def new_method(self, other, prefix=prefix):
if not check_special_methods():
raise NotImplementedError, 'Special method %s called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%(op_name, str(self))
# This code will create one of two Deterministic objects.
if prefix == 'r':
# Right version: raises error on failure.
parents = {'self':self, 'other':other, 'op':'__r' + op_name + '__'}
def eval_fun(self,other,op):
out = getattr(self, op)(other)
if out is NotImplemented:
# the rt version has failed, meainng the lft version has failed as well.
raise TypeError, "unsupported operand type(s) for %s: '%s' and '%s'"%(op.replace('_',''), self.__class__.__name__, other.__class__.__name__)
return out
else:
# Left version: tries right version on failure.
parents = {'self':self, 'other':other, 'op':'__' + op_name + '__', 'rt_op': '__r'+op_name+'__'}
def eval_fun(self, other, op, rt_op):
out = getattr(self, op)(other)
if out is NotImplemented:
# if try the rt version.
out = getattr(other, rt_op)(self)
return out
return pm.Deterministic(eval_fun,
'A Deterministic returning the value of %s(%s,%s)'%(prefix+op_name,self.__name__, str(other)),
'('+'_'.join([self.__name__,prefix+op_name,str(other)])+')',
parents,
trace=False,
plot=False)
def __call__(self, *args, **kwargs):
if not check_special_methods():
raise NotImplementedError, 'Special method __call__ called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%str(self)
def eval_fun(self, args=args, kwargs=kwargs):
return self(*args, **kwargs)
return pm.Deterministic(eval_fun,
'A Deterministic returning the value of %s(*%s, **%s)'%(self.__name__, str(args), str(kwargs)),
self.__name__+'(*%s, **%s)'%(str(args), str(kwargs)),
{'self':self, 'args': args, 'kwargs': kwargs},
trace=False,
plot=False)
def new_method(self, other):
if not check_special_methods():
raise NotImplementedError, 'Special method %s called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%(op_name, str(self))
# This code creates a Deterministic object.
def eval_fun(self, other, op):
return getattr(self, op)(other)
return pm.Deterministic(eval_fun,
'A Deterministic returning the value of %s(%s,%s)'%(op_name,self.__name__, str(other)),
'('+'_'.join([self.__name__,op_name,str(other)])+')',
{'self':self, 'other':other, 'op':'__'+op_name+'__'},
trace=False,
plot=False)
def new_method(self):
# This code creates a Deterministic object.
if not check_special_methods():
raise NotImplementedError, 'Special method %s called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%(op_name, str(self))
jacobian_formats = {'self' : 'transformation_operation'}
return pm.Deterministic(op_function,
'A Deterministic returning the value of %s(%s)'%(op_name, self.__name__),
'('+op_name+'_'+self.__name__+')',
parents = {'self':self},
trace=False,
plot=False,
jacobians=jacobians,
jacobian_formats = jacobian_formats)
def __getitem__(self, index):
if not check_special_methods():
raise NotImplementedError, 'Special method __index__ called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%str(self)
# If index is number or number-valued variable, make an Index object
name = '%s[%s]'%(self.__name__, str(index))
if np.isscalar(value(index)):
if np.isreal(value(index)):
return Index(name, self, index, trace=False, plot=False)
# Otherwise make a standard Deterministic.
def eval_fun(self, index):
return self[index]
return pm.Deterministic(eval_fun,
'A Deterministic returning the value of %s[%s]'%(self.__name__, str(index)),
name,
{'self':self, 'index':index},
trace=False,
plot=False)
def new_method(self, other, prefix=prefix):
if not check_special_methods():
raise NotImplementedError, 'Special method %s called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%(op_name, str(self))
# This code will create one of two Deterministic objects.
if prefix == 'r':
parents = {'a':other, 'b':self}
else:
parents = {'a':self, 'b':other}
jacobian_formats = {'a' : 'broadcast_operation',
'b' : 'broadcast_operation'}
return pm.Deterministic(op_function,
'A Deterministic returning the value of %s(%s,%s)'%(prefix+op_name,self.__name__, str(other)),
'('+'_'.join([self.__name__,prefix+op_name,str(other)])+')',
parents,
trace=False,
plot=False,
jacobians = jacobians,
jacobian_formats = jacobian_formats)
def new_method(self, other, x_roles=x_roles, y_roles=y_roles):
if not check_special_methods():
raise NotImplementedError, 'Special method %s called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%(op_name, str(self))
x = []
y = []
for xr in x_roles:
if xr=='self':
x.append(self)
elif xr=='other':
x.append(other)
else:
x.append(xr)
for yr in y_roles:
if yr=='self':
y.append(self)
elif yr=='other':
y.append(other)
else:
y.append(yr)
# This code will create one of two Deterministic objects.
return LinearCombination('('+'_'.join([self.__name__,op_name,str(other)])+')', x, y, trace=False, plot=False)
def new_method(self, op=op):
if not check_special_methods():
raise NotImplementedError, 'Special method %s called on %s, but special methods have been disabled. Set pymc.special_methods_available to True to enable them.'%(op_name, str(self))
return op(self.value)