# Source code for pyomo.dae.diffvar

```
# ___________________________________________________________________________
#
# Pyomo: Python Optimization Modeling Objects
# Copyright (c) 2008-2024
# National Technology and Engineering Solutions of Sandia, LLC
# Under the terms of Contract DE-NA0003525 with National Technology and
# Engineering Solutions of Sandia, LLC, the U.S. Government retains certain
# rights in this software.
# This software is distributed under the 3-clause BSD License.
# ___________________________________________________________________________
import weakref
from pyomo.common.collections import ComponentMap
from pyomo.core.base.component import ModelComponentFactory
from pyomo.core.base.set import UnknownSetDimen
from pyomo.core.base.var import Var
from pyomo.dae.contset import ContinuousSet
def create_access_function(var):
"""
This method returns a function that returns a component by calling
it rather than indexing it
"""
def _fun(*args):
return var[args]
return _fun
class DAE_Error(Exception):
"""Exception raised while processing DAE Models"""
[docs]@ModelComponentFactory.register("Derivative of a Var in a DAE model.")
class DerivativeVar(Var):
"""
Represents derivatives in a model and defines how a
:py:class:`Var<pyomo.environ.Var>` is differentiated
The :py:class:`DerivativeVar <pyomo.dae.DerivativeVar>` component is
used to declare a derivative of a :py:class:`Var <pyomo.environ.Var>`.
The constructor accepts a single positional argument which is the
:py:class:`Var<pyomo.environ.Var>` that's being differentiated. A
:py:class:`Var <pyomo.environ.Var>` may only be differentiated with
respect to a :py:class:`ContinuousSet<pyomo.dae.ContinuousSet>` that it
is indexed by. The indexing sets of a :py:class:`DerivativeVar
<pyomo.dae.DerivativeVar>` are identical to those of the :py:class:`Var
<pyomo.environ.Var>` it is differentiating.
Parameters
----------
sVar : ``pyomo.environ.Var``
The variable being differentiated
wrt : ``pyomo.dae.ContinuousSet`` or tuple
Equivalent to `withrespectto` keyword argument. The
:py:class:`ContinuousSet<pyomo.dae.ContinuousSet>` that the
derivative is being taken with respect to. Higher order derivatives
are represented by including the
:py:class:`ContinuousSet<pyomo.dae.ContinuousSet>` multiple times in
the tuple sent to this keyword. i.e. ``wrt=(m.t, m.t)`` would be the
second order derivative with respect to ``m.t``
"""
# Private Attributes:
# _stateVar The :class:`Var` being differentiated
# _wrt A list of the :class:`ContinuousSet` components the
# derivative is being taken with respect to
# _expr An expression representing the discretization equations
# linking the :class:`DerivativeVar` to its state :class:`Var`.
def __init__(self, sVar, **kwds):
if not isinstance(sVar, Var):
raise DAE_Error(
"%s is not a variable. Can only take the derivative of a Var"
"component." % sVar
)
if "wrt" in kwds and "withrespectto" in kwds:
raise TypeError(
"Cannot specify both 'wrt' and 'withrespectto keywords "
"in a DerivativeVar"
)
wrt = kwds.pop('wrt', None)
wrt = kwds.pop('withrespectto', wrt)
try:
num_contset = len(sVar._contset)
except AttributeError:
# This dictionary keeps track of where the ContinuousSet appears
# in the index. This implementation assumes that every element
# in an indexing set has the same dimension.
sVar._contset = ComponentMap()
sVar._derivative = {}
if sVar.dim() == 0:
num_contset = 0
else:
sidx_sets = list(sVar.index_set().subsets())
loc = 0
for i, s in enumerate(sidx_sets):
if s.ctype is ContinuousSet:
sVar._contset[s] = loc
_dim = s.dimen
if _dim is None:
raise DAE_Error(
"The variable %s is indexed by a Set (%s) with a "
"non-fixed dimension. A DerivativeVar may only be "
"indexed by Sets with constant dimension" % (sVar, s.name)
)
elif _dim is UnknownSetDimen:
raise DAE_Error(
"The variable %s is indexed by a Set (%s) with an "
"unknown dimension. A DerivativeVar may only be "
"indexed by Sets with known constant dimension"
% (sVar, s.name)
)
loc += s.dimen
num_contset = len(sVar._contset)
if num_contset == 0:
raise DAE_Error(
"The variable %s is not indexed by any ContinuousSets. A "
"derivative may only be taken with respect to a continuous "
"domain" % sVar
)
if wrt is None:
# Check to be sure Var is indexed by single ContinuousSet and take
# first deriv wrt that set
if num_contset != 1:
raise DAE_Error(
"The variable %s is indexed by multiple ContinuousSets. "
"The desired ContinuousSet must be specified using the "
"keyword argument 'wrt'" % sVar
)
wrt = [next(iter(sVar._contset.keys()))]
elif type(wrt) is ContinuousSet:
if wrt not in sVar._contset:
raise DAE_Error(
"Invalid derivative: The variable %s is not indexed by "
"the ContinuousSet %s" % (sVar, wrt)
)
wrt = [wrt]
elif type(wrt) is tuple or type(wrt) is list:
for i in wrt:
if type(i) is not ContinuousSet:
raise DAE_Error(
"Cannot take the derivative with respect to %s. "
"Expected a ContinuousSet or a tuple of "
"ContinuousSets" % i
)
if i not in sVar._contset:
raise DAE_Error(
"Invalid derivative: The variable %s is not indexed "
"by the ContinuousSet %s" % (sVar, i)
)
wrt = list(wrt)
else:
raise DAE_Error(
"Cannot take the derivative with respect to %s. "
"Expected a ContinuousSet or a tuple of ContinuousSets" % i
)
wrtkey = [str(i) for i in wrt]
wrtkey.sort()
wrtkey = tuple(wrtkey)
if wrtkey in sVar._derivative:
raise DAE_Error(
"Cannot create a new derivative variable for variable "
"%s: derivative already defined as %s"
% (sVar.name, sVar._derivative[wrtkey]().name)
)
sVar._derivative[wrtkey] = weakref.ref(self)
self._sVar = sVar
self._wrt = wrt
kwds.setdefault('ctype', DerivativeVar)
Var.__init__(self, sVar.index_set(), **kwds)
[docs] def get_continuousset_list(self):
"""Return the a list of :py:class:`ContinuousSet` components the
derivative is being taken with respect to.
Returns
-------
`list`
"""
return self._wrt
[docs] def is_fully_discretized(self):
"""
Check to see if all the
:py:class:`ContinuousSets<pyomo.dae.ContinuousSet>` this derivative
is taken with respect to have been discretized.
Returns
-------
`boolean`
"""
for i in self._wrt:
if 'scheme' not in i.get_discretization_info():
return False
return True
[docs] def get_state_var(self):
"""Return the :py:class:`Var` that is being differentiated.
Returns
-------
:py:class:`Var<pyomo.environ.Var>`
"""
return self._sVar
[docs] def get_derivative_expression(self):
"""
Returns the current discretization expression for this derivative or
creates an access function to its :py:class:`Var` the first time
this method is called. The expression gets built up as the
discretization transformations are sequentially applied to each
:py:class:`ContinuousSet` in the model.
"""
try:
return self._expr
except:
self._expr = create_access_function(self._sVar)
return self._expr
[docs] def set_derivative_expression(self, expr):
"""Sets``_expr``, an expression representing the discretization
equations linking the :class:`DerivativeVar` to its state
:class:`Var`
"""
self._expr = expr
```