def conditional(self, f): # TODO: Is this right? What about non-scalars?
c, a, b = f.operands()
s = f.shape()
ufl_assert(s == (), "TODO: Assuming scalar valued expressions.")
_0 = Zero()
_1 = IntValue(1)
da = conditional(c, _1, _0)
db = conditional(c, _0, _1)
return (None, da, db)
def conditional(self, o, c, t, f):
o = self.reuse_if_possible(o, c[0], t[0], f[0])
if isinstance(t[1], Zero) and isinstance(f[1], Zero):
tp = t[1] # Assuming t[1] and f[1] have the same indices here, which should be the case
fi = tp.free_indices()
fid = subdict(tp.index_dimensions(), fi)
op = Zero(tp.shape(), fi, fid)
else:
op = conditional(c[0], 1, 0)*t[1] + conditional(c[0], 0, 1)*f[1]
return (o, op)
def conditional(self, o, c, t, f):
o = self.reuse_if_possible(o, c[0], t[0], f[0])
if isinstance(t[1], Zero) and isinstance(f[1], Zero):
tp = t[
1] # Assuming t[1] and f[1] have the same indices here, which should be the case
fi = tp.free_indices()
fid = subdict(tp.index_dimensions(), fi)
op = Zero(tp.shape(), fi, fid)
else:
op = conditional(c[0], 1, 0) * t[1] + conditional(c[0], 0,
1) * f[1]
return (o, op)
def min_value(self, o, df, dg):
# d/dx min(f, g) =
# f < g: df/dx
# else: dg/dx
# Placing df,dg outside here to avoid getting arguments
# inside conditionals
f, g = o.ufl_operands
dc = conditional(f < g, 1, 0)
return dc * df + (1.0 - dc) * dg
def min_value(self, o, df, dg):
# d/dx min(f, g) =
# f < g: df/dx
# else: dg/dx
# Placing df,dg outside here to avoid getting arguments
# inside conditionals
f, g = o.ufl_operands
dc = conditional(f < g, 1, 0)
return dc*df + (1.0 - dc)*dg
def conditional(self, o, unused_dc, dt, df):
global CONDITIONAL_WORKAROUND
if isinstance(dt, Zero) and isinstance(df, Zero):
# Assuming dt and df have the same indices here, which
# should be the case
return dt
elif CONDITIONAL_WORKAROUND:
# Placing t[1],f[1] outside here to avoid getting
# arguments inside conditionals. This will fail when dt
# or df become NaN or Inf in floating point computations!
c = o.ufl_operands[0]
dc = conditional(c, 1, 0)
return dc * dt + (1.0 - dc) * df
else:
# Not placing t[1],f[1] outside, allowing arguments inside
# conditionals. This will make legacy ffc fail, but
# should work with uflacs.
c = o.ufl_operands[0]
return conditional(c, dt, df)
def conditional(self, o, unused_dc, dt, df):
global CONDITIONAL_WORKAROUND
if isinstance(dt, Zero) and isinstance(df, Zero):
# Assuming dt and df have the same indices here, which
# should be the case
return dt
elif CONDITIONAL_WORKAROUND:
# Placing t[1],f[1] outside here to avoid getting
# arguments inside conditionals. This will fail when dt
# or df become NaN or Inf in floating point computations!
c = o.ufl_operands[0]
dc = conditional(c, 1, 0)
return dc*dt + (1.0 - dc)*df
else:
# Not placing t[1],f[1] outside, allowing arguments inside
# conditionals. This will make legacy ffc fail, but
# should work with uflacs.
c = o.ufl_operands[0]
return conditional(c, dt, df)