def _eval_term( self, sol, term, sops ):
"""Works for scalar, single unknown terms only!"""
expr = term.symbolic['expression']
arg_map = term.symbolic['map']
env = {'x' : sops.Symbol( 'x' ),
'y' : sops.Symbol( 'y' ),
'z' : sops.Symbol( 'z' ),
'dim' : dim}
for key, val in arg_map.iteritems():
if val == 'state':
env[key] = sol
else:
term.set_current_group(0)
env[key] = term.get_args( [val] )[0]
if 'material' in val:
# Take the first value - constant in all QPs.
aux = env[key][0,0]
if nm.prod( aux.shape ) == 1:
env[key] = aux.squeeze()
else:
import sympy
env[key] = sympy.Matrix( aux )
# print env
self.report( ' <= ', sol )
sops.set_dim( dim )
val = str( eval( expr, sops.__dict__, env ) )
self.report( ' =>', val )
return val
def _eval_term( self, sol, term, sops ):
"""Works for scalar, single unknown terms only!"""
expr = term.symbolic['expression']
arg_map = term.symbolic['map']
env = {'x' : sops.Symbol( 'x' ),
'y' : sops.Symbol( 'y' ),
'z' : sops.Symbol( 'z' ),
'dim' : dim}
for key, val in arg_map.iteritems():
if val == 'state':
env[key] = sol
else:
term.set_current_group(0)
env[key] = term.get_args( [val] )[0]
if 'material' in val:
# Take the first value - constant in all QPs.
aux = env[key][0,0]
if nm.prod( aux.shape ) == 1:
env[key] = aux.squeeze()
else:
import sympy
env[key] = sympy.Matrix( aux )
# print env
self.report( ' <= ', sol )
sops.set_dim( dim )
val = str( eval( expr, sops.__dict__, env ) )
self.report( ' =>', val )
return val
def _eval_term( self, sol, term, args, sops ):
"""Works for scalar, single unknown terms only!"""
expr = term.symbolic['expression']
arg_map = term.symbolic['map']
env = {'x' : sops.Symbol( 'x' ),
'y' : sops.Symbol( 'y' ),
'z' : sops.Symbol( 'z' ),
'dim' : dim}
for key, val in arg_map.iteritems():
if val == 'state':
env[key] = sol
else:
env[key] = term.get_args( [val], **args )[0]
if val[:8] == 'material':
aux = nm.array( env[key] )
if nm.prod( aux.shape ) == 1:
env[key] = aux.squeeze()
else:
import sympy
env[key] = sympy.Matrix( aux )
# print env
self.report( ' <= ', sol )
sops.set_dim( dim )
val = str( eval( expr, sops.__dict__, env ) )
self.report( ' =>', val )
return val
