def _norm_2_op(discr, num_components):
from pytential import sym, bind
if num_components is not None:
from pymbolic.primitives import make_sym_vector
v = make_sym_vector("integrand", num_components)
integrand = sym.real(np.dot(sym.conj(v), v))
else:
integrand = sym.abs(sym.var("integrand"))**2
return bind(discr, sym.integral(discr.ambient_dim, discr.dim, integrand))
def _norm_inf_op(discr, num_components):
from pytential import sym, bind
if num_components is not None:
from pymbolic.primitives import make_sym_vector
v = make_sym_vector("arg", num_components)
max_arg = sym.abs(v)
else:
max_arg = sym.abs(sym.var("arg"))
return bind(discr, sym.NodeMax(max_arg))
def _norm_op(discr, num_components):
from pytential import sym, bind
if num_components is not None:
from pymbolic.primitives import make_sym_vector
v = make_sym_vector("integrand", num_components)
integrand = sym.real(np.dot(sym.conj(v), v))
else:
integrand = sym.abs(sym.var("integrand"))**2
return bind(discr, sym.integral(integrand))
def _norm_inf_op(discr, num_components):
from pytential import sym, bind
if num_components is not None:
from pymbolic.primitives import make_sym_vector
v = make_sym_vector("arg", num_components)
max_arg = sym.abs(v)
else:
max_arg = sym.abs(sym.var("arg"))
return bind(discr, sym.NodeMax(max_arg))
def map_num_reference_derivative(self, expr):
rec_operand = self.rec(expr.operand)
assert isinstance(rec_operand, np.ndarray)
if self.is_kind_matrix(rec_operand):
raise NotImplementedError("derivatives")
where_discr = self.places[expr.where]
op = sym.NumReferenceDerivative(expr.ref_axes, sym.var("u"))
return bind(where_discr, op)(
self.queue, u=cl.array.to_device(self.queue, rec_operand)).get()
def map_num_reference_derivative(self, expr):
rec_operand = self.rec(expr.operand)
assert isinstance(rec_operand, np.ndarray)
if self.is_kind_matrix(rec_operand):
raise NotImplementedError("derivatives")
rec_operand = cl.array.to_device(self.queue, rec_operand)
op = sym.NumReferenceDerivative(ref_axes=expr.ref_axes,
operand=sym.var("u"),
dofdesc=expr.dofdesc)
return bind(self.places, op)(self.queue, u=rec_operand).get()
def map_call(self, expr):
arg, = expr.parameters
rec_arg = self.rec(arg)
if isinstance(rec_arg, np.ndarray) and self.is_kind_matrix(rec_arg):
raise RuntimeError("expression is nonlinear in variable")
if isinstance(rec_arg, np.ndarray):
rec_arg = cl.array.to_device(self.queue, rec_arg)
op = expr.function(sym.var("u"))
result = bind(self.dep_source, op)(self.queue, u=rec_arg)
if isinstance(result, cl.array.Array):
result = result.get()
return result
def map_call(self, expr):
arg, = expr.parameters
rec_arg = self.rec(arg)
if isinstance(rec_arg, np.ndarray) and self.is_kind_matrix(rec_arg):
raise RuntimeError("expression is nonlinear in variable")
if isinstance(rec_arg, np.ndarray):
rec_arg = cl.array.to_device(self.queue, rec_arg)
op = expr.function(sym.var("u"))
result = bind(self.dep_source, op)(self.queue, u=rec_arg)
if isinstance(result, cl.array.Array):
result = result.get()
return result
def _integral_op(discr):
from pytential import sym, bind
return bind(
discr, sym.integral(discr.ambient_dim, discr.dim,
sym.var("integrand")))
def _integral_op(discr):
from pytential import sym, bind
return bind(discr, sym.integral(sym.var("integrand")))
def _integral_op(discr):
from pytential import sym, bind
return bind(discr,
sym.integral(
discr.ambient_dim, discr.dim, sym.var("integrand")))
