def DCoeff(*args, **kwargs):
class DCoeff(MatrixPhysCoefficient):
def __init__(self, *args, **kwargs):
self.conj = kwargs.pop('conj', False)
self.space_dim = args[0]
super(DCoeff, self).__init__(*args, **kwargs)
def EvalValue(self, x):
from petram.phys.phys_model import Coefficient_Evaluator
val = Coefficient_Evaluator.EvalValue(self, x)
val = np.diag(val)
if self.conj: val=np.conj(val)
return val
e = args[1]
if any([isinstance(ee, str) for ee in e]):
return DCoeff(*args, **kwargs)
else:
e = np.diag(e)
conj = kwargs.get('conj', False)
real = kwargs.get('real', True)
if np.iscomplexobj(e):
if conj: e = np.conj(e)
if real: e = e.real
else: e = e.imag
else:
e = np.array(e, dtype=float, copy=False)
return PhysMatrixConstant(e)
def DCoeff(dim, exprs, ind_vars, l, g, **kwargs):
if isinstance(exprs, str):
exprs = [exprs]
if isinstance(exprs, NativeCoefficientGenBase):
exprs = [exprs]
class DCoeff(MatrixPhysCoefficient):
def __init__(self, *args, **kwargs):
self.conj = kwargs.pop('conj', False)
self.scale = kwargs.pop('scale', 1.0)
self.space_dim = args[0]
super(DCoeff, self).__init__(*args, **kwargs)
def EvalValue(self, x):
from petram.phys.phys_model import Coefficient_Evaluator
val = Coefficient_Evaluator.EvalValue(self, x)
val = np.diag(val)
val = val * self.scale
if self.conj:
val = np.conj(val)
if np.iscomplexobj(val):
if self.real:
return val.real
else:
return val.imag
elif not self.real:
return val * 0.0
else:
return val
conj = kwargs.get('conj', False)
real = kwargs.get('real', True)
scale = kwargs.get('scale', 1.0)
#print("matrix exprs", exprs)
if any([isinstance(ee, str) for ee in exprs]):
return DCoeff(dim, exprs, ind_vars, l, g, **kwargs)
else:
e = exprs
if isinstance(e[0], NativeCoefficientGenBase):
return call_nativegen(e[0], l, g, real, conj, scale)
e = e * scale
e = np.diag(e)
if np.iscomplexobj(e):
if conj:
e = np.conj(e)
if real:
e = e.real
else:
e = e.imag
elif not real:
e = np.array(e * 0.0, dtype=float, copy=False)
else:
e = np.array(e, dtype=float, copy=False)
return PhysMatrixConstant(e)
def MCoeff(*args, **kwargs):
class MCoeff(MatrixPhysCoefficient):
def __init__(self, *args, **kwargs):
self.conj = kwargs.pop('conj', False)
super(MCoeff, self).__init__(*args, **kwargs)
def EvalValue(self, x):
val = super(MCoeff, self).EvalValue(x)
if self.conj: val=np.conj(val)
return val
e = args[1]
if any([isinstance(ee, str) for ee in e]):
return MCoeff(*args, **kwargs)
else:
conj = kwargs.get('conj', False)
real = kwargs.get('real', True)
if np.iscomplexobj(e):
if conj: e = np.conj(e)
if real: e = e.real
else: e = e.imag
else:
e = np.array(e, dtype=float, copy=False)
return PhysMatrixConstant(e)
def get_imag_coefficient(self):
return PhysMatrixConstant(self.value.imag)
def get_real_coefficient(self):
return PhysMatrixConstant(self.value.real)
def MCoeff(dim, exprs, ind_vars, l, g, return_complex=False, **kwargs):
if isinstance(exprs, str):
exprs = [exprs]
if isinstance(exprs, NativeCoefficientGenBase):
exprs = [exprs]
class MCoeff_Base(object):
def __init__(self, conj=False, scale=1.0):
self.conj = conj
self.scale = scale
def proc_value(self, val):
val = val * self.scale
if self.conj:
val = np.conj(val)
return val
class MCoeff(MatrixPhysCoefficient, MCoeff_Base):
def __init__(self,
sdim,
exprs,
ind_vars,
l,
g,
scale=1.0,
conj=False,
**kwargs):
MCoeff_Base.__init__(self, conj=conj, scale=scale)
MatrixPhysCoefficient.__init__(self, sdim, exprs, ind_vars, l, g,
**kwargs)
def EvalValue(self, x):
val = super(MCoeff, self).EvalValue(x)
val = self.proc_value(val)
if np.iscomplexobj(val):
if self.real:
return val.real
else:
return val.imag
elif not self.real:
return val * 0.0
else:
return val
class MCoeffCC(Coefficient_Evaluator, MCoeff_Base,
PyComplexMatrixCoefficient):
def __init__(self,
c1,
c2,
exprs,
ind_vars,
l,
g,
conj=False,
scale=1.0,
**kwargs):
MCoeff_Base.__init__(self, conj=conj, scale=scale)
# real is not used...
Coefficient_Evaluator.__init__(self,
exprs,
ind_vars,
l,
g,
real=True)
PyComplexMatrixCoefficient.__init__(self, c1, c2)
def Eval(self, K, T, ip):
for n, v in self.variables:
v.set_point(T, ip, self.g, self.l)
x = T.Transform(ip)
val = Coefficient_Evaluator.EvalValue(self, x)
val = val.reshape(self.height, self.width)
return self.proc_value(val)
conj = kwargs.get('conj', False)
real = kwargs.get('real', True)
scale = kwargs.get('scale', 1.0)
if any([isinstance(ee, str) for ee in exprs]):
if return_complex:
kwargs['real'] = True
c1 = MCoeff(dim, exprs, ind_vars, l, g, **kwargs)
kwargs['real'] = False
c2 = MCoeff(dim, exprs, ind_vars, l, g, **kwargs)
return MCoeffCC(c1, c2, exprs, ind_vars, l, g, **kwargs)
else:
return MCoeff(dim, exprs, ind_vars, l, g, **kwargs)
else:
e = exprs
if isinstance(e[0], NativeCoefficientGenBase):
if return_complex:
c1 = call_nativegen(e[0], l, g, True, conj, scale)
c2 = call_nativegen(e[0], l, g, False, conj, scale)
return complex_coefficient_from_real_and_imag(c1, c2)
else:
return call_nativegen(e[0], l, g, real, conj, scale)
e = np.array(e, copy=False).reshape(dim, dim)
e = e * scale
if conj:
e = np.conj(e)
if return_complex:
e = e.astype(complex)
return PyComplexMatrixConstant(e)
else:
if np.iscomplexobj(e):
if real:
e = e.real
else:
e = e.imag
elif not real:
e = np.array(e * 0.0, dtype=float, copy=False)
else:
e = np.array(e, dtype=float, copy=False)
return PhysMatrixConstant(e)