def eval_at_points(self, expr, solvars, phys):
from petram.helper.variables import Variable, var_g, NativeCoefficientGenBase, CoefficientVariable
variables = []
st = parser.expr(expr)
code = st.compile('<string>')
names = code.co_names
g = {}
#print solvars.keys()
for key in phys._global_ns.keys():
g[key] = phys._global_ns[key]
for key in solvars.keys():
g[key] = solvars[key]
ll_name = []
ll_value = []
var_g2 = var_g.copy()
new_names = []
name_translation = {}
for n in names:
if (n in g and isinstance(g[n], NativeCoefficientGenBase)):
g[n + "_coeff"] = CoefficientVariable(g[n], g)
new_names.append(n + "_coeff")
name_translation[n + "_coeff"] = n
if (n in g and isinstance(g[n], Variable)):
new_names.extend(g[n].dependency)
new_names.append(n)
name_translation[n] = n
elif n in g:
new_names.append(n)
name_translation[n] = n
for n in new_names:
if (n in g and isinstance(g[n], Variable)):
if not g[n] in self.knowns:
self.knowns[g[n]] = g[n].point_values(
counts=self.counts,
locs=self.locs,
attrs=self.masked_attrs,
elem_ids=self.elem_ids,
mesh=self.mesh()[self.emesh_idx],
int_points=self.int_points,
g=g,
knowns=self.knowns)
#ll[n] = self.knowns[g[n]]
ll_name.append(name_translation[n])
ll_value.append(self.knowns[g[n]])
elif (n in g):
var_g2[n] = g[n]
if len(ll_value) > 0:
val = np.array([
eval(code, var_g2, dict(zip(ll_name, v)))
for v in zip(*ll_value)
])
else:
# if expr does not involve Varialbe, evaluate code once
# and generate an array
val = np.array([eval(code, var_g2)] * len(self.locs))
return val
def __init__(self, exprs, ind_vars, l, g, real=True):
'''
this is complicated....
elemental (or array) form
[1,a,3] (a is namespace variable) is given as [[1, a (valued), 3]]
single box
1+1j is given as '(1+1j)' (string)
matrix
given as string like '[0, 1, 2, 3, 4]'
if variable is used it is become string element '['=variable', 1, 2, 3, 4]'
if =Varialbe in matrix form, it is passed as [['Variable']]
'''
flag, exprs = try_eval(exprs, l, g)
#print("after try_eval", flag, exprs)
if not flag:
if isinstance(exprs, str):
exprs = [exprs]
#elif isinstance(exprs, float):
# exprs = [exprs]
#elif isinstance(exprs, long):
# exprs = [exprs]
elif isinstance(exprs, numbers.Number):
exprs = [exprs]
else:
pass
if isinstance(exprs, list) and isinstance(exprs[0], list):
exprs = exprs[0]
#dprint1("final exprs", exprs)
self.l = {}
#### TODO g must be copied since some may passs _global_ns.
#### (I don't do it now since it requires a substantial testing)
self.g = g
for key in l.keys():
self.g[key] = l[key]
self.real = real
self.variables = []
self.co = []
for expr in exprs:
if isinstance(expr, str):
st = parser.expr(expr.strip())
code= st.compile('<string>')
names = code.co_names
for n in names:
if (n in g and isinstance(g[n], NativeCoefficientGenBase)):
coeff_var = CoefficientVariable(g[n], l, g)
self.variables.append((n, coeff_var))
elif n in g and isinstance(g[n], Variable):
self.variables.append((n, g[n]))
for nn in g[n].dependency:
self.variables.append((nn, g[nn]))
else:
pass
self.co.append(code)
else:
self.co.append(expr)
# 'x, y, z' -> 'x', 'y', 'z'
self.ind_vars = [x.strip() for x in ind_vars.split(',')]
self.exprs = exprs
self.flags = [isinstance(co, types.CodeType) for co in self.co]
self.variables_dd = dict(self.variables)
def eval_at_nodals(obj, expr, solvars, phys):
'''
evaluate nodal valus based on preproceessed
geometry data
to be done : obj should be replaced by a dictionary
'''
from petram.helper.variables import Variable, var_g, NativeCoefficientGenBase, CoefficientVariable
if len(obj.iverts) == 0: return None
variables = []
st = parser.expr(expr)
code = st.compile('<string>')
names = code.co_names
g = {}
for key in phys._global_ns.keys():
g[key] = phys._global_ns[key]
for key in solvars.keys():
g[key] = solvars[key]
ll_name = []
ll_value = []
var_g2 = var_g.copy()
new_names = []
name_translation = {}
for n in names:
if (n in g and isinstance(g[n], NativeCoefficientGenBase)):
g[n + "_coeff"] = CoefficientVariable(g[n], g)
new_names.append(n + "_coeff")
name_translation[n + "_coeff"] = n
if (n in g and isinstance(g[n], Variable)):
new_names.extend(g[n].dependency)
new_names.append(n)
name_translation[n] = n
elif n in g:
new_names.append(n)
name_translation[n] = n
for n in new_names:
if (n in g and isinstance(g[n], Variable)):
if not g[n] in obj.knowns:
obj.knowns[g[n]] = (g[n].nodal_values(
iele=obj.ieles,
ibele=obj.ibeles,
elattr=obj.elattr,
el2v=obj.elvert2facevert,
locs=obj.locs,
elvertloc=obj.elvertloc,
wverts=obj.wverts,
mesh=obj.mesh()[obj.emesh_idx],
iverts_f=obj.iverts_f,
g=g,
knowns=obj.knowns))
#ll[n] = self.knowns[g[n]]
ll_name.append(name_translation[n])
ll_value.append(obj.knowns[g[n]])
elif (n in g):
var_g2[n] = g[n]
if len(ll_value) > 0:
val = np.array([
eval(code, var_g2, dict(zip(ll_name, v))) for v in zip(*ll_value)
])
else:
# if expr does not involve Varialbe, evaluate code once
# and generate an array
val = np.array([eval(code, var_g2)] * len(obj.locs))
return val