val = 0.0
for ig in self.iter_groups():
args = self.get_args(**kwargs)
val_qp = self(*args, **kwargs)
_val = self.integrate(val_qp, var)
val += self.sign * _val.sum()
elif mode in ('el_avg', 'qp'):
raise NotImplementedError()
elif mode == 'weak':
varr = self.get_virtual_variable()
vals = []
iels = []
if diff_var is None:
for ig in self.iter_groups():
args = self.get_args(**kwargs)
aux = varr.get_data_shape(ig, self.integral,
shape_kind, self.region.name)
n_elr, n_qpr, dim, n_enr, n_cr = aux
n_row = n_cr * n_enr
shape = (n_elr, 1, n_row, 1)
val = nm.zeros(shape, dtype=varr.dtype)
for ir in varr.iter_dofs():
irs = slice(ir, ir + 1)
try:
val_qp = self(*args, **kwargs)
except ValueError:
output('%s term evaluation failed!' % self.name)
raise
_val = self.integrate(val_qp, varr)
val[..., irs, :] = _val
vals.append(self.sign * val)
iels.append((ig, nm.arange(n_elr, dtype=nm.int32)))
else:
varc = self.get_variables(as_list=False)[diff_var]
for ig in self.iter_groups():
args = self.get_args(**kwargs)
aux = varr.get_data_shape(ig, self.integral,
shape_kind, self.region.name)
n_elr, n_qpr, dim, n_enr, n_cr = aux
n_row = n_cr * n_enr
aux = varc.get_data_shape(ig, self.integral,
shape_kind, self.region.name)
n_elc, n_qpc, dim, n_enc, n_cc = aux
n_col = n_cc * n_enc
shape = (n_elr, 1, n_row, n_col)
val = nm.zeros(shape, dtype=varr.dtype)
for ir in varr.iter_dofs():
irs = slice(ir, ir + 1)
for ic in varc.iter_dofs():
ics = slice(ic, ic + 1)
try:
val_qp = self(*args, **kwargs)
except ValueError:
output('%s term evaluation failed!' % self.name)
raise
_val = self.integrate(val_qp, varr)
val[..., irs, ics] = _val
vals.append(self.sign * val)
iels.append((ig, nm.arange(n_elr, dtype=nm.int32)))
# Setup return value.
if mode == 'eval':
out = (val,)
else:
out = (vals, iels)
# Hack: add zero status.
out = out + (0,)
if len(out) == 1:
out = out[0]
return out
