def clone_without_expression_components(expr, substitute=None):
"""A function that is used to clone an expression.
Cloning is roughly equivalent to calling ``copy.deepcopy``.
However, the :attr:`clone_leaves` argument can be used to
clone only interior (i.e. non-leaf) nodes in the expression
tree. Note that named expression objects are treated as
leaves when :attr:`clone_leaves` is :const:`True`, and hence
those subexpressions are not cloned.
This function uses a non-recursive
logic, which makes it more scalable than the logic in
``copy.deepcopy``.
Args:
expr: The expression that will be cloned.
substitute (dict): A dictionary mapping object ids to
objects. This dictionary has the same semantics as
the memo object used with ``copy.deepcopy``. Defaults
to None, which indicates that no user-defined
dictionary is used.
Returns:
The cloned expression.
"""
if substitute is None:
substitute = {}
#
visitor = EXPR.ExpressionReplacementVisitor(substitute=substitute,
remove_named_expressions=True)
return visitor.dfs_postorder_stack(expr)
def grad_fd(c, scaled=False, h=1e-6):
"""Finite difference the gradient for a constraint, objective or named
expression. This is only for use in examining scaling. For faster more
accurate gradients refer to pynumero.
Args:
c: constraint to evaluate
scaled: if True calculate the scaled grad (default=False)
h: step size for calculating finite differnced derivatives
Returns:
(list of gradient values, list for varibles in the constraint) The order
of the variables coresoponds to the gradient values.
"""
try:
ex = c.body
except AttributeError:
ex = c.expr
vars = list(EXPR.identify_variables(ex))
grad = [None]*len(vars)
r = {}
if scaled: # If you want the scaled grad put in variable scaling tansform
orig = [pyo.value(v) for v in vars]
for i, v in enumerate(vars):
try:
sf = v.parent_block().scaling_factor.get(v, 1)
except AttributeError:
sf = 1
r[id(v)] = v/sf
v.value = orig[i]*sf
vis = EXPR.ExpressionReplacementVisitor(
substitute=r,
remove_named_expressions=True,
)
e = vis.dfs_postorder_stack(ex)
else:
e = ex
for i, v in enumerate(vars):
ov = pyo.value(v) # original variable value
f1 = pyo.value(e)
v.value = ov + h
f2 = pyo.value(e)
v.value = ov
if scaled:
try:
sf = c.parent_block().scaling_factor.get(c, 1)
except AttributeError:
sf = 1
grad[i] = sf*(f2 - f1)/h
else:
grad[i] = (f2 - f1)/h
if scaled:
for i, v in enumerate(vars):
v.value = orig[i]
return grad, vars
def replace(instance, substitute):
# Create the replacement dict. Do some argument validation and indexed
# var handling
d = {}
for r in substitute:
if not (_is_var(r[0]) and _is_var(r[1])):
raise TypeError(
"Replace only allows variables to be replaced, {} is type {}"
" and {} is type {}".format(r[0], type(r[0]), r[1],
type(r[1])))
if r[0].is_indexed() != r[1].is_indexed():
raise TypeError(
"IndexedVars must be replaced by IndexedVars, {} is type {}"
" and {} is type {}".format(r[0], type(r[0]), r[1],
type(r[1])))
if r[0].is_indexed() and r[1].is_indexed():
if not r[0].index_set().issubset(r[1].index_set()):
raise ValueError("The index set of {} must be a subset of"
" {}.".format(r[0], r[1]))
for i in r[0]:
d[id(r[0][i])] = r[1][i]
else:
#scalar replace
d[id(r[0])] = r[1]
# Replacement Visitor
vis = EXPR.ExpressionReplacementVisitor(
substitute=d,
descend_into_named_expressions=True,
remove_named_expressions=False,
)
# Do replacements in Expressions, Constraints, and Objectives
for c in instance.component_data_objects(
(Constraint, Expression, Objective),
descend_into=True,
active=True):
c.set_value(expr=vis.dfs_postorder_stack(c.expr))
def _apply_to(self, instance, max_iter=5, reversible=True):
"""
Apply the transformation. This is called by ``apply_to`` in the
superclass, and should not be called directly. ``apply_to`` takes the
same arguments.
Args:
instance: A block or model to apply the transformation to
Returns:
None
"""
self.reversible = reversible
if reversible:
self._instance = instance
self._all_subs = []
self._subs_map = {}
self._expr_map = {}
self._all_fixes = []
self._all_deactivate = []
self._original = {}
# The named expressions could be changed as a side effect of the
# constraint expression replacements, so for maximum saftey, just
# store all the expressions for Expressions
for c in instance.component_data_objects(
pyo.Expression,
descend_into=True,
):
self._original[id(c)] = c.expr
self._expr_map[id(c)] = c
nr_tot = 0
# repeat elimination until no more can be eliminated or hit max_iter
for i in range(max_iter):
subs, cnstr, fixes, subs_map = self._get_subs(instance)
if reversible:
self._all_fixes += fixes
self._all_deactivate += cnstr
self._all_subs.append(subs)
self._subs_map.update(subs_map)
nr = len(cnstr)
if nr == 0:
break
nr_tot += nr
for c in cnstr: # deactivate constraints that aren't needed
c.deactivate()
for v in fixes: # fix variables that can be fixed
v[0].fix(v[1])
# Do replacements in Expressions, Constraints, and Objectives
# where one var is replaced with a linear expression containing
# another
vis = EXPR.ExpressionReplacementVisitor(
substitute=subs,
descend_into_named_expressions=True,
remove_named_expressions=False,
)
for c in instance.component_data_objects(
(pyo.Constraint, pyo.Objective),
descend_into=True,
active=True
):
if id(c) not in self._original and reversible:
self._original[id(c)] = c.expr
self._expr_map[id(c)] = c
c.set_value(expr=vis.dfs_postorder_stack(c.expr))
_log.info("Eliminated {} variables and constraints".format(nr_tot))
def _replacement(m, basis):
"""PRIVATE FUNCTION
Create a replacement visitor. The replacement visitor is used on
user-provided scaling expressions. These expressions are written
with model variables, but you generally don't want to calculate
scaling factors based on the curent value of the model variables,
you want to use their scaling factors, so the replacment visitor
takes the user-defined scaling expression and replaces the model
varible by some scaling factor, and returns a new expression. The
basis argument can be used to specify the basis to use for scaling.
Args:
m (Block): model to collect vars from
basis (list of ScalingBasis): value type to use as basis for scaling calcs
Return:
None or ExpressionReplacementVisitor
"""
# These long ifs up front find values to replace variables in the scaling
# expressions with.
if basis[0] == ScalingBasis.Value:
return None # no need to replace anything if using value
else:
rdict = {}
for v in m.component_data_objects((pyo.Var)):
val = 1.0
for b in basis:
try:
if b == ScalingBasis.VarScale:
val = v.parent_block().scaling_factor[v]
break
elif b == ScalingBasis.InverseVarScale:
val = 1/v.parent_block().scaling_factor[v]
break
elif b == ScalingBasis.Value:
val = pyo.value(v)
break
elif b == ScalingBasis.Mid:
if v.lb is not None and v.ub is not None:
val = (v.ub + v.lb)/2.0
break
elif b == ScalingBasis.Lower:
if v.lb is not None:
val = v.lb
break
elif b == ScalingBasis.Upper:
if v.ub is not None:
val = v.ub
break
else:
_log.warning("Unknown scaling expression basis {}".format(b))
except AttributeError:
pass
except KeyError:
pass
rdict[id(v)] = val
for v in m.component_data_objects((pyo.Expression)):
# check for expression scaling factors, while expressions don't
# get scaled, the factor can be used in the calculation of other
# scale factors.
val = 1.0
for b in basis:
try:
if b == ScalingBasis.VarScale:
val = v.parent_block().scaling_factor[v]
break
elif b == ScalingBasis.InverseVarScale:
val = 1/v.parent_block().scaling_factor[v]
break
elif b == ScalingBasis.Value:
val = pyo.value(v)
break
else: # Expressions don't have bounds
continue
except AttributeError:
pass
except KeyError:
pass
rdict[id(v)] = val
# Use the substitutions dictionary from above to make a replacemnt visitor
return EXPR.ExpressionReplacementVisitor(substitute=rdict)
