def at(self, var_and_param_names_and_values={}, **kw_var_and_param_names_and_values):
var_and_param_names_and_values =\
combine_dict_and_kwargs(var_and_param_names_and_values, kw_var_and_param_names_and_values)
cond = deepcopy(self.Cond) # just to be careful
scope = deepcopy(self.Scope) # just to be careful
param = self.Param.copy()
syms_and_values = {}
for var, value in list(var_and_param_names_and_values.items()):
if var in self.Vars:
if var in cond:
cond[var] = value
if var in scope:
scope[var] = value
syms_and_values[self.Vars[var]] = value
if var in param:
try:
syms_and_values[param[var]] = value
except:
pass
param[var] = value
cond = sympy_xreplace(cond, syms_and_values)
scope = sympy_xreplace(scope, syms_and_values)
self.CompyledFunc = None # remove compiled version because many things can be changing
if self.is_discrete_finite():
neg_log_p = {}
s = set(var_and_param_names_and_values)
s_items = set(var_and_param_names_and_values.items())
for var_values___frozen_dict, mapping_value in list(param['NegLogP'].items()):
other_items___dict = dict(set(var_values___frozen_dict.items()) - s_items)
if not (set(other_items___dict) & s):
neg_log_p[frozendict(set(var_values___frozen_dict.items()) - set(cond.items()))] =\
sympy_xreplace(mapping_value, syms_and_values)
return DiscreteFinitePMF(var_names_and_syms=self.Vars.copy(), p_or_neg_log_p=neg_log_p, p=False,
cond=cond, scope=scope)
else:
pdf = self.copy()
pdf.Cond = cond
pdf.Scope = scope
pdf.Param = sympy_xreplace(param, syms_and_values)
#print(pdf.Mapping)
#print(syms_and_values)
#print(type(syms_and_values.keys().pop()))
pdf.Mapping = sympy_xreplace(pdf.Mapping, syms_and_values)
return pdf
def at(self, var_and_param_names_and_values={}, **kw_var_and_param_names_and_values):
var_and_param_names_and_values =\
combine_dict_and_kwargs(var_and_param_names_and_values, kw_var_and_param_names_and_values)
cond = deepcopy(self.Cond) # just to be careful
scope = deepcopy(self.Scope) # just to be careful
param = self.Param.copy()
syms_and_values = {}
for var, value in var_and_param_names_and_values.items():
if var in self.Vars:
if var in cond:
cond[var] = value
if var in scope:
scope[var] = value
syms_and_values[self.Vars[var]] = value
if var in param:
try:
syms_and_values[param[var]] = value
except:
pass
param[var] = value
cond = sympy_xreplace(cond, syms_and_values)
scope = sympy_xreplace(scope, syms_and_values)
self.CompyledFunc = None # remove compiled version because many things can be changing
if self.is_discrete_finite():
neg_log_p = {}
s = set(var_and_param_names_and_values)
s_items = set(var_and_param_names_and_values.items())
for var_values___frozen_dict, mapping_value in param['NegLogP'].items():
other_items___dict = dict(set(var_values___frozen_dict.items()) - s_items)
if not (set(other_items___dict) & s):
neg_log_p[frozendict(set(var_values___frozen_dict.items()) - set(cond.items()))] =\
sympy_xreplace(mapping_value, syms_and_values)
return DiscreteFinitePMF(var_names_and_syms=self.Vars.copy(), p_or_neg_log_p=neg_log_p, p=False,
cond=cond, scope=scope)
else:
pdf = self.copy()
pdf.Cond = cond
pdf.Scope = scope
pdf.Param = sympy_xreplace(param, syms_and_values)
#print(pdf.Mapping)
#print(syms_and_values)
#print(type(syms_and_values.keys().pop()))
pdf.Mapping = sympy_xreplace(pdf.Mapping, syms_and_values)
return pdf
def gauss_neg_log_dens(pdf, var_and_param_names_and_values={}, **kw_var_and_param_names_and_values):
var_and_param_names_and_values = combine_dict_and_kwargs(var_and_param_names_and_values,
kw_var_and_param_names_and_values)
if not pdf.PreProcessed:
pdf.preprocess()
if pdf.LogDetCov is None:
neg_log_dens = (pdf.NumDims * log(2 * pi) + log(det(pdf.Cov)) +
det(pdf.DemeanedVarVector * pdf.Cov.inverse() * pdf.DemeanedVarVector.T)) / 2
else:
neg_log_dens = (pdf.NumDims * log(2 * pi) + pdf.LogDetCov +
det(pdf.DemeanedVarVector * Matrix(pdf.InvCov) * pdf.DemeanedVarVector.T)) / 2
return sympy_xreplace(neg_log_dens, var_and_param_names_and_values)
def gauss_neg_log_dens(pdf, var_and_param_names_and_values={}, **kw_var_and_param_names_and_values):
var_and_param_names_and_values = combine_dict_and_kwargs(var_and_param_names_and_values,
kw_var_and_param_names_and_values)
if not pdf.PreProcessed:
pdf.preprocess()
if pdf.LogDetCov is None:
neg_log_dens = (pdf.NumDims * log(2 * pi) + log(det(pdf.Cov)) +
det(pdf.DemeanedVarVector * pdf.Cov.inverse() * pdf.DemeanedVarVector.T)) / 2
else:
neg_log_dens = (pdf.NumDims * log(2 * pi) + pdf.LogDetCov +
det(pdf.DemeanedVarVector * Matrix(pdf.InvCov) * pdf.DemeanedVarVector.T)) / 2
return sympy_xreplace(neg_log_dens, var_and_param_names_and_values)
def discrete_finite_neg_log_mass(pmf, var_names_and_values={}):
v = var_names_and_values.copy()
for var, value in list(var_names_and_values.items()):
if (value is None) or is_non_atomic_sympy_expr(value):
del v[var]
s0 = set(v.items())
d = MathDict(())
for var_names_and_values___frozen_dict, func_value in list(pmf.Param['NegLogP'].items()):
spare_var_values = dict(s0 - set(var_names_and_values___frozen_dict.items()))
s = set(spare_var_values.keys())
if not(s) or (s and not(s & set(var_names_and_values___frozen_dict))):
d[var_names_and_values___frozen_dict] = sympy_xreplace(func_value, var_names_and_values)
return d
def discrete_finite_neg_log_mass(pmf, var_names_and_values={}):
v = var_names_and_values.copy()
for var, value in var_names_and_values.items():
if (value is None) or is_non_atomic_sympy_expr(value):
del v[var]
s0 = set(v.items())
d = MathDict(())
for var_names_and_values___frozen_dict, func_value in pmf.Param['NegLogP'].items():
spare_var_values = dict(s0 - set(var_names_and_values___frozen_dict.items()))
s = set(spare_var_values.keys())
if not(s) or (s and not(s & set(var_names_and_values___frozen_dict))):
d[var_names_and_values___frozen_dict] = sympy_xreplace(func_value, var_names_and_values)
return d
def at(self, vars_and_values___dict={}, **kw_vars_and_values___dict):
vars_and_values___dict = combine_dict_and_kwargs(vars_and_values___dict, kw_vars_and_values___dict)
for var in (set(self.Vars) & set(vars_and_values___dict)):
vars_and_values___dict[self.Vars[var]] = vars_and_values___dict[var]
conds = self.Cond.copy()
scope = self.Scope.copy()
for var, value in vars_and_values___dict.items():
if var in conds:
conds.update({var: value})
if var in scope:
scope.update({var: value})
conds = sympy_xreplace(conds, vars_and_values___dict)
scope = sympy_xreplace(scope, vars_and_values___dict)
if hasattr(self.Mapping, 'keys'):
mapping = {}
for vars_and_values___frozen_dict, func_value in self.Mapping.items():
other_items___dict = dict(set(vars_and_values___frozen_dict.items()) -
set(vars_and_values___dict.items()))
if not (set(other_items___dict) and set(vars_and_values___dict)):
mapping[frozendict(set(vars_and_values___frozen_dict.items()) - set(conds.items()))] =\
sympy_xreplace(func_value, vars_and_values___dict)
else:
mapping = sympy_xreplace(self.Mapping, vars_and_values___dict)
return MathFunc(self.Vars.copy(), mapping, cond=conds, scope=scope)
