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@@ -263,3 +263,4 @@ tuning-competition-baseline/.venv/lib/python3.11/site-packages/torch/_inductor/_
 .venv/lib/python3.11/site-packages/setuptools/gui-arm64.exe filter=lfs diff=lfs merge=lfs -text
 .venv/lib/python3.11/site-packages/numpy.libs/libquadmath-96973f99.so.0.0.0 filter=lfs diff=lfs merge=lfs -text
 .venv/lib/python3.11/site-packages/numpy.libs/libgfortran-040039e1.so.5.0.0 filter=lfs diff=lfs merge=lfs -text
+tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/stats/__pycache__/stochastic_process_types.cpython-311.pyc filter=lfs diff=lfs merge=lfs -text

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/biomechanics/curve.py

@@ -0,0 +1,1763 @@
+"""Implementations of characteristic curves for musculotendon models."""
+
+from dataclasses import dataclass
+
+from sympy.core.expr import UnevaluatedExpr
+from sympy.core.function import ArgumentIndexError, Function
+from sympy.core.numbers import Float, Integer
+from sympy.functions.elementary.exponential import exp, log
+from sympy.functions.elementary.hyperbolic import cosh, sinh
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.printing.precedence import PRECEDENCE
+
+
+__all__ = [
+    'CharacteristicCurveCollection',
+    'CharacteristicCurveFunction',
+    'FiberForceLengthActiveDeGroote2016',
+    'FiberForceLengthPassiveDeGroote2016',
+    'FiberForceLengthPassiveInverseDeGroote2016',
+    'FiberForceVelocityDeGroote2016',
+    'FiberForceVelocityInverseDeGroote2016',
+    'TendonForceLengthDeGroote2016',
+    'TendonForceLengthInverseDeGroote2016',
+]
+
+
+class CharacteristicCurveFunction(Function):
+    """Base class for all musculotendon characteristic curve functions."""
+
+    @classmethod
+    def eval(cls):
+        msg = (
+            f'Cannot directly instantiate {cls.__name__!r}, instances of '
+            f'characteristic curves must be of a concrete subclass.'
+
+        )
+        raise TypeError(msg)
+
+    def _print_code(self, printer):
+        """Print code for the function defining the curve using a printer.
+
+        Explanation
+        ===========
+
+        The order of operations may need to be controlled as constant folding
+        the numeric terms within the equations of a musculotendon
+        characteristic curve can sometimes results in a numerically-unstable
+        expression.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print a string representation of the
+            characteristic curve as valid code in the target language.
+
+        """
+        return printer._print(printer.parenthesize(
+            self.doit(deep=False, evaluate=False), PRECEDENCE['Atom'],
+        ))
+
+    _ccode = _print_code
+    _cupycode = _print_code
+    _cxxcode = _print_code
+    _fcode = _print_code
+    _jaxcode = _print_code
+    _lambdacode = _print_code
+    _mpmathcode = _print_code
+    _octave = _print_code
+    _pythoncode = _print_code
+    _numpycode = _print_code
+    _scipycode = _print_code
+
+
+class TendonForceLengthDeGroote2016(CharacteristicCurveFunction):
+    r"""Tendon force-length curve based on De Groote et al., 2016 [1]_.
+
+    Explanation
+    ===========
+
+    Gives the normalized tendon force produced as a function of normalized
+    tendon length.
+
+    The function is defined by the equation:
+
+    $fl^T = c_0 \exp{c_3 \left( \tilde{l}^T - c_1 \right)} - c_2$
+
+    with constant values of $c_0 = 0.2$, $c_1 = 0.995$, $c_2 = 0.25$, and
+    $c_3 = 33.93669377311689$.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces no
+    force when the tendon is in an unstrained state. It also produces a force
+    of 1 normalized unit when the tendon is under a 5% strain.
+
+    Examples
+    ========
+
+    The preferred way to instantiate :class:`TendonForceLengthDeGroote2016` is using
+    the :meth:`~.with_defaults` constructor because this will automatically
+    populate the constants within the characteristic curve equation with the
+    floating point values from the original publication. This constructor takes
+    a single argument corresponding to normalized tendon length. We'll create a
+    :class:`~.Symbol` called ``l_T_tilde`` to represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import TendonForceLengthDeGroote2016
+    >>> l_T_tilde = Symbol('l_T_tilde')
+    >>> fl_T = TendonForceLengthDeGroote2016.with_defaults(l_T_tilde)
+    >>> fl_T
+    TendonForceLengthDeGroote2016(l_T_tilde, 0.2, 0.995, 0.25,
+    33.93669377311689)
+
+    It's also possible to populate the four constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1, c2, c3 = symbols('c0 c1 c2 c3')
+    >>> fl_T = TendonForceLengthDeGroote2016(l_T_tilde, c0, c1, c2, c3)
+    >>> fl_T
+    TendonForceLengthDeGroote2016(l_T_tilde, c0, c1, c2, c3)
+
+    You don't just have to use symbols as the arguments, it's also possible to
+    use expressions. Let's create a new pair of symbols, ``l_T`` and
+    ``l_T_slack``, representing tendon length and tendon slack length
+    respectively. We can then represent ``l_T_tilde`` as an expression, the
+    ratio of these.
+
+    >>> l_T, l_T_slack = symbols('l_T l_T_slack')
+    >>> l_T_tilde = l_T/l_T_slack
+    >>> fl_T = TendonForceLengthDeGroote2016.with_defaults(l_T_tilde)
+    >>> fl_T
+    TendonForceLengthDeGroote2016(l_T/l_T_slack, 0.2, 0.995, 0.25,
+    33.93669377311689)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> fl_T.doit(evaluate=False)
+    -0.25 + 0.2*exp(33.93669377311689*(l_T/l_T_slack - 0.995))
+
+    The function can also be differentiated. We'll differentiate with respect
+    to l_T using the ``diff`` method on an instance with the single positional
+    argument ``l_T``.
+
+    >>> fl_T.diff(l_T)
+    6.787338754623378*exp(33.93669377311689*(l_T/l_T_slack - 0.995))/l_T_slack
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, l_T_tilde):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the tendon force-length function using the
+        four constant values specified in the original publication.
+
+        These have the values:
+
+        $c_0 = 0.2$
+        $c_1 = 0.995$
+        $c_2 = 0.25$
+        $c_3 = 33.93669377311689$
+
+        Parameters
+        ==========
+
+        l_T_tilde : Any (sympifiable)
+            Normalized tendon length.
+
+        """
+        c0 = Float('0.2')
+        c1 = Float('0.995')
+        c2 = Float('0.25')
+        c3 = Float('33.93669377311689')
+        return cls(l_T_tilde, c0, c1, c2, c3)
+
+    @classmethod
+    def eval(cls, l_T_tilde, c0, c1, c2, c3):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        l_T_tilde : Any (sympifiable)
+            Normalized tendon length.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``0.2``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``0.995``.
+        c2 : Any (sympifiable)
+            The third constant in the characteristic equation. The published
+            value is ``0.25``.
+        c3 : Any (sympifiable)
+            The fourth constant in the characteristic equation. The published
+            value is ``33.93669377311689``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``l_T_tilde`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        l_T_tilde, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            l_T_tilde = l_T_tilde.doit(deep=deep, **hints)
+            c0, c1, c2, c3 = [c.doit(deep=deep, **hints) for c in constants]
+        else:
+            c0, c1, c2, c3 = constants
+
+        if evaluate:
+            return c0*exp(c3*(l_T_tilde - c1)) - c2
+
+        return c0*exp(c3*UnevaluatedExpr(l_T_tilde - c1)) - c2
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        l_T_tilde, c0, c1, c2, c3 = self.args
+        if argindex == 1:
+            return c0*c3*exp(c3*UnevaluatedExpr(l_T_tilde - c1))
+        elif argindex == 2:
+            return exp(c3*UnevaluatedExpr(l_T_tilde - c1))
+        elif argindex == 3:
+            return -c0*c3*exp(c3*UnevaluatedExpr(l_T_tilde - c1))
+        elif argindex == 4:
+            return Integer(-1)
+        elif argindex == 5:
+            return c0*(l_T_tilde - c1)*exp(c3*UnevaluatedExpr(l_T_tilde - c1))
+
+        raise ArgumentIndexError(self, argindex)
+
+    def inverse(self, argindex=1):
+        """Inverse function.
+
+        Parameters
+        ==========
+
+        argindex : int
+            Value to start indexing the arguments at. Default is ``1``.
+
+        """
+        return TendonForceLengthInverseDeGroote2016
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        l_T_tilde = self.args[0]
+        _l_T_tilde = printer._print(l_T_tilde)
+        return r'\operatorname{fl}^T \left( %s \right)' % _l_T_tilde
+
+
+class TendonForceLengthInverseDeGroote2016(CharacteristicCurveFunction):
+    r"""Inverse tendon force-length curve based on De Groote et al., 2016 [1]_.
+
+    Explanation
+    ===========
+
+    Gives the normalized tendon length that produces a specific normalized
+    tendon force.
+
+    The function is defined by the equation:
+
+    ${fl^T}^{-1} = frac{\log{\frac{fl^T + c_2}{c_0}}}{c_3} + c_1$
+
+    with constant values of $c_0 = 0.2$, $c_1 = 0.995$, $c_2 = 0.25$, and
+    $c_3 = 33.93669377311689$. This function is the exact analytical inverse
+    of the related tendon force-length curve ``TendonForceLengthDeGroote2016``.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces no
+    force when the tendon is in an unstrained state. It also produces a force
+    of 1 normalized unit when the tendon is under a 5% strain.
+
+    Examples
+    ========
+
+    The preferred way to instantiate :class:`TendonForceLengthInverseDeGroote2016` is
+    using the :meth:`~.with_defaults` constructor because this will automatically
+    populate the constants within the characteristic curve equation with the
+    floating point values from the original publication. This constructor takes
+    a single argument corresponding to normalized tendon force-length, which is
+    equal to the tendon force. We'll create a :class:`~.Symbol` called ``fl_T`` to
+    represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import TendonForceLengthInverseDeGroote2016
+    >>> fl_T = Symbol('fl_T')
+    >>> l_T_tilde = TendonForceLengthInverseDeGroote2016.with_defaults(fl_T)
+    >>> l_T_tilde
+    TendonForceLengthInverseDeGroote2016(fl_T, 0.2, 0.995, 0.25,
+    33.93669377311689)
+
+    It's also possible to populate the four constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1, c2, c3 = symbols('c0 c1 c2 c3')
+    >>> l_T_tilde = TendonForceLengthInverseDeGroote2016(fl_T, c0, c1, c2, c3)
+    >>> l_T_tilde
+    TendonForceLengthInverseDeGroote2016(fl_T, c0, c1, c2, c3)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> l_T_tilde.doit(evaluate=False)
+    c1 + log((c2 + fl_T)/c0)/c3
+
+    The function can also be differentiated. We'll differentiate with respect
+    to l_T using the ``diff`` method on an instance with the single positional
+    argument ``l_T``.
+
+    >>> l_T_tilde.diff(fl_T)
+    1/(c3*(c2 + fl_T))
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, fl_T):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the inverse tendon force-length function
+        using the four constant values specified in the original publication.
+
+        These have the values:
+
+        $c_0 = 0.2$
+        $c_1 = 0.995$
+        $c_2 = 0.25$
+        $c_3 = 33.93669377311689$
+
+        Parameters
+        ==========
+
+        fl_T : Any (sympifiable)
+            Normalized tendon force as a function of tendon length.
+
+        """
+        c0 = Float('0.2')
+        c1 = Float('0.995')
+        c2 = Float('0.25')
+        c3 = Float('33.93669377311689')
+        return cls(fl_T, c0, c1, c2, c3)
+
+    @classmethod
+    def eval(cls, fl_T, c0, c1, c2, c3):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        fl_T : Any (sympifiable)
+            Normalized tendon force as a function of tendon length.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``0.2``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``0.995``.
+        c2 : Any (sympifiable)
+            The third constant in the characteristic equation. The published
+            value is ``0.25``.
+        c3 : Any (sympifiable)
+            The fourth constant in the characteristic equation. The published
+            value is ``33.93669377311689``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``l_T_tilde`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        fl_T, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            fl_T = fl_T.doit(deep=deep, **hints)
+            c0, c1, c2, c3 = [c.doit(deep=deep, **hints) for c in constants]
+        else:
+            c0, c1, c2, c3 = constants
+
+        if evaluate:
+            return log((fl_T + c2)/c0)/c3 + c1
+
+        return log(UnevaluatedExpr((fl_T + c2)/c0))/c3 + c1
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        fl_T, c0, c1, c2, c3 = self.args
+        if argindex == 1:
+            return 1/(c3*(fl_T + c2))
+        elif argindex == 2:
+            return -1/(c0*c3)
+        elif argindex == 3:
+            return Integer(1)
+        elif argindex == 4:
+            return 1/(c3*(fl_T + c2))
+        elif argindex == 5:
+            return -log(UnevaluatedExpr((fl_T + c2)/c0))/c3**2
+
+        raise ArgumentIndexError(self, argindex)
+
+    def inverse(self, argindex=1):
+        """Inverse function.
+
+        Parameters
+        ==========
+
+        argindex : int
+            Value to start indexing the arguments at. Default is ``1``.
+
+        """
+        return TendonForceLengthDeGroote2016
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        fl_T = self.args[0]
+        _fl_T = printer._print(fl_T)
+        return r'\left( \operatorname{fl}^T \right)^{-1} \left( %s \right)' % _fl_T
+
+
+class FiberForceLengthPassiveDeGroote2016(CharacteristicCurveFunction):
+    r"""Passive muscle fiber force-length curve based on De Groote et al., 2016
+    [1]_.
+
+    Explanation
+    ===========
+
+    The function is defined by the equation:
+
+    $fl^M_{pas} = \frac{\frac{\exp{c_1 \left(\tilde{l^M} - 1\right)}}{c_0} - 1}{\exp{c_1} - 1}$
+
+    with constant values of $c_0 = 0.6$ and $c_1 = 4.0$.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces a
+    passive fiber force very close to 0 for all normalized fiber lengths
+    between 0 and 1.
+
+    Examples
+    ========
+
+    The preferred way to instantiate :class:`FiberForceLengthPassiveDeGroote2016` is
+    using the :meth:`~.with_defaults` constructor because this will automatically
+    populate the constants within the characteristic curve equation with the
+    floating point values from the original publication. This constructor takes
+    a single argument corresponding to normalized muscle fiber length. We'll
+    create a :class:`~.Symbol` called ``l_M_tilde`` to represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import FiberForceLengthPassiveDeGroote2016
+    >>> l_M_tilde = Symbol('l_M_tilde')
+    >>> fl_M = FiberForceLengthPassiveDeGroote2016.with_defaults(l_M_tilde)
+    >>> fl_M
+    FiberForceLengthPassiveDeGroote2016(l_M_tilde, 0.6, 4.0)
+
+    It's also possible to populate the two constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1 = symbols('c0 c1')
+    >>> fl_M = FiberForceLengthPassiveDeGroote2016(l_M_tilde, c0, c1)
+    >>> fl_M
+    FiberForceLengthPassiveDeGroote2016(l_M_tilde, c0, c1)
+
+    You don't just have to use symbols as the arguments, it's also possible to
+    use expressions. Let's create a new pair of symbols, ``l_M`` and
+    ``l_M_opt``, representing muscle fiber length and optimal muscle fiber
+    length respectively. We can then represent ``l_M_tilde`` as an expression,
+    the ratio of these.
+
+    >>> l_M, l_M_opt = symbols('l_M l_M_opt')
+    >>> l_M_tilde = l_M/l_M_opt
+    >>> fl_M = FiberForceLengthPassiveDeGroote2016.with_defaults(l_M_tilde)
+    >>> fl_M
+    FiberForceLengthPassiveDeGroote2016(l_M/l_M_opt, 0.6, 4.0)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> fl_M.doit(evaluate=False)
+    0.0186573603637741*(-1 + exp(6.66666666666667*(l_M/l_M_opt - 1)))
+
+    The function can also be differentiated. We'll differentiate with respect
+    to l_M using the ``diff`` method on an instance with the single positional
+    argument ``l_M``.
+
+    >>> fl_M.diff(l_M)
+    0.12438240242516*exp(6.66666666666667*(l_M/l_M_opt - 1))/l_M_opt
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, l_M_tilde):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the muscle fiber passive force-length
+        function using the four constant values specified in the original
+        publication.
+
+        These have the values:
+
+        $c_0 = 0.6$
+        $c_1 = 4.0$
+
+        Parameters
+        ==========
+
+        l_M_tilde : Any (sympifiable)
+            Normalized muscle fiber length.
+
+        """
+        c0 = Float('0.6')
+        c1 = Float('4.0')
+        return cls(l_M_tilde, c0, c1)
+
+    @classmethod
+    def eval(cls, l_M_tilde, c0, c1):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        l_M_tilde : Any (sympifiable)
+            Normalized muscle fiber length.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``0.6``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``4.0``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``l_T_tilde`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        l_M_tilde, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            l_M_tilde = l_M_tilde.doit(deep=deep, **hints)
+            c0, c1 = [c.doit(deep=deep, **hints) for c in constants]
+        else:
+            c0, c1 = constants
+
+        if evaluate:
+            return (exp((c1*(l_M_tilde - 1))/c0) - 1)/(exp(c1) - 1)
+
+        return (exp((c1*UnevaluatedExpr(l_M_tilde - 1))/c0) - 1)/(exp(c1) - 1)
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        l_M_tilde, c0, c1 = self.args
+        if argindex == 1:
+            return c1*exp(c1*UnevaluatedExpr(l_M_tilde - 1)/c0)/(c0*(exp(c1) - 1))
+        elif argindex == 2:
+            return (
+                -c1*exp(c1*UnevaluatedExpr(l_M_tilde - 1)/c0)
+                *UnevaluatedExpr(l_M_tilde - 1)/(c0**2*(exp(c1) - 1))
+            )
+        elif argindex == 3:
+            return (
+                -exp(c1)*(-1 + exp(c1*UnevaluatedExpr(l_M_tilde - 1)/c0))/(exp(c1) - 1)**2
+                + exp(c1*UnevaluatedExpr(l_M_tilde - 1)/c0)*(l_M_tilde - 1)/(c0*(exp(c1) - 1))
+            )
+
+        raise ArgumentIndexError(self, argindex)
+
+    def inverse(self, argindex=1):
+        """Inverse function.
+
+        Parameters
+        ==========
+
+        argindex : int
+            Value to start indexing the arguments at. Default is ``1``.
+
+        """
+        return FiberForceLengthPassiveInverseDeGroote2016
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        l_M_tilde = self.args[0]
+        _l_M_tilde = printer._print(l_M_tilde)
+        return r'\operatorname{fl}^M_{pas} \left( %s \right)' % _l_M_tilde
+
+
+class FiberForceLengthPassiveInverseDeGroote2016(CharacteristicCurveFunction):
+    r"""Inverse passive muscle fiber force-length curve based on De Groote et
+    al., 2016 [1]_.
+
+    Explanation
+    ===========
+
+    Gives the normalized muscle fiber length that produces a specific normalized
+    passive muscle fiber force.
+
+    The function is defined by the equation:
+
+    ${fl^M_{pas}}^{-1} = \frac{c_0 \log{\left(\exp{c_1} - 1\right)fl^M_pas + 1}}{c_1} + 1$
+
+    with constant values of $c_0 = 0.6$ and $c_1 = 4.0$. This function is the
+    exact analytical inverse of the related tendon force-length curve
+    ``FiberForceLengthPassiveDeGroote2016``.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces a
+    passive fiber force very close to 0 for all normalized fiber lengths
+    between 0 and 1.
+
+    Examples
+    ========
+
+    The preferred way to instantiate
+    :class:`FiberForceLengthPassiveInverseDeGroote2016` is using the
+    :meth:`~.with_defaults` constructor because this will automatically populate the
+    constants within the characteristic curve equation with the floating point
+    values from the original publication. This constructor takes a single
+    argument corresponding to the normalized passive muscle fiber length-force
+    component of the muscle fiber force. We'll create a :class:`~.Symbol` called
+    ``fl_M_pas`` to represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import FiberForceLengthPassiveInverseDeGroote2016
+    >>> fl_M_pas = Symbol('fl_M_pas')
+    >>> l_M_tilde = FiberForceLengthPassiveInverseDeGroote2016.with_defaults(fl_M_pas)
+    >>> l_M_tilde
+    FiberForceLengthPassiveInverseDeGroote2016(fl_M_pas, 0.6, 4.0)
+
+    It's also possible to populate the two constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1 = symbols('c0 c1')
+    >>> l_M_tilde = FiberForceLengthPassiveInverseDeGroote2016(fl_M_pas, c0, c1)
+    >>> l_M_tilde
+    FiberForceLengthPassiveInverseDeGroote2016(fl_M_pas, c0, c1)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> l_M_tilde.doit(evaluate=False)
+    c0*log(1 + fl_M_pas*(exp(c1) - 1))/c1 + 1
+
+    The function can also be differentiated. We'll differentiate with respect
+    to fl_M_pas using the ``diff`` method on an instance with the single positional
+    argument ``fl_M_pas``.
+
+    >>> l_M_tilde.diff(fl_M_pas)
+    c0*(exp(c1) - 1)/(c1*(fl_M_pas*(exp(c1) - 1) + 1))
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, fl_M_pas):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the inverse muscle fiber passive force-length
+        function using the four constant values specified in the original
+        publication.
+
+        These have the values:
+
+        $c_0 = 0.6$
+        $c_1 = 4.0$
+
+        Parameters
+        ==========
+
+        fl_M_pas : Any (sympifiable)
+            Normalized passive muscle fiber force as a function of muscle fiber
+            length.
+
+        """
+        c0 = Float('0.6')
+        c1 = Float('4.0')
+        return cls(fl_M_pas, c0, c1)
+
+    @classmethod
+    def eval(cls, fl_M_pas, c0, c1):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        fl_M_pas : Any (sympifiable)
+            Normalized passive muscle fiber force.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``0.6``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``4.0``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``l_T_tilde`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        fl_M_pas, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            fl_M_pas = fl_M_pas.doit(deep=deep, **hints)
+            c0, c1 = [c.doit(deep=deep, **hints) for c in constants]
+        else:
+            c0, c1 = constants
+
+        if evaluate:
+            return c0*log(fl_M_pas*(exp(c1) - 1) + 1)/c1 + 1
+
+        return c0*log(UnevaluatedExpr(fl_M_pas*(exp(c1) - 1)) + 1)/c1 + 1
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        fl_M_pas, c0, c1 = self.args
+        if argindex == 1:
+            return c0*(exp(c1) - 1)/(c1*(fl_M_pas*(exp(c1) - 1) + 1))
+        elif argindex == 2:
+            return log(fl_M_pas*(exp(c1) - 1) + 1)/c1
+        elif argindex == 3:
+            return (
+                c0*fl_M_pas*exp(c1)/(c1*(fl_M_pas*(exp(c1) - 1) + 1))
+                - c0*log(fl_M_pas*(exp(c1) - 1) + 1)/c1**2
+            )
+
+        raise ArgumentIndexError(self, argindex)
+
+    def inverse(self, argindex=1):
+        """Inverse function.
+
+        Parameters
+        ==========
+
+        argindex : int
+            Value to start indexing the arguments at. Default is ``1``.
+
+        """
+        return FiberForceLengthPassiveDeGroote2016
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        fl_M_pas = self.args[0]
+        _fl_M_pas = printer._print(fl_M_pas)
+        return r'\left( \operatorname{fl}^M_{pas} \right)^{-1} \left( %s \right)' % _fl_M_pas
+
+
+class FiberForceLengthActiveDeGroote2016(CharacteristicCurveFunction):
+    r"""Active muscle fiber force-length curve based on De Groote et al., 2016
+    [1]_.
+
+    Explanation
+    ===========
+
+    The function is defined by the equation:
+
+    $fl_{\text{act}}^M = c_0 \exp\left(-\frac{1}{2}\left(\frac{\tilde{l}^M - c_1}{c_2 + c_3 \tilde{l}^M}\right)^2\right)
+    + c_4 \exp\left(-\frac{1}{2}\left(\frac{\tilde{l}^M - c_5}{c_6 + c_7 \tilde{l}^M}\right)^2\right)
+    + c_8 \exp\left(-\frac{1}{2}\left(\frac{\tilde{l}^M - c_9}{c_{10} + c_{11} \tilde{l}^M}\right)^2\right)$
+
+    with constant values of $c0 = 0.814$, $c1 = 1.06$, $c2 = 0.162$,
+    $c3 = 0.0633$, $c4 = 0.433$, $c5 = 0.717$, $c6 = -0.0299$, $c7 = 0.2$,
+    $c8 = 0.1$, $c9 = 1.0$, $c10 = 0.354$, and $c11 = 0.0$.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces a
+    active fiber force of 1 at a normalized fiber length of 1, and an active
+    fiber force of 0 at normalized fiber lengths of 0 and 2.
+
+    Examples
+    ========
+
+    The preferred way to instantiate :class:`FiberForceLengthActiveDeGroote2016` is
+    using the :meth:`~.with_defaults` constructor because this will automatically
+    populate the constants within the characteristic curve equation with the
+    floating point values from the original publication. This constructor takes
+    a single argument corresponding to normalized muscle fiber length. We'll
+    create a :class:`~.Symbol` called ``l_M_tilde`` to represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import FiberForceLengthActiveDeGroote2016
+    >>> l_M_tilde = Symbol('l_M_tilde')
+    >>> fl_M = FiberForceLengthActiveDeGroote2016.with_defaults(l_M_tilde)
+    >>> fl_M
+    FiberForceLengthActiveDeGroote2016(l_M_tilde, 0.814, 1.06, 0.162, 0.0633,
+    0.433, 0.717, -0.0299, 0.2, 0.1, 1.0, 0.354, 0.0)
+
+    It's also possible to populate the two constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11 = symbols('c0:12')
+    >>> fl_M = FiberForceLengthActiveDeGroote2016(l_M_tilde, c0, c1, c2, c3,
+    ...     c4, c5, c6, c7, c8, c9, c10, c11)
+    >>> fl_M
+    FiberForceLengthActiveDeGroote2016(l_M_tilde, c0, c1, c2, c3, c4, c5, c6,
+    c7, c8, c9, c10, c11)
+
+    You don't just have to use symbols as the arguments, it's also possible to
+    use expressions. Let's create a new pair of symbols, ``l_M`` and
+    ``l_M_opt``, representing muscle fiber length and optimal muscle fiber
+    length respectively. We can then represent ``l_M_tilde`` as an expression,
+    the ratio of these.
+
+    >>> l_M, l_M_opt = symbols('l_M l_M_opt')
+    >>> l_M_tilde = l_M/l_M_opt
+    >>> fl_M = FiberForceLengthActiveDeGroote2016.with_defaults(l_M_tilde)
+    >>> fl_M
+    FiberForceLengthActiveDeGroote2016(l_M/l_M_opt, 0.814, 1.06, 0.162, 0.0633,
+    0.433, 0.717, -0.0299, 0.2, 0.1, 1.0, 0.354, 0.0)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> fl_M.doit(evaluate=False)
+    0.814*exp(-19.0519737844841*(l_M/l_M_opt
+    - 1.06)**2/(0.390740740740741*l_M/l_M_opt + 1)**2)
+    + 0.433*exp(-12.5*(l_M/l_M_opt - 0.717)**2/(l_M/l_M_opt - 0.1495)**2)
+    + 0.1*exp(-3.98991349867535*(l_M/l_M_opt - 1.0)**2)
+
+    The function can also be differentiated. We'll differentiate with respect
+    to l_M using the ``diff`` method on an instance with the single positional
+    argument ``l_M``.
+
+    >>> fl_M.diff(l_M)
+    ((-0.79798269973507*l_M/l_M_opt
+    + 0.79798269973507)*exp(-3.98991349867535*(l_M/l_M_opt - 1.0)**2)
+    + (10.825*(-l_M/l_M_opt + 0.717)/(l_M/l_M_opt - 0.1495)**2
+    + 10.825*(l_M/l_M_opt - 0.717)**2/(l_M/l_M_opt
+    - 0.1495)**3)*exp(-12.5*(l_M/l_M_opt - 0.717)**2/(l_M/l_M_opt - 0.1495)**2)
+    + (31.0166133211401*(-l_M/l_M_opt + 1.06)/(0.390740740740741*l_M/l_M_opt
+    + 1)**2 + 13.6174190361677*(0.943396226415094*l_M/l_M_opt
+    - 1)**2/(0.390740740740741*l_M/l_M_opt
+    + 1)**3)*exp(-21.4067977442463*(0.943396226415094*l_M/l_M_opt
+    - 1)**2/(0.390740740740741*l_M/l_M_opt + 1)**2))/l_M_opt
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, l_M_tilde):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the inverse muscle fiber act force-length
+        function using the four constant values specified in the original
+        publication.
+
+        These have the values:
+
+        $c0 = 0.814$
+        $c1 = 1.06$
+        $c2 = 0.162$
+        $c3 = 0.0633$
+        $c4 = 0.433$
+        $c5 = 0.717$
+        $c6 = -0.0299$
+        $c7 = 0.2$
+        $c8 = 0.1$
+        $c9 = 1.0$
+        $c10 = 0.354$
+        $c11 = 0.0$
+
+        Parameters
+        ==========
+
+        fl_M_act : Any (sympifiable)
+            Normalized passive muscle fiber force as a function of muscle fiber
+            length.
+
+        """
+        c0 = Float('0.814')
+        c1 = Float('1.06')
+        c2 = Float('0.162')
+        c3 = Float('0.0633')
+        c4 = Float('0.433')
+        c5 = Float('0.717')
+        c6 = Float('-0.0299')
+        c7 = Float('0.2')
+        c8 = Float('0.1')
+        c9 = Float('1.0')
+        c10 = Float('0.354')
+        c11 = Float('0.0')
+        return cls(l_M_tilde, c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11)
+
+    @classmethod
+    def eval(cls, l_M_tilde, c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        l_M_tilde : Any (sympifiable)
+            Normalized muscle fiber length.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``0.814``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``1.06``.
+        c2 : Any (sympifiable)
+            The third constant in the characteristic equation. The published
+            value is ``0.162``.
+        c3 : Any (sympifiable)
+            The fourth constant in the characteristic equation. The published
+            value is ``0.0633``.
+        c4 : Any (sympifiable)
+            The fifth constant in the characteristic equation. The published
+            value is ``0.433``.
+        c5 : Any (sympifiable)
+            The sixth constant in the characteristic equation. The published
+            value is ``0.717``.
+        c6 : Any (sympifiable)
+            The seventh constant in the characteristic equation. The published
+            value is ``-0.0299``.
+        c7 : Any (sympifiable)
+            The eighth constant in the characteristic equation. The published
+            value is ``0.2``.
+        c8 : Any (sympifiable)
+            The ninth constant in the characteristic equation. The published
+            value is ``0.1``.
+        c9 : Any (sympifiable)
+            The tenth constant in the characteristic equation. The published
+            value is ``1.0``.
+        c10 : Any (sympifiable)
+            The eleventh constant in the characteristic equation. The published
+            value is ``0.354``.
+        c11 : Any (sympifiable)
+            The tweflth constant in the characteristic equation. The published
+            value is ``0.0``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``l_M_tilde`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        l_M_tilde, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            l_M_tilde = l_M_tilde.doit(deep=deep, **hints)
+            constants = [c.doit(deep=deep, **hints) for c in constants]
+        c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11 = constants
+
+        if evaluate:
+            return (
+                c0*exp(-(((l_M_tilde - c1)/(c2 + c3*l_M_tilde))**2)/2)
+                + c4*exp(-(((l_M_tilde - c5)/(c6 + c7*l_M_tilde))**2)/2)
+                + c8*exp(-(((l_M_tilde - c9)/(c10 + c11*l_M_tilde))**2)/2)
+            )
+
+        return (
+            c0*exp(-((UnevaluatedExpr(l_M_tilde - c1)/(c2 + c3*l_M_tilde))**2)/2)
+            + c4*exp(-((UnevaluatedExpr(l_M_tilde - c5)/(c6 + c7*l_M_tilde))**2)/2)
+            + c8*exp(-((UnevaluatedExpr(l_M_tilde - c9)/(c10 + c11*l_M_tilde))**2)/2)
+        )
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        l_M_tilde, c0, c1, c2, c3, c4, c5, c6, c7, c8, c9, c10, c11 = self.args
+        if argindex == 1:
+            return (
+                c0*(
+                    c3*(l_M_tilde - c1)**2/(c2 + c3*l_M_tilde)**3
+                    + (c1 - l_M_tilde)/((c2 + c3*l_M_tilde)**2)
+                )*exp(-(l_M_tilde - c1)**2/(2*(c2 + c3*l_M_tilde)**2))
+                + c4*(
+                    c7*(l_M_tilde - c5)**2/(c6 + c7*l_M_tilde)**3
+                    + (c5 - l_M_tilde)/((c6 + c7*l_M_tilde)**2)
+                )*exp(-(l_M_tilde - c5)**2/(2*(c6 + c7*l_M_tilde)**2))
+                + c8*(
+                    c11*(l_M_tilde - c9)**2/(c10 + c11*l_M_tilde)**3
+                    + (c9 - l_M_tilde)/((c10 + c11*l_M_tilde)**2)
+                )*exp(-(l_M_tilde - c9)**2/(2*(c10 + c11*l_M_tilde)**2))
+            )
+        elif argindex == 2:
+            return exp(-(l_M_tilde - c1)**2/(2*(c2 + c3*l_M_tilde)**2))
+        elif argindex == 3:
+            return (
+                c0*(l_M_tilde - c1)/(c2 + c3*l_M_tilde)**2
+                *exp(-(l_M_tilde - c1)**2 /(2*(c2 + c3*l_M_tilde)**2))
+            )
+        elif argindex == 4:
+            return (
+                c0*(l_M_tilde - c1)**2/(c2 + c3*l_M_tilde)**3
+                *exp(-(l_M_tilde - c1)**2/(2*(c2 + c3*l_M_tilde)**2))
+            )
+        elif argindex == 5:
+            return (
+                c0*l_M_tilde*(l_M_tilde - c1)**2/(c2 + c3*l_M_tilde)**3
+                *exp(-(l_M_tilde - c1)**2/(2*(c2 + c3*l_M_tilde)**2))
+            )
+        elif argindex == 6:
+            return exp(-(l_M_tilde - c5)**2/(2*(c6 + c7*l_M_tilde)**2))
+        elif argindex == 7:
+            return (
+                c4*(l_M_tilde - c5)/(c6 + c7*l_M_tilde)**2
+                *exp(-(l_M_tilde - c5)**2 /(2*(c6 + c7*l_M_tilde)**2))
+            )
+        elif argindex == 8:
+            return (
+                c4*(l_M_tilde - c5)**2/(c6 + c7*l_M_tilde)**3
+                *exp(-(l_M_tilde - c5)**2/(2*(c6 + c7*l_M_tilde)**2))
+            )
+        elif argindex == 9:
+            return (
+                c4*l_M_tilde*(l_M_tilde - c5)**2/(c6 + c7*l_M_tilde)**3
+                *exp(-(l_M_tilde - c5)**2/(2*(c6 + c7*l_M_tilde)**2))
+            )
+        elif argindex == 10:
+            return exp(-(l_M_tilde - c9)**2/(2*(c10 + c11*l_M_tilde)**2))
+        elif argindex == 11:
+            return (
+                c8*(l_M_tilde - c9)/(c10 + c11*l_M_tilde)**2
+                *exp(-(l_M_tilde - c9)**2 /(2*(c10 + c11*l_M_tilde)**2))
+            )
+        elif argindex == 12:
+            return (
+                c8*(l_M_tilde - c9)**2/(c10 + c11*l_M_tilde)**3
+                *exp(-(l_M_tilde - c9)**2/(2*(c10 + c11*l_M_tilde)**2))
+            )
+        elif argindex == 13:
+            return (
+                c8*l_M_tilde*(l_M_tilde - c9)**2/(c10 + c11*l_M_tilde)**3
+                *exp(-(l_M_tilde - c9)**2/(2*(c10 + c11*l_M_tilde)**2))
+            )
+
+        raise ArgumentIndexError(self, argindex)
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        l_M_tilde = self.args[0]
+        _l_M_tilde = printer._print(l_M_tilde)
+        return r'\operatorname{fl}^M_{act} \left( %s \right)' % _l_M_tilde
+
+
+class FiberForceVelocityDeGroote2016(CharacteristicCurveFunction):
+    r"""Muscle fiber force-velocity curve based on De Groote et al., 2016 [1]_.
+
+    Explanation
+    ===========
+
+    Gives the normalized muscle fiber force produced as a function of
+    normalized tendon velocity.
+
+    The function is defined by the equation:
+
+    $fv^M = c_0 \log{\left(c_1 \tilde{v}_m + c_2\right) + \sqrt{\left(c_1 \tilde{v}_m + c_2\right)^2 + 1}} + c_3$
+
+    with constant values of $c_0 = -0.318$, $c_1 = -8.149$, $c_2 = -0.374$, and
+    $c_3 = 0.886$.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces a
+    normalized muscle fiber force of 1 when the muscle fibers are contracting
+    isometrically (they have an extension rate of 0).
+
+    Examples
+    ========
+
+    The preferred way to instantiate :class:`FiberForceVelocityDeGroote2016` is using
+    the :meth:`~.with_defaults` constructor because this will automatically populate
+    the constants within the characteristic curve equation with the floating
+    point values from the original publication. This constructor takes a single
+    argument corresponding to normalized muscle fiber extension velocity. We'll
+    create a :class:`~.Symbol` called ``v_M_tilde`` to represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import FiberForceVelocityDeGroote2016
+    >>> v_M_tilde = Symbol('v_M_tilde')
+    >>> fv_M = FiberForceVelocityDeGroote2016.with_defaults(v_M_tilde)
+    >>> fv_M
+    FiberForceVelocityDeGroote2016(v_M_tilde, -0.318, -8.149, -0.374, 0.886)
+
+    It's also possible to populate the four constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1, c2, c3 = symbols('c0 c1 c2 c3')
+    >>> fv_M = FiberForceVelocityDeGroote2016(v_M_tilde, c0, c1, c2, c3)
+    >>> fv_M
+    FiberForceVelocityDeGroote2016(v_M_tilde, c0, c1, c2, c3)
+
+    You don't just have to use symbols as the arguments, it's also possible to
+    use expressions. Let's create a new pair of symbols, ``v_M`` and
+    ``v_M_max``, representing muscle fiber extension velocity and maximum
+    muscle fiber extension velocity respectively. We can then represent
+    ``v_M_tilde`` as an expression, the ratio of these.
+
+    >>> v_M, v_M_max = symbols('v_M v_M_max')
+    >>> v_M_tilde = v_M/v_M_max
+    >>> fv_M = FiberForceVelocityDeGroote2016.with_defaults(v_M_tilde)
+    >>> fv_M
+    FiberForceVelocityDeGroote2016(v_M/v_M_max, -0.318, -8.149, -0.374, 0.886)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> fv_M.doit(evaluate=False)
+    0.886 - 0.318*log(-8.149*v_M/v_M_max - 0.374 + sqrt(1 + (-8.149*v_M/v_M_max
+    - 0.374)**2))
+
+    The function can also be differentiated. We'll differentiate with respect
+    to v_M using the ``diff`` method on an instance with the single positional
+    argument ``v_M``.
+
+    >>> fv_M.diff(v_M)
+    2.591382*(1 + (-8.149*v_M/v_M_max - 0.374)**2)**(-1/2)/v_M_max
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, v_M_tilde):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the muscle fiber force-velocity function
+        using the four constant values specified in the original publication.
+
+        These have the values:
+
+        $c_0 = -0.318$
+        $c_1 = -8.149$
+        $c_2 = -0.374$
+        $c_3 = 0.886$
+
+        Parameters
+        ==========
+
+        v_M_tilde : Any (sympifiable)
+            Normalized muscle fiber extension velocity.
+
+        """
+        c0 = Float('-0.318')
+        c1 = Float('-8.149')
+        c2 = Float('-0.374')
+        c3 = Float('0.886')
+        return cls(v_M_tilde, c0, c1, c2, c3)
+
+    @classmethod
+    def eval(cls, v_M_tilde, c0, c1, c2, c3):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        v_M_tilde : Any (sympifiable)
+            Normalized muscle fiber extension velocity.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``-0.318``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``-8.149``.
+        c2 : Any (sympifiable)
+            The third constant in the characteristic equation. The published
+            value is ``-0.374``.
+        c3 : Any (sympifiable)
+            The fourth constant in the characteristic equation. The published
+            value is ``0.886``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``v_M_tilde`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        v_M_tilde, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            v_M_tilde = v_M_tilde.doit(deep=deep, **hints)
+            c0, c1, c2, c3 = [c.doit(deep=deep, **hints) for c in constants]
+        else:
+            c0, c1, c2, c3 = constants
+
+        if evaluate:
+            return c0*log(c1*v_M_tilde + c2 + sqrt((c1*v_M_tilde + c2)**2 + 1)) + c3
+
+        return c0*log(c1*v_M_tilde + c2 + sqrt(UnevaluatedExpr(c1*v_M_tilde + c2)**2 + 1)) + c3
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        v_M_tilde, c0, c1, c2, c3 = self.args
+        if argindex == 1:
+            return c0*c1/sqrt(UnevaluatedExpr(c1*v_M_tilde + c2)**2 + 1)
+        elif argindex == 2:
+            return log(
+                c1*v_M_tilde + c2
+                + sqrt(UnevaluatedExpr(c1*v_M_tilde + c2)**2 + 1)
+            )
+        elif argindex == 3:
+            return c0*v_M_tilde/sqrt(UnevaluatedExpr(c1*v_M_tilde + c2)**2 + 1)
+        elif argindex == 4:
+            return c0/sqrt(UnevaluatedExpr(c1*v_M_tilde + c2)**2 + 1)
+        elif argindex == 5:
+            return Integer(1)
+
+        raise ArgumentIndexError(self, argindex)
+
+    def inverse(self, argindex=1):
+        """Inverse function.
+
+        Parameters
+        ==========
+
+        argindex : int
+            Value to start indexing the arguments at. Default is ``1``.
+
+        """
+        return FiberForceVelocityInverseDeGroote2016
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        v_M_tilde = self.args[0]
+        _v_M_tilde = printer._print(v_M_tilde)
+        return r'\operatorname{fv}^M \left( %s \right)' % _v_M_tilde
+
+
+class FiberForceVelocityInverseDeGroote2016(CharacteristicCurveFunction):
+    r"""Inverse muscle fiber force-velocity curve based on De Groote et al.,
+    2016 [1]_.
+
+    Explanation
+    ===========
+
+    Gives the normalized muscle fiber velocity that produces a specific
+    normalized muscle fiber force.
+
+    The function is defined by the equation:
+
+    ${fv^M}^{-1} = \frac{\sinh{\frac{fv^M - c_3}{c_0}} - c_2}{c_1}$
+
+    with constant values of $c_0 = -0.318$, $c_1 = -8.149$, $c_2 = -0.374$, and
+    $c_3 = 0.886$. This function is the exact analytical inverse of the related
+    muscle fiber force-velocity curve ``FiberForceVelocityDeGroote2016``.
+
+    While it is possible to change the constant values, these were carefully
+    selected in the original publication to give the characteristic curve
+    specific and required properties. For example, the function produces a
+    normalized muscle fiber force of 1 when the muscle fibers are contracting
+    isometrically (they have an extension rate of 0).
+
+    Examples
+    ========
+
+    The preferred way to instantiate :class:`FiberForceVelocityInverseDeGroote2016`
+    is using the :meth:`~.with_defaults` constructor because this will automatically
+    populate the constants within the characteristic curve equation with the
+    floating point values from the original publication. This constructor takes
+    a single argument corresponding to normalized muscle fiber force-velocity
+    component of the muscle fiber force. We'll create a :class:`~.Symbol` called
+    ``fv_M`` to represent this.
+
+    >>> from sympy import Symbol
+    >>> from sympy.physics.biomechanics import FiberForceVelocityInverseDeGroote2016
+    >>> fv_M = Symbol('fv_M')
+    >>> v_M_tilde = FiberForceVelocityInverseDeGroote2016.with_defaults(fv_M)
+    >>> v_M_tilde
+    FiberForceVelocityInverseDeGroote2016(fv_M, -0.318, -8.149, -0.374, 0.886)
+
+    It's also possible to populate the four constants with your own values too.
+
+    >>> from sympy import symbols
+    >>> c0, c1, c2, c3 = symbols('c0 c1 c2 c3')
+    >>> v_M_tilde = FiberForceVelocityInverseDeGroote2016(fv_M, c0, c1, c2, c3)
+    >>> v_M_tilde
+    FiberForceVelocityInverseDeGroote2016(fv_M, c0, c1, c2, c3)
+
+    To inspect the actual symbolic expression that this function represents,
+    we can call the :meth:`~.doit` method on an instance. We'll use the keyword
+    argument ``evaluate=False`` as this will keep the expression in its
+    canonical form and won't simplify any constants.
+
+    >>> v_M_tilde.doit(evaluate=False)
+    (-c2 + sinh((-c3 + fv_M)/c0))/c1
+
+    The function can also be differentiated. We'll differentiate with respect
+    to fv_M using the ``diff`` method on an instance with the single positional
+    argument ``fv_M``.
+
+    >>> v_M_tilde.diff(fv_M)
+    cosh((-c3 + fv_M)/c0)/(c0*c1)
+
+    References
+    ==========
+
+    .. [1] De Groote, F., Kinney, A. L., Rao, A. V., & Fregly, B. J., Evaluation
+           of direct collocation optimal control problem formulations for
+           solving the muscle redundancy problem, Annals of biomedical
+           engineering, 44(10), (2016) pp. 2922-2936
+
+    """
+
+    @classmethod
+    def with_defaults(cls, fv_M):
+        r"""Recommended constructor that will use the published constants.
+
+        Explanation
+        ===========
+
+        Returns a new instance of the inverse muscle fiber force-velocity
+        function using the four constant values specified in the original
+        publication.
+
+        These have the values:
+
+        $c_0 = -0.318$
+        $c_1 = -8.149$
+        $c_2 = -0.374$
+        $c_3 = 0.886$
+
+        Parameters
+        ==========
+
+        fv_M : Any (sympifiable)
+            Normalized muscle fiber extension velocity.
+
+        """
+        c0 = Float('-0.318')
+        c1 = Float('-8.149')
+        c2 = Float('-0.374')
+        c3 = Float('0.886')
+        return cls(fv_M, c0, c1, c2, c3)
+
+    @classmethod
+    def eval(cls, fv_M, c0, c1, c2, c3):
+        """Evaluation of basic inputs.
+
+        Parameters
+        ==========
+
+        fv_M : Any (sympifiable)
+            Normalized muscle fiber force as a function of muscle fiber
+            extension velocity.
+        c0 : Any (sympifiable)
+            The first constant in the characteristic equation. The published
+            value is ``-0.318``.
+        c1 : Any (sympifiable)
+            The second constant in the characteristic equation. The published
+            value is ``-8.149``.
+        c2 : Any (sympifiable)
+            The third constant in the characteristic equation. The published
+            value is ``-0.374``.
+        c3 : Any (sympifiable)
+            The fourth constant in the characteristic equation. The published
+            value is ``0.886``.
+
+        """
+        pass
+
+    def _eval_evalf(self, prec):
+        """Evaluate the expression numerically using ``evalf``."""
+        return self.doit(deep=False, evaluate=False)._eval_evalf(prec)
+
+    def doit(self, deep=True, evaluate=True, **hints):
+        """Evaluate the expression defining the function.
+
+        Parameters
+        ==========
+
+        deep : bool
+            Whether ``doit`` should be recursively called. Default is ``True``.
+        evaluate : bool.
+            Whether the SymPy expression should be evaluated as it is
+            constructed. If ``False``, then no constant folding will be
+            conducted which will leave the expression in a more numerically-
+            stable for values of ``fv_M`` that correspond to a sensible
+            operating range for a musculotendon. Default is ``True``.
+        **kwargs : dict[str, Any]
+            Additional keyword argument pairs to be recursively passed to
+            ``doit``.
+
+        """
+        fv_M, *constants = self.args
+        if deep:
+            hints['evaluate'] = evaluate
+            fv_M = fv_M.doit(deep=deep, **hints)
+            c0, c1, c2, c3 = [c.doit(deep=deep, **hints) for c in constants]
+        else:
+            c0, c1, c2, c3 = constants
+
+        if evaluate:
+            return (sinh((fv_M - c3)/c0) - c2)/c1
+
+        return (sinh(UnevaluatedExpr(fv_M - c3)/c0) - c2)/c1
+
+    def fdiff(self, argindex=1):
+        """Derivative of the function with respect to a single argument.
+
+        Parameters
+        ==========
+
+        argindex : int
+            The index of the function's arguments with respect to which the
+            derivative should be taken. Argument indexes start at ``1``.
+            Default is ``1``.
+
+        """
+        fv_M, c0, c1, c2, c3 = self.args
+        if argindex == 1:
+            return cosh((fv_M - c3)/c0)/(c0*c1)
+        elif argindex == 2:
+            return (c3 - fv_M)*cosh((fv_M - c3)/c0)/(c0**2*c1)
+        elif argindex == 3:
+            return (c2 - sinh((fv_M - c3)/c0))/c1**2
+        elif argindex == 4:
+            return -1/c1
+        elif argindex == 5:
+            return -cosh((fv_M - c3)/c0)/(c0*c1)
+
+        raise ArgumentIndexError(self, argindex)
+
+    def inverse(self, argindex=1):
+        """Inverse function.
+
+        Parameters
+        ==========
+
+        argindex : int
+            Value to start indexing the arguments at. Default is ``1``.
+
+        """
+        return FiberForceVelocityDeGroote2016
+
+    def _latex(self, printer):
+        """Print a LaTeX representation of the function defining the curve.
+
+        Parameters
+        ==========
+
+        printer : Printer
+            The printer to be used to print the LaTeX string representation.
+
+        """
+        fv_M = self.args[0]
+        _fv_M = printer._print(fv_M)
+        return r'\left( \operatorname{fv}^M \right)^{-1} \left( %s \right)' % _fv_M
+
+
+@dataclass(frozen=True)
+class CharacteristicCurveCollection:
+    """Simple data container to group together related characteristic curves."""
+    tendon_force_length: CharacteristicCurveFunction
+    tendon_force_length_inverse: CharacteristicCurveFunction
+    fiber_force_length_passive: CharacteristicCurveFunction
+    fiber_force_length_passive_inverse: CharacteristicCurveFunction
+    fiber_force_length_active: CharacteristicCurveFunction
+    fiber_force_velocity: CharacteristicCurveFunction
+    fiber_force_velocity_inverse: CharacteristicCurveFunction
+
+    def __iter__(self):
+        """Iterator support for ``CharacteristicCurveCollection``."""
+        yield self.tendon_force_length
+        yield self.tendon_force_length_inverse
+        yield self.fiber_force_length_passive
+        yield self.fiber_force_length_passive_inverse
+        yield self.fiber_force_length_active
+        yield self.fiber_force_velocity
+        yield self.fiber_force_velocity_inverse

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/biomechanics/tests/test_activation.py

@@ -0,0 +1,348 @@
+"""Tests for the ``sympy.physics.biomechanics.activation.py`` module."""
+
+import pytest
+
+from sympy import Symbol
+from sympy.core.numbers import Float, Integer, Rational
+from sympy.functions.elementary.hyperbolic import tanh
+from sympy.matrices import Matrix
+from sympy.matrices.dense import zeros
+from sympy.physics.mechanics import dynamicsymbols
+from sympy.physics.biomechanics import (
+    ActivationBase,
+    FirstOrderActivationDeGroote2016,
+    ZerothOrderActivation,
+)
+from sympy.physics.biomechanics._mixin import _NamedMixin
+from sympy.simplify.simplify import simplify
+
+
+class TestZerothOrderActivation:
+
+    @staticmethod
+    def test_class():
+        assert issubclass(ZerothOrderActivation, ActivationBase)
+        assert issubclass(ZerothOrderActivation, _NamedMixin)
+        assert ZerothOrderActivation.__name__ == 'ZerothOrderActivation'
+
+    @pytest.fixture(autouse=True)
+    def _zeroth_order_activation_fixture(self):
+        self.name = 'name'
+        self.e = dynamicsymbols('e_name')
+        self.instance = ZerothOrderActivation(self.name)
+
+    def test_instance(self):
+        instance = ZerothOrderActivation(self.name)
+        assert isinstance(instance, ZerothOrderActivation)
+
+    def test_with_defaults(self):
+        instance = ZerothOrderActivation.with_defaults(self.name)
+        assert isinstance(instance, ZerothOrderActivation)
+        assert instance == ZerothOrderActivation(self.name)
+
+    def test_name(self):
+        assert hasattr(self.instance, 'name')
+        assert self.instance.name == self.name
+
+    def test_order(self):
+        assert hasattr(self.instance, 'order')
+        assert self.instance.order == 0
+
+    def test_excitation_attribute(self):
+        assert hasattr(self.instance, 'e')
+        assert hasattr(self.instance, 'excitation')
+        e_expected = dynamicsymbols('e_name')
+        assert self.instance.e == e_expected
+        assert self.instance.excitation == e_expected
+        assert self.instance.e is self.instance.excitation
+
+    def test_activation_attribute(self):
+        assert hasattr(self.instance, 'a')
+        assert hasattr(self.instance, 'activation')
+        a_expected = dynamicsymbols('e_name')
+        assert self.instance.a == a_expected
+        assert self.instance.activation == a_expected
+        assert self.instance.a is self.instance.activation is self.instance.e
+
+    def test_state_vars_attribute(self):
+        assert hasattr(self.instance, 'x')
+        assert hasattr(self.instance, 'state_vars')
+        assert self.instance.x == self.instance.state_vars
+        x_expected = zeros(0, 1)
+        assert self.instance.x == x_expected
+        assert self.instance.state_vars == x_expected
+        assert isinstance(self.instance.x, Matrix)
+        assert isinstance(self.instance.state_vars, Matrix)
+        assert self.instance.x.shape == (0, 1)
+        assert self.instance.state_vars.shape == (0, 1)
+
+    def test_input_vars_attribute(self):
+        assert hasattr(self.instance, 'r')
+        assert hasattr(self.instance, 'input_vars')
+        assert self.instance.r == self.instance.input_vars
+        r_expected = Matrix([self.e])
+        assert self.instance.r == r_expected
+        assert self.instance.input_vars == r_expected
+        assert isinstance(self.instance.r, Matrix)
+        assert isinstance(self.instance.input_vars, Matrix)
+        assert self.instance.r.shape == (1, 1)
+        assert self.instance.input_vars.shape == (1, 1)
+
+    def test_constants_attribute(self):
+        assert hasattr(self.instance, 'p')
+        assert hasattr(self.instance, 'constants')
+        assert self.instance.p == self.instance.constants
+        p_expected = zeros(0, 1)
+        assert self.instance.p == p_expected
+        assert self.instance.constants == p_expected
+        assert isinstance(self.instance.p, Matrix)
+        assert isinstance(self.instance.constants, Matrix)
+        assert self.instance.p.shape == (0, 1)
+        assert self.instance.constants.shape == (0, 1)
+
+    def test_M_attribute(self):
+        assert hasattr(self.instance, 'M')
+        M_expected = Matrix([])
+        assert self.instance.M == M_expected
+        assert isinstance(self.instance.M, Matrix)
+        assert self.instance.M.shape == (0, 0)
+
+    def test_F(self):
+        assert hasattr(self.instance, 'F')
+        F_expected = zeros(0, 1)
+        assert self.instance.F == F_expected
+        assert isinstance(self.instance.F, Matrix)
+        assert self.instance.F.shape == (0, 1)
+
+    def test_rhs(self):
+        assert hasattr(self.instance, 'rhs')
+        rhs_expected = zeros(0, 1)
+        rhs = self.instance.rhs()
+        assert rhs == rhs_expected
+        assert isinstance(rhs, Matrix)
+        assert rhs.shape == (0, 1)
+
+    def test_repr(self):
+        expected = 'ZerothOrderActivation(\'name\')'
+        assert repr(self.instance) == expected
+
+
+class TestFirstOrderActivationDeGroote2016:
+
+    @staticmethod
+    def test_class():
+        assert issubclass(FirstOrderActivationDeGroote2016, ActivationBase)
+        assert issubclass(FirstOrderActivationDeGroote2016, _NamedMixin)
+        assert FirstOrderActivationDeGroote2016.__name__ == 'FirstOrderActivationDeGroote2016'
+
+    @pytest.fixture(autouse=True)
+    def _first_order_activation_de_groote_2016_fixture(self):
+        self.name = 'name'
+        self.e = dynamicsymbols('e_name')
+        self.a = dynamicsymbols('a_name')
+        self.tau_a = Symbol('tau_a')
+        self.tau_d = Symbol('tau_d')
+        self.b = Symbol('b')
+        self.instance = FirstOrderActivationDeGroote2016(
+            self.name,
+            self.tau_a,
+            self.tau_d,
+            self.b,
+        )
+
+    def test_instance(self):
+        instance = FirstOrderActivationDeGroote2016(self.name)
+        assert isinstance(instance, FirstOrderActivationDeGroote2016)
+
+    def test_with_defaults(self):
+        instance = FirstOrderActivationDeGroote2016.with_defaults(self.name)
+        assert isinstance(instance, FirstOrderActivationDeGroote2016)
+        assert instance.tau_a == Float('0.015')
+        assert instance.activation_time_constant == Float('0.015')
+        assert instance.tau_d == Float('0.060')
+        assert instance.deactivation_time_constant == Float('0.060')
+        assert instance.b == Float('10.0')
+        assert instance.smoothing_rate == Float('10.0')
+
+    def test_name(self):
+        assert hasattr(self.instance, 'name')
+        assert self.instance.name == self.name
+
+    def test_order(self):
+        assert hasattr(self.instance, 'order')
+        assert self.instance.order == 1
+
+    def test_excitation(self):
+        assert hasattr(self.instance, 'e')
+        assert hasattr(self.instance, 'excitation')
+        e_expected = dynamicsymbols('e_name')
+        assert self.instance.e == e_expected
+        assert self.instance.excitation == e_expected
+        assert self.instance.e is self.instance.excitation
+
+    def test_excitation_is_immutable(self):
+        with pytest.raises(AttributeError):
+            self.instance.e = None
+        with pytest.raises(AttributeError):
+            self.instance.excitation = None
+
+    def test_activation(self):
+        assert hasattr(self.instance, 'a')
+        assert hasattr(self.instance, 'activation')
+        a_expected = dynamicsymbols('a_name')
+        assert self.instance.a == a_expected
+        assert self.instance.activation == a_expected
+
+    def test_activation_is_immutable(self):
+        with pytest.raises(AttributeError):
+            self.instance.a = None
+        with pytest.raises(AttributeError):
+            self.instance.activation = None
+
+    @pytest.mark.parametrize(
+        'tau_a, expected',
+        [
+            (None, Symbol('tau_a_name')),
+            (Symbol('tau_a'), Symbol('tau_a')),
+            (Float('0.015'), Float('0.015')),
+        ]
+    )
+    def test_activation_time_constant(self, tau_a, expected):
+        instance = FirstOrderActivationDeGroote2016(
+            'name', activation_time_constant=tau_a,
+        )
+        assert instance.tau_a == expected
+        assert instance.activation_time_constant == expected
+        assert instance.tau_a is instance.activation_time_constant
+
+    def test_activation_time_constant_is_immutable(self):
+        with pytest.raises(AttributeError):
+            self.instance.tau_a = None
+        with pytest.raises(AttributeError):
+            self.instance.activation_time_constant = None
+
+    @pytest.mark.parametrize(
+        'tau_d, expected',
+        [
+            (None, Symbol('tau_d_name')),
+            (Symbol('tau_d'), Symbol('tau_d')),
+            (Float('0.060'), Float('0.060')),
+        ]
+    )
+    def test_deactivation_time_constant(self, tau_d, expected):
+        instance = FirstOrderActivationDeGroote2016(
+            'name', deactivation_time_constant=tau_d,
+        )
+        assert instance.tau_d == expected
+        assert instance.deactivation_time_constant == expected
+        assert instance.tau_d is instance.deactivation_time_constant
+
+    def test_deactivation_time_constant_is_immutable(self):
+        with pytest.raises(AttributeError):
+            self.instance.tau_d = None
+        with pytest.raises(AttributeError):
+            self.instance.deactivation_time_constant = None
+
+    @pytest.mark.parametrize(
+        'b, expected',
+        [
+            (None, Symbol('b_name')),
+            (Symbol('b'), Symbol('b')),
+            (Integer('10'), Integer('10')),
+        ]
+    )
+    def test_smoothing_rate(self, b, expected):
+        instance = FirstOrderActivationDeGroote2016(
+            'name', smoothing_rate=b,
+        )
+        assert instance.b == expected
+        assert instance.smoothing_rate == expected
+        assert instance.b is instance.smoothing_rate
+
+    def test_smoothing_rate_is_immutable(self):
+        with pytest.raises(AttributeError):
+            self.instance.b = None
+        with pytest.raises(AttributeError):
+            self.instance.smoothing_rate = None
+
+    def test_state_vars(self):
+        assert hasattr(self.instance, 'x')
+        assert hasattr(self.instance, 'state_vars')
+        assert self.instance.x == self.instance.state_vars
+        x_expected = Matrix([self.a])
+        assert self.instance.x == x_expected
+        assert self.instance.state_vars == x_expected
+        assert isinstance(self.instance.x, Matrix)
+        assert isinstance(self.instance.state_vars, Matrix)
+        assert self.instance.x.shape == (1, 1)
+        assert self.instance.state_vars.shape == (1, 1)
+
+    def test_input_vars(self):
+        assert hasattr(self.instance, 'r')
+        assert hasattr(self.instance, 'input_vars')
+        assert self.instance.r == self.instance.input_vars
+        r_expected = Matrix([self.e])
+        assert self.instance.r == r_expected
+        assert self.instance.input_vars == r_expected
+        assert isinstance(self.instance.r, Matrix)
+        assert isinstance(self.instance.input_vars, Matrix)
+        assert self.instance.r.shape == (1, 1)
+        assert self.instance.input_vars.shape == (1, 1)
+
+    def test_constants(self):
+        assert hasattr(self.instance, 'p')
+        assert hasattr(self.instance, 'constants')
+        assert self.instance.p == self.instance.constants
+        p_expected = Matrix([self.tau_a, self.tau_d, self.b])
+        assert self.instance.p == p_expected
+        assert self.instance.constants == p_expected
+        assert isinstance(self.instance.p, Matrix)
+        assert isinstance(self.instance.constants, Matrix)
+        assert self.instance.p.shape == (3, 1)
+        assert self.instance.constants.shape == (3, 1)
+
+    def test_M(self):
+        assert hasattr(self.instance, 'M')
+        M_expected = Matrix([1])
+        assert self.instance.M == M_expected
+        assert isinstance(self.instance.M, Matrix)
+        assert self.instance.M.shape == (1, 1)
+
+    def test_F(self):
+        assert hasattr(self.instance, 'F')
+        da_expr = (
+            ((1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
+            *(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
+            + ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
+            *(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a))))
+            *(self.e - self.a)
+        )
+        F_expected = Matrix([da_expr])
+        assert self.instance.F == F_expected
+        assert isinstance(self.instance.F, Matrix)
+        assert self.instance.F.shape == (1, 1)
+
+    def test_rhs(self):
+        assert hasattr(self.instance, 'rhs')
+        da_expr = (
+            ((1/(self.tau_a*(Rational(1, 2) + Rational(3, 2)*self.a)))
+            *(Rational(1, 2) + Rational(1, 2)*tanh(self.b*(self.e - self.a)))
+            + ((Rational(1, 2) + Rational(3, 2)*self.a)/self.tau_d)
+            *(Rational(1, 2) - Rational(1, 2)*tanh(self.b*(self.e - self.a))))
+            *(self.e - self.a)
+        )
+        rhs_expected = Matrix([da_expr])
+        rhs = self.instance.rhs()
+        assert rhs == rhs_expected
+        assert isinstance(rhs, Matrix)
+        assert rhs.shape == (1, 1)
+        assert simplify(self.instance.M.solve(self.instance.F) - rhs) == zeros(1)
+
+    def test_repr(self):
+        expected = (
+            'FirstOrderActivationDeGroote2016(\'name\', '
+            'activation_time_constant=tau_a, '
+            'deactivation_time_constant=tau_d, '
+            'smoothing_rate=b)'
+        )
+        assert repr(self.instance) == expected

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/control/__init__.py

@@ -0,0 +1,16 @@
+from .lti import (TransferFunction, Series, MIMOSeries, Parallel, MIMOParallel,
+    Feedback, MIMOFeedback, TransferFunctionMatrix, StateSpace, gbt, bilinear, forward_diff,
+    backward_diff, phase_margin, gain_margin)
+from .control_plots import (pole_zero_numerical_data, pole_zero_plot, step_response_numerical_data,
+    step_response_plot, impulse_response_numerical_data, impulse_response_plot, ramp_response_numerical_data,
+    ramp_response_plot, bode_magnitude_numerical_data, bode_phase_numerical_data, bode_magnitude_plot,
+    bode_phase_plot, bode_plot)
+
+__all__ = ['TransferFunction', 'Series', 'MIMOSeries', 'Parallel',
+    'MIMOParallel', 'Feedback', 'MIMOFeedback', 'TransferFunctionMatrix', 'StateSpace',
+    'gbt', 'bilinear', 'forward_diff', 'backward_diff', 'phase_margin', 'gain_margin',
+    'pole_zero_numerical_data', 'pole_zero_plot', 'step_response_numerical_data',
+    'step_response_plot', 'impulse_response_numerical_data', 'impulse_response_plot',
+    'ramp_response_numerical_data', 'ramp_response_plot',
+    'bode_magnitude_numerical_data', 'bode_phase_numerical_data',
+    'bode_magnitude_plot', 'bode_phase_plot', 'bode_plot']

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/control/control_plots.py

@@ -0,0 +1,978 @@
+from sympy.core.numbers import I, pi
+from sympy.functions.elementary.exponential import (exp, log)
+from sympy.polys.partfrac import apart
+from sympy.core.symbol import Dummy
+from sympy.external import import_module
+from sympy.functions import arg, Abs
+from sympy.integrals.laplace import _fast_inverse_laplace
+from sympy.physics.control.lti import SISOLinearTimeInvariant
+from sympy.plotting.series import LineOver1DRangeSeries
+from sympy.polys.polytools import Poly
+from sympy.printing.latex import latex
+
+__all__ = ['pole_zero_numerical_data', 'pole_zero_plot',
+    'step_response_numerical_data', 'step_response_plot',
+    'impulse_response_numerical_data', 'impulse_response_plot',
+    'ramp_response_numerical_data', 'ramp_response_plot',
+    'bode_magnitude_numerical_data', 'bode_phase_numerical_data',
+    'bode_magnitude_plot', 'bode_phase_plot', 'bode_plot']
+
+matplotlib = import_module(
+        'matplotlib', import_kwargs={'fromlist': ['pyplot']},
+        catch=(RuntimeError,))
+
+numpy = import_module('numpy')
+
+if matplotlib:
+    plt = matplotlib.pyplot
+
+if numpy:
+    np = numpy  # Matplotlib already has numpy as a compulsory dependency. No need to install it separately.
+
+
+def _check_system(system):
+    """Function to check whether the dynamical system passed for plots is
+    compatible or not."""
+    if not isinstance(system, SISOLinearTimeInvariant):
+        raise NotImplementedError("Only SISO LTI systems are currently supported.")
+    sys = system.to_expr()
+    len_free_symbols = len(sys.free_symbols)
+    if len_free_symbols > 1:
+        raise ValueError("Extra degree of freedom found. Make sure"
+            " that there are no free symbols in the dynamical system other"
+            " than the variable of Laplace transform.")
+    if sys.has(exp):
+        # Should test that exp is not part of a constant, in which case
+        # no exception is required, compare exp(s) with s*exp(1)
+        raise NotImplementedError("Time delay terms are not supported.")
+
+
+def pole_zero_numerical_data(system):
+    """
+    Returns the numerical data of poles and zeros of the system.
+    It is internally used by ``pole_zero_plot`` to get the data
+    for plotting poles and zeros. Users can use this data to further
+    analyse the dynamics of the system or plot using a different
+    backend/plotting-module.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant
+        The system for which the pole-zero data is to be computed.
+
+    Returns
+    =======
+
+    tuple : (zeros, poles)
+        zeros = Zeros of the system. NumPy array of complex numbers.
+        poles = Poles of the system. NumPy array of complex numbers.
+
+    Raises
+    ======
+
+    NotImplementedError
+        When a SISO LTI system is not passed.
+
+        When time delay terms are present in the system.
+
+    ValueError
+        When more than one free symbol is present in the system.
+        The only variable in the transfer function should be
+        the variable of the Laplace transform.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import s
+    >>> from sympy.physics.control.lti import TransferFunction
+    >>> from sympy.physics.control.control_plots import pole_zero_numerical_data
+    >>> tf1 = TransferFunction(s**2 + 1, s**4 + 4*s**3 + 6*s**2 + 5*s + 2, s)
+    >>> pole_zero_numerical_data(tf1)   # doctest: +SKIP
+    ([-0.+1.j  0.-1.j], [-2. +0.j        -0.5+0.8660254j -0.5-0.8660254j -1. +0.j       ])
+
+    See Also
+    ========
+
+    pole_zero_plot
+
+    """
+    _check_system(system)
+    system = system.doit()  # Get the equivalent TransferFunction object.
+
+    num_poly = Poly(system.num, system.var).all_coeffs()
+    den_poly = Poly(system.den, system.var).all_coeffs()
+
+    num_poly = np.array(num_poly, dtype=np.complex128)
+    den_poly = np.array(den_poly, dtype=np.complex128)
+
+    zeros = np.roots(num_poly)
+    poles = np.roots(den_poly)
+
+    return zeros, poles
+
+
+def pole_zero_plot(system, pole_color='blue', pole_markersize=10,
+    zero_color='orange', zero_markersize=7, grid=True, show_axes=True,
+    show=True, **kwargs):
+    r"""
+    Returns the Pole-Zero plot (also known as PZ Plot or PZ Map) of a system.
+
+    A Pole-Zero plot is a graphical representation of a system's poles and
+    zeros. It is plotted on a complex plane, with circular markers representing
+    the system's zeros and 'x' shaped markers representing the system's poles.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant type systems
+        The system for which the pole-zero plot is to be computed.
+    pole_color : str, tuple, optional
+        The color of the pole points on the plot. Default color
+        is blue. The color can be provided as a matplotlib color string,
+        or a 3-tuple of floats each in the 0-1 range.
+    pole_markersize : Number, optional
+        The size of the markers used to mark the poles in the plot.
+        Default pole markersize is 10.
+    zero_color : str, tuple, optional
+        The color of the zero points on the plot. Default color
+        is orange. The color can be provided as a matplotlib color string,
+        or a 3-tuple of floats each in the 0-1 range.
+    zero_markersize : Number, optional
+        The size of the markers used to mark the zeros in the plot.
+        Default zero markersize is 7.
+    grid : boolean, optional
+        If ``True``, the plot will have a grid. Defaults to True.
+    show_axes : boolean, optional
+        If ``True``, the coordinate axes will be shown. Defaults to False.
+    show : boolean, optional
+        If ``True``, the plot will be displayed otherwise
+        the equivalent matplotlib ``plot`` object will be returned.
+        Defaults to True.
+
+    Examples
+    ========
+
+    .. plot::
+        :context: close-figs
+        :format: doctest
+        :include-source: True
+
+        >>> from sympy.abc import s
+        >>> from sympy.physics.control.lti import TransferFunction
+        >>> from sympy.physics.control.control_plots import pole_zero_plot
+        >>> tf1 = TransferFunction(s**2 + 1, s**4 + 4*s**3 + 6*s**2 + 5*s + 2, s)
+        >>> pole_zero_plot(tf1)   # doctest: +SKIP
+
+    See Also
+    ========
+
+    pole_zero_numerical_data
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Pole%E2%80%93zero_plot
+
+    """
+    zeros, poles = pole_zero_numerical_data(system)
+
+    zero_real = np.real(zeros)
+    zero_imag = np.imag(zeros)
+
+    pole_real = np.real(poles)
+    pole_imag = np.imag(poles)
+
+    plt.plot(pole_real, pole_imag, 'x', mfc='none',
+        markersize=pole_markersize, color=pole_color)
+    plt.plot(zero_real, zero_imag, 'o', markersize=zero_markersize,
+        color=zero_color)
+    plt.xlabel('Real Axis')
+    plt.ylabel('Imaginary Axis')
+    plt.title(f'Poles and Zeros of ${latex(system)}$', pad=20)
+
+    if grid:
+        plt.grid()
+    if show_axes:
+        plt.axhline(0, color='black')
+        plt.axvline(0, color='black')
+    if show:
+        plt.show()
+        return
+
+    return plt
+
+
+def step_response_numerical_data(system, prec=8, lower_limit=0,
+    upper_limit=10, **kwargs):
+    """
+    Returns the numerical values of the points in the step response plot
+    of a SISO continuous-time system. By default, adaptive sampling
+    is used. If the user wants to instead get an uniformly
+    sampled response, then ``adaptive`` kwarg should be passed ``False``
+    and ``n`` must be passed as additional kwargs.
+    Refer to the parameters of class :class:`sympy.plotting.series.LineOver1DRangeSeries`
+    for more details.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant
+        The system for which the unit step response data is to be computed.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    lower_limit : Number, optional
+        The lower limit of the plot range. Defaults to 0.
+    upper_limit : Number, optional
+        The upper limit of the plot range. Defaults to 10.
+    kwargs :
+        Additional keyword arguments are passed to the underlying
+        :class:`sympy.plotting.series.LineOver1DRangeSeries` class.
+
+    Returns
+    =======
+
+    tuple : (x, y)
+        x = Time-axis values of the points in the step response. NumPy array.
+        y = Amplitude-axis values of the points in the step response. NumPy array.
+
+    Raises
+    ======
+
+    NotImplementedError
+        When a SISO LTI system is not passed.
+
+        When time delay terms are present in the system.
+
+    ValueError
+        When more than one free symbol is present in the system.
+        The only variable in the transfer function should be
+        the variable of the Laplace transform.
+
+        When ``lower_limit`` parameter is less than 0.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import s
+    >>> from sympy.physics.control.lti import TransferFunction
+    >>> from sympy.physics.control.control_plots import step_response_numerical_data
+    >>> tf1 = TransferFunction(s, s**2 + 5*s + 8, s)
+    >>> step_response_numerical_data(tf1)   # doctest: +SKIP
+    ([0.0, 0.025413462339411542, 0.0484508722725343, ... , 9.670250533855183, 9.844291913708725, 10.0],
+    [0.0, 0.023844582399907256, 0.042894276802320226, ..., 6.828770759094287e-12, 6.456457160755703e-12])
+
+    See Also
+    ========
+
+    step_response_plot
+
+    """
+    if lower_limit < 0:
+        raise ValueError("Lower limit of time must be greater "
+            "than or equal to zero.")
+    _check_system(system)
+    _x = Dummy("x")
+    expr = system.to_expr()/(system.var)
+    expr = apart(expr, system.var, full=True)
+    _y = _fast_inverse_laplace(expr, system.var, _x).evalf(prec)
+    return LineOver1DRangeSeries(_y, (_x, lower_limit, upper_limit),
+        **kwargs).get_points()
+
+
+def step_response_plot(system, color='b', prec=8, lower_limit=0,
+    upper_limit=10, show_axes=False, grid=True, show=True, **kwargs):
+    r"""
+    Returns the unit step response of a continuous-time system. It is
+    the response of the system when the input signal is a step function.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant type
+        The LTI SISO system for which the Step Response is to be computed.
+    color : str, tuple, optional
+        The color of the line. Default is Blue.
+    show : boolean, optional
+        If ``True``, the plot will be displayed otherwise
+        the equivalent matplotlib ``plot`` object will be returned.
+        Defaults to True.
+    lower_limit : Number, optional
+        The lower limit of the plot range. Defaults to 0.
+    upper_limit : Number, optional
+        The upper limit of the plot range. Defaults to 10.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    show_axes : boolean, optional
+        If ``True``, the coordinate axes will be shown. Defaults to False.
+    grid : boolean, optional
+        If ``True``, the plot will have a grid. Defaults to True.
+
+    Examples
+    ========
+
+    .. plot::
+        :context: close-figs
+        :format: doctest
+        :include-source: True
+
+        >>> from sympy.abc import s
+        >>> from sympy.physics.control.lti import TransferFunction
+        >>> from sympy.physics.control.control_plots import step_response_plot
+        >>> tf1 = TransferFunction(8*s**2 + 18*s + 32, s**3 + 6*s**2 + 14*s + 24, s)
+        >>> step_response_plot(tf1)   # doctest: +SKIP
+
+    See Also
+    ========
+
+    impulse_response_plot, ramp_response_plot
+
+    References
+    ==========
+
+    .. [1] https://www.mathworks.com/help/control/ref/lti.step.html
+
+    """
+    x, y = step_response_numerical_data(system, prec=prec,
+        lower_limit=lower_limit, upper_limit=upper_limit, **kwargs)
+    plt.plot(x, y, color=color)
+    plt.xlabel('Time (s)')
+    plt.ylabel('Amplitude')
+    plt.title(f'Unit Step Response of ${latex(system)}$', pad=20)
+
+    if grid:
+        plt.grid()
+    if show_axes:
+        plt.axhline(0, color='black')
+        plt.axvline(0, color='black')
+    if show:
+        plt.show()
+        return
+
+    return plt
+
+
+def impulse_response_numerical_data(system, prec=8, lower_limit=0,
+    upper_limit=10, **kwargs):
+    """
+    Returns the numerical values of the points in the impulse response plot
+    of a SISO continuous-time system. By default, adaptive sampling
+    is used. If the user wants to instead get an uniformly
+    sampled response, then ``adaptive`` kwarg should be passed ``False``
+    and ``n`` must be passed as additional kwargs.
+    Refer to the parameters of class :class:`sympy.plotting.series.LineOver1DRangeSeries`
+    for more details.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant
+        The system for which the impulse response data is to be computed.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    lower_limit : Number, optional
+        The lower limit of the plot range. Defaults to 0.
+    upper_limit : Number, optional
+        The upper limit of the plot range. Defaults to 10.
+    kwargs :
+        Additional keyword arguments are passed to the underlying
+        :class:`sympy.plotting.series.LineOver1DRangeSeries` class.
+
+    Returns
+    =======
+
+    tuple : (x, y)
+        x = Time-axis values of the points in the impulse response. NumPy array.
+        y = Amplitude-axis values of the points in the impulse response. NumPy array.
+
+    Raises
+    ======
+
+    NotImplementedError
+        When a SISO LTI system is not passed.
+
+        When time delay terms are present in the system.
+
+    ValueError
+        When more than one free symbol is present in the system.
+        The only variable in the transfer function should be
+        the variable of the Laplace transform.
+
+        When ``lower_limit`` parameter is less than 0.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import s
+    >>> from sympy.physics.control.lti import TransferFunction
+    >>> from sympy.physics.control.control_plots import impulse_response_numerical_data
+    >>> tf1 = TransferFunction(s, s**2 + 5*s + 8, s)
+    >>> impulse_response_numerical_data(tf1)   # doctest: +SKIP
+    ([0.0, 0.06616480200395854,... , 9.854500743565858, 10.0],
+    [0.9999999799999999, 0.7042848373025861,...,7.170748906965121e-13, -5.1901263495547205e-12])
+
+    See Also
+    ========
+
+    impulse_response_plot
+
+    """
+    if lower_limit < 0:
+        raise ValueError("Lower limit of time must be greater "
+            "than or equal to zero.")
+    _check_system(system)
+    _x = Dummy("x")
+    expr = system.to_expr()
+    expr = apart(expr, system.var, full=True)
+    _y = _fast_inverse_laplace(expr, system.var, _x).evalf(prec)
+    return LineOver1DRangeSeries(_y, (_x, lower_limit, upper_limit),
+        **kwargs).get_points()
+
+
+def impulse_response_plot(system, color='b', prec=8, lower_limit=0,
+    upper_limit=10, show_axes=False, grid=True, show=True, **kwargs):
+    r"""
+    Returns the unit impulse response (Input is the Dirac-Delta Function) of a
+    continuous-time system.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant type
+        The LTI SISO system for which the Impulse Response is to be computed.
+    color : str, tuple, optional
+        The color of the line. Default is Blue.
+    show : boolean, optional
+        If ``True``, the plot will be displayed otherwise
+        the equivalent matplotlib ``plot`` object will be returned.
+        Defaults to True.
+    lower_limit : Number, optional
+        The lower limit of the plot range. Defaults to 0.
+    upper_limit : Number, optional
+        The upper limit of the plot range. Defaults to 10.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    show_axes : boolean, optional
+        If ``True``, the coordinate axes will be shown. Defaults to False.
+    grid : boolean, optional
+        If ``True``, the plot will have a grid. Defaults to True.
+
+    Examples
+    ========
+
+    .. plot::
+        :context: close-figs
+        :format: doctest
+        :include-source: True
+
+        >>> from sympy.abc import s
+        >>> from sympy.physics.control.lti import TransferFunction
+        >>> from sympy.physics.control.control_plots import impulse_response_plot
+        >>> tf1 = TransferFunction(8*s**2 + 18*s + 32, s**3 + 6*s**2 + 14*s + 24, s)
+        >>> impulse_response_plot(tf1)   # doctest: +SKIP
+
+    See Also
+    ========
+
+    step_response_plot, ramp_response_plot
+
+    References
+    ==========
+
+    .. [1] https://www.mathworks.com/help/control/ref/dynamicsystem.impulse.html
+
+    """
+    x, y = impulse_response_numerical_data(system, prec=prec,
+        lower_limit=lower_limit, upper_limit=upper_limit, **kwargs)
+    plt.plot(x, y, color=color)
+    plt.xlabel('Time (s)')
+    plt.ylabel('Amplitude')
+    plt.title(f'Impulse Response of ${latex(system)}$', pad=20)
+
+    if grid:
+        plt.grid()
+    if show_axes:
+        plt.axhline(0, color='black')
+        plt.axvline(0, color='black')
+    if show:
+        plt.show()
+        return
+
+    return plt
+
+
+def ramp_response_numerical_data(system, slope=1, prec=8,
+    lower_limit=0, upper_limit=10, **kwargs):
+    """
+    Returns the numerical values of the points in the ramp response plot
+    of a SISO continuous-time system. By default, adaptive sampling
+    is used. If the user wants to instead get an uniformly
+    sampled response, then ``adaptive`` kwarg should be passed ``False``
+    and ``n`` must be passed as additional kwargs.
+    Refer to the parameters of class :class:`sympy.plotting.series.LineOver1DRangeSeries`
+    for more details.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant
+        The system for which the ramp response data is to be computed.
+    slope : Number, optional
+        The slope of the input ramp function. Defaults to 1.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    lower_limit : Number, optional
+        The lower limit of the plot range. Defaults to 0.
+    upper_limit : Number, optional
+        The upper limit of the plot range. Defaults to 10.
+    kwargs :
+        Additional keyword arguments are passed to the underlying
+        :class:`sympy.plotting.series.LineOver1DRangeSeries` class.
+
+    Returns
+    =======
+
+    tuple : (x, y)
+        x = Time-axis values of the points in the ramp response plot. NumPy array.
+        y = Amplitude-axis values of the points in the ramp response plot. NumPy array.
+
+    Raises
+    ======
+
+    NotImplementedError
+        When a SISO LTI system is not passed.
+
+        When time delay terms are present in the system.
+
+    ValueError
+        When more than one free symbol is present in the system.
+        The only variable in the transfer function should be
+        the variable of the Laplace transform.
+
+        When ``lower_limit`` parameter is less than 0.
+
+        When ``slope`` is negative.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import s
+    >>> from sympy.physics.control.lti import TransferFunction
+    >>> from sympy.physics.control.control_plots import ramp_response_numerical_data
+    >>> tf1 = TransferFunction(s, s**2 + 5*s + 8, s)
+    >>> ramp_response_numerical_data(tf1)   # doctest: +SKIP
+    (([0.0, 0.12166980856813935,..., 9.861246379582118, 10.0],
+    [1.4504508011325967e-09, 0.006046440489058766,..., 0.12499999999568202, 0.12499999999661349]))
+
+    See Also
+    ========
+
+    ramp_response_plot
+
+    """
+    if slope < 0:
+        raise ValueError("Slope must be greater than or equal"
+            " to zero.")
+    if lower_limit < 0:
+        raise ValueError("Lower limit of time must be greater "
+            "than or equal to zero.")
+    _check_system(system)
+    _x = Dummy("x")
+    expr = (slope*system.to_expr())/((system.var)**2)
+    expr = apart(expr, system.var, full=True)
+    _y = _fast_inverse_laplace(expr, system.var, _x).evalf(prec)
+    return LineOver1DRangeSeries(_y, (_x, lower_limit, upper_limit),
+        **kwargs).get_points()
+
+
+def ramp_response_plot(system, slope=1, color='b', prec=8, lower_limit=0,
+    upper_limit=10, show_axes=False, grid=True, show=True, **kwargs):
+    r"""
+    Returns the ramp response of a continuous-time system.
+
+    Ramp function is defined as the straight line
+    passing through origin ($f(x) = mx$). The slope of
+    the ramp function can be varied by the user and
+    the default value is 1.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant type
+        The LTI SISO system for which the Ramp Response is to be computed.
+    slope : Number, optional
+        The slope of the input ramp function. Defaults to 1.
+    color : str, tuple, optional
+        The color of the line. Default is Blue.
+    show : boolean, optional
+        If ``True``, the plot will be displayed otherwise
+        the equivalent matplotlib ``plot`` object will be returned.
+        Defaults to True.
+    lower_limit : Number, optional
+        The lower limit of the plot range. Defaults to 0.
+    upper_limit : Number, optional
+        The upper limit of the plot range. Defaults to 10.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    show_axes : boolean, optional
+        If ``True``, the coordinate axes will be shown. Defaults to False.
+    grid : boolean, optional
+        If ``True``, the plot will have a grid. Defaults to True.
+
+    Examples
+    ========
+
+    .. plot::
+        :context: close-figs
+        :format: doctest
+        :include-source: True
+
+        >>> from sympy.abc import s
+        >>> from sympy.physics.control.lti import TransferFunction
+        >>> from sympy.physics.control.control_plots import ramp_response_plot
+        >>> tf1 = TransferFunction(s, (s+4)*(s+8), s)
+        >>> ramp_response_plot(tf1, upper_limit=2)   # doctest: +SKIP
+
+    See Also
+    ========
+
+    step_response_plot, impulse_response_plot
+
+    References
+    ==========
+
+    .. [1] https://en.wikipedia.org/wiki/Ramp_function
+
+    """
+    x, y = ramp_response_numerical_data(system, slope=slope, prec=prec,
+        lower_limit=lower_limit, upper_limit=upper_limit, **kwargs)
+    plt.plot(x, y, color=color)
+    plt.xlabel('Time (s)')
+    plt.ylabel('Amplitude')
+    plt.title(f'Ramp Response of ${latex(system)}$ [Slope = {slope}]', pad=20)
+
+    if grid:
+        plt.grid()
+    if show_axes:
+        plt.axhline(0, color='black')
+        plt.axvline(0, color='black')
+    if show:
+        plt.show()
+        return
+
+    return plt
+
+
+def bode_magnitude_numerical_data(system, initial_exp=-5, final_exp=5, freq_unit='rad/sec', **kwargs):
+    """
+    Returns the numerical data of the Bode magnitude plot of the system.
+    It is internally used by ``bode_magnitude_plot`` to get the data
+    for plotting Bode magnitude plot. Users can use this data to further
+    analyse the dynamics of the system or plot using a different
+    backend/plotting-module.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant
+        The system for which the data is to be computed.
+    initial_exp : Number, optional
+        The initial exponent of 10 of the semilog plot. Defaults to -5.
+    final_exp : Number, optional
+        The final exponent of 10 of the semilog plot. Defaults to 5.
+    freq_unit : string, optional
+        User can choose between ``'rad/sec'`` (radians/second) and ``'Hz'`` (Hertz) as frequency units.
+
+    Returns
+    =======
+
+    tuple : (x, y)
+        x = x-axis values of the Bode magnitude plot.
+        y = y-axis values of the Bode magnitude plot.
+
+    Raises
+    ======
+
+    NotImplementedError
+        When a SISO LTI system is not passed.
+
+        When time delay terms are present in the system.
+
+    ValueError
+        When more than one free symbol is present in the system.
+        The only variable in the transfer function should be
+        the variable of the Laplace transform.
+
+        When incorrect frequency units are given as input.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import s
+    >>> from sympy.physics.control.lti import TransferFunction
+    >>> from sympy.physics.control.control_plots import bode_magnitude_numerical_data
+    >>> tf1 = TransferFunction(s**2 + 1, s**4 + 4*s**3 + 6*s**2 + 5*s + 2, s)
+    >>> bode_magnitude_numerical_data(tf1)   # doctest: +SKIP
+    ([1e-05, 1.5148378120533502e-05,..., 68437.36188804005, 100000.0],
+    [-6.020599914256786, -6.0205999155219505,..., -193.4117304087953, -200.00000000260573])
+
+    See Also
+    ========
+
+    bode_magnitude_plot, bode_phase_numerical_data
+
+    """
+    _check_system(system)
+    expr = system.to_expr()
+    freq_units = ('rad/sec', 'Hz')
+    if freq_unit not in freq_units:
+        raise ValueError('Only "rad/sec" and "Hz" are accepted frequency units.')
+
+    _w = Dummy("w", real=True)
+    if freq_unit == 'Hz':
+        repl = I*_w*2*pi
+    else:
+        repl = I*_w
+    w_expr = expr.subs({system.var: repl})
+
+    mag = 20*log(Abs(w_expr), 10)
+
+    x, y = LineOver1DRangeSeries(mag,
+        (_w, 10**initial_exp, 10**final_exp), xscale='log', **kwargs).get_points()
+
+    return x, y
+
+
+def bode_magnitude_plot(system, initial_exp=-5, final_exp=5,
+    color='b', show_axes=False, grid=True, show=True, freq_unit='rad/sec', **kwargs):
+    r"""
+    Returns the Bode magnitude plot of a continuous-time system.
+
+    See ``bode_plot`` for all the parameters.
+    """
+    x, y = bode_magnitude_numerical_data(system, initial_exp=initial_exp,
+        final_exp=final_exp, freq_unit=freq_unit)
+    plt.plot(x, y, color=color, **kwargs)
+    plt.xscale('log')
+
+
+    plt.xlabel('Frequency (%s) [Log Scale]' % freq_unit)
+    plt.ylabel('Magnitude (dB)')
+    plt.title(f'Bode Plot (Magnitude) of ${latex(system)}$', pad=20)
+
+    if grid:
+        plt.grid(True)
+    if show_axes:
+        plt.axhline(0, color='black')
+        plt.axvline(0, color='black')
+    if show:
+        plt.show()
+        return
+
+    return plt
+
+
+def bode_phase_numerical_data(system, initial_exp=-5, final_exp=5, freq_unit='rad/sec', phase_unit='rad', phase_unwrap = True, **kwargs):
+    """
+    Returns the numerical data of the Bode phase plot of the system.
+    It is internally used by ``bode_phase_plot`` to get the data
+    for plotting Bode phase plot. Users can use this data to further
+    analyse the dynamics of the system or plot using a different
+    backend/plotting-module.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant
+        The system for which the Bode phase plot data is to be computed.
+    initial_exp : Number, optional
+        The initial exponent of 10 of the semilog plot. Defaults to -5.
+    final_exp : Number, optional
+        The final exponent of 10 of the semilog plot. Defaults to 5.
+    freq_unit : string, optional
+        User can choose between ``'rad/sec'`` (radians/second) and '``'Hz'`` (Hertz) as frequency units.
+    phase_unit : string, optional
+        User can choose between ``'rad'`` (radians) and ``'deg'`` (degree) as phase units.
+    phase_unwrap : bool, optional
+        Set to ``True`` by default.
+
+    Returns
+    =======
+
+    tuple : (x, y)
+        x = x-axis values of the Bode phase plot.
+        y = y-axis values of the Bode phase plot.
+
+    Raises
+    ======
+
+    NotImplementedError
+        When a SISO LTI system is not passed.
+
+        When time delay terms are present in the system.
+
+    ValueError
+        When more than one free symbol is present in the system.
+        The only variable in the transfer function should be
+        the variable of the Laplace transform.
+
+        When incorrect frequency or phase units are given as input.
+
+    Examples
+    ========
+
+    >>> from sympy.abc import s
+    >>> from sympy.physics.control.lti import TransferFunction
+    >>> from sympy.physics.control.control_plots import bode_phase_numerical_data
+    >>> tf1 = TransferFunction(s**2 + 1, s**4 + 4*s**3 + 6*s**2 + 5*s + 2, s)
+    >>> bode_phase_numerical_data(tf1)   # doctest: +SKIP
+    ([1e-05, 1.4472354033813751e-05, 2.035581932165858e-05,..., 47577.3248186011, 67884.09326036123, 100000.0],
+    [-2.5000000000291665e-05, -3.6180885085e-05, -5.08895483066e-05,...,-3.1415085799262523, -3.14155265358979])
+
+    See Also
+    ========
+
+    bode_magnitude_plot, bode_phase_numerical_data
+
+    """
+    _check_system(system)
+    expr = system.to_expr()
+    freq_units = ('rad/sec', 'Hz')
+    phase_units = ('rad', 'deg')
+    if freq_unit not in freq_units:
+        raise ValueError('Only "rad/sec" and "Hz" are accepted frequency units.')
+    if phase_unit not in phase_units:
+        raise ValueError('Only "rad" and "deg" are accepted phase units.')
+
+    _w = Dummy("w", real=True)
+    if freq_unit == 'Hz':
+        repl = I*_w*2*pi
+    else:
+        repl = I*_w
+    w_expr = expr.subs({system.var: repl})
+
+    if phase_unit == 'deg':
+        phase = arg(w_expr)*180/pi
+    else:
+        phase = arg(w_expr)
+
+    x, y = LineOver1DRangeSeries(phase,
+        (_w, 10**initial_exp, 10**final_exp), xscale='log', **kwargs).get_points()
+
+    half = None
+    if phase_unwrap:
+        if(phase_unit == 'rad'):
+            half = pi
+        elif(phase_unit == 'deg'):
+            half = 180
+    if half:
+        unit = 2*half
+        for i in range(1, len(y)):
+            diff = y[i] - y[i - 1]
+            if diff > half:      # Jump from -half to half
+                y[i] = (y[i] - unit)
+            elif diff < -half:   # Jump from half to -half
+                y[i] = (y[i] + unit)
+
+    return x, y
+
+
+def bode_phase_plot(system, initial_exp=-5, final_exp=5,
+    color='b', show_axes=False, grid=True, show=True, freq_unit='rad/sec', phase_unit='rad', phase_unwrap=True, **kwargs):
+    r"""
+    Returns the Bode phase plot of a continuous-time system.
+
+    See ``bode_plot`` for all the parameters.
+    """
+    x, y = bode_phase_numerical_data(system, initial_exp=initial_exp,
+        final_exp=final_exp, freq_unit=freq_unit, phase_unit=phase_unit, phase_unwrap=phase_unwrap)
+    plt.plot(x, y, color=color, **kwargs)
+    plt.xscale('log')
+
+    plt.xlabel('Frequency (%s) [Log Scale]' % freq_unit)
+    plt.ylabel('Phase (%s)' % phase_unit)
+    plt.title(f'Bode Plot (Phase) of ${latex(system)}$', pad=20)
+
+    if grid:
+        plt.grid(True)
+    if show_axes:
+        plt.axhline(0, color='black')
+        plt.axvline(0, color='black')
+    if show:
+        plt.show()
+        return
+
+    return plt
+
+
+def bode_plot(system, initial_exp=-5, final_exp=5,
+    grid=True, show_axes=False, show=True, freq_unit='rad/sec', phase_unit='rad', phase_unwrap=True, **kwargs):
+    r"""
+    Returns the Bode phase and magnitude plots of a continuous-time system.
+
+    Parameters
+    ==========
+
+    system : SISOLinearTimeInvariant type
+        The LTI SISO system for which the Bode Plot is to be computed.
+    initial_exp : Number, optional
+        The initial exponent of 10 of the semilog plot. Defaults to -5.
+    final_exp : Number, optional
+        The final exponent of 10 of the semilog plot. Defaults to 5.
+    show : boolean, optional
+        If ``True``, the plot will be displayed otherwise
+        the equivalent matplotlib ``plot`` object will be returned.
+        Defaults to True.
+    prec : int, optional
+        The decimal point precision for the point coordinate values.
+        Defaults to 8.
+    grid : boolean, optional
+        If ``True``, the plot will have a grid. Defaults to True.
+    show_axes : boolean, optional
+        If ``True``, the coordinate axes will be shown. Defaults to False.
+    freq_unit : string, optional
+        User can choose between ``'rad/sec'`` (radians/second) and ``'Hz'`` (Hertz) as frequency units.
+    phase_unit : string, optional
+        User can choose between ``'rad'`` (radians) and ``'deg'`` (degree) as phase units.
+
+    Examples
+    ========
+
+    .. plot::
+        :context: close-figs
+        :format: doctest
+        :include-source: True
+
+        >>> from sympy.abc import s
+        >>> from sympy.physics.control.lti import TransferFunction
+        >>> from sympy.physics.control.control_plots import bode_plot
+        >>> tf1 = TransferFunction(1*s**2 + 0.1*s + 7.5, 1*s**4 + 0.12*s**3 + 9*s**2, s)
+        >>> bode_plot(tf1, initial_exp=0.2, final_exp=0.7)   # doctest: +SKIP
+
+    See Also
+    ========
+
+    bode_magnitude_plot, bode_phase_plot
+
+    """
+    plt.subplot(211)
+    mag = bode_magnitude_plot(system, initial_exp=initial_exp, final_exp=final_exp,
+        show=False, grid=grid, show_axes=show_axes,
+        freq_unit=freq_unit, **kwargs)
+    mag.title(f'Bode Plot of ${latex(system)}$', pad=20)
+    mag.xlabel(None)
+    plt.subplot(212)
+    bode_phase_plot(system, initial_exp=initial_exp, final_exp=final_exp,
+        show=False, grid=grid, show_axes=show_axes, freq_unit=freq_unit, phase_unit=phase_unit, phase_unwrap=phase_unwrap, **kwargs).title(None)
+
+    if show:
+        plt.show()
+        return
+
+    return plt

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/tests/test_physics_matrices.py

@@ -0,0 +1,84 @@
+from sympy.physics.matrices import msigma, mgamma, minkowski_tensor, pat_matrix, mdft
+from sympy.core.numbers import (I, Rational)
+from sympy.core.singleton import S
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.matrices.dense import (Matrix, eye, zeros)
+from sympy.testing.pytest import warns_deprecated_sympy
+
+
+def test_parallel_axis_theorem():
+    # This tests the parallel axis theorem matrix by comparing to test
+    # matrices.
+
+    # First case, 1 in all directions.
+    mat1 = Matrix(((2, -1, -1), (-1, 2, -1), (-1, -1, 2)))
+    assert pat_matrix(1, 1, 1, 1) == mat1
+    assert pat_matrix(2, 1, 1, 1) == 2*mat1
+
+    # Second case, 1 in x, 0 in all others
+    mat2 = Matrix(((0, 0, 0), (0, 1, 0), (0, 0, 1)))
+    assert pat_matrix(1, 1, 0, 0) == mat2
+    assert pat_matrix(2, 1, 0, 0) == 2*mat2
+
+    # Third case, 1 in y, 0 in all others
+    mat3 = Matrix(((1, 0, 0), (0, 0, 0), (0, 0, 1)))
+    assert pat_matrix(1, 0, 1, 0) == mat3
+    assert pat_matrix(2, 0, 1, 0) == 2*mat3
+
+    # Fourth case, 1 in z, 0 in all others
+    mat4 = Matrix(((1, 0, 0), (0, 1, 0), (0, 0, 0)))
+    assert pat_matrix(1, 0, 0, 1) == mat4
+    assert pat_matrix(2, 0, 0, 1) == 2*mat4
+
+
+def test_Pauli():
+    #this and the following test are testing both Pauli and Dirac matrices
+    #and also that the general Matrix class works correctly in a real world
+    #situation
+    sigma1 = msigma(1)
+    sigma2 = msigma(2)
+    sigma3 = msigma(3)
+
+    assert sigma1 == sigma1
+    assert sigma1 != sigma2
+
+    # sigma*I -> I*sigma    (see #354)
+    assert sigma1*sigma2 == sigma3*I
+    assert sigma3*sigma1 == sigma2*I
+    assert sigma2*sigma3 == sigma1*I
+
+    assert sigma1*sigma1 == eye(2)
+    assert sigma2*sigma2 == eye(2)
+    assert sigma3*sigma3 == eye(2)
+
+    assert sigma1*2*sigma1 == 2*eye(2)
+    assert sigma1*sigma3*sigma1 == -sigma3
+
+
+def test_Dirac():
+    gamma0 = mgamma(0)
+    gamma1 = mgamma(1)
+    gamma2 = mgamma(2)
+    gamma3 = mgamma(3)
+    gamma5 = mgamma(5)
+
+    # gamma*I -> I*gamma    (see #354)
+    assert gamma5 == gamma0 * gamma1 * gamma2 * gamma3 * I
+    assert gamma1 * gamma2 + gamma2 * gamma1 == zeros(4)
+    assert gamma0 * gamma0 == eye(4) * minkowski_tensor[0, 0]
+    assert gamma2 * gamma2 != eye(4) * minkowski_tensor[0, 0]
+    assert gamma2 * gamma2 == eye(4) * minkowski_tensor[2, 2]
+
+    assert mgamma(5, True) == \
+        mgamma(0, True)*mgamma(1, True)*mgamma(2, True)*mgamma(3, True)*I
+
+def test_mdft():
+    with warns_deprecated_sympy():
+        assert mdft(1) == Matrix([[1]])
+    with warns_deprecated_sympy():
+        assert mdft(2) == 1/sqrt(2)*Matrix([[1,1],[1,-1]])
+    with warns_deprecated_sympy():
+        assert mdft(4) == Matrix([[S.Half,  S.Half,  S.Half, S.Half],
+                                  [S.Half, -I/2, Rational(-1,2),  I/2],
+                                  [S.Half, Rational(-1,2),  S.Half, Rational(-1,2)],
+                                  [S.Half,  I/2, Rational(-1,2), -I/2]])

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/__init__.py

@@ -0,0 +1,453 @@
+# isort:skip_file
+"""
+Dimensional analysis and unit systems.
+
+This module defines dimension/unit systems and physical quantities. It is
+based on a group-theoretical construction where dimensions are represented as
+vectors (coefficients being the exponents), and units are defined as a dimension
+to which we added a scale.
+
+Quantities are built from a factor and a unit, and are the basic objects that
+one will use when doing computations.
+
+All objects except systems and prefixes can be used in SymPy expressions.
+Note that as part of a CAS, various objects do not combine automatically
+under operations.
+
+Details about the implementation can be found in the documentation, and we
+will not repeat all the explanations we gave there concerning our approach.
+Ideas about future developments can be found on the `Github wiki
+<https://github.com/sympy/sympy/wiki/Unit-systems>`_, and you should consult
+this page if you are willing to help.
+
+Useful functions:
+
+- ``find_unit``: easily lookup pre-defined units.
+- ``convert_to(expr, newunit)``: converts an expression into the same
+    expression expressed in another unit.
+
+"""
+
+from .dimensions import Dimension, DimensionSystem
+from .unitsystem import UnitSystem
+from .util import convert_to
+from .quantities import Quantity
+
+from .definitions.dimension_definitions import (
+    amount_of_substance, acceleration, action, area,
+    capacitance, charge, conductance, current, energy,
+    force, frequency, impedance, inductance, length,
+    luminous_intensity, magnetic_density,
+    magnetic_flux, mass, momentum, power, pressure, temperature, time,
+    velocity, voltage, volume
+)
+
+Unit = Quantity
+
+speed = velocity
+luminosity = luminous_intensity
+magnetic_flux_density = magnetic_density
+amount = amount_of_substance
+
+from .prefixes import (
+    # 10-power based:
+    yotta,
+    zetta,
+    exa,
+    peta,
+    tera,
+    giga,
+    mega,
+    kilo,
+    hecto,
+    deca,
+    deci,
+    centi,
+    milli,
+    micro,
+    nano,
+    pico,
+    femto,
+    atto,
+    zepto,
+    yocto,
+    # 2-power based:
+    kibi,
+    mebi,
+    gibi,
+    tebi,
+    pebi,
+    exbi,
+)
+
+from .definitions import (
+    percent, percents,
+    permille,
+    rad, radian, radians,
+    deg, degree, degrees,
+    sr, steradian, steradians,
+    mil, angular_mil, angular_mils,
+    m, meter, meters,
+    kg, kilogram, kilograms,
+    s, second, seconds,
+    A, ampere, amperes,
+    K, kelvin, kelvins,
+    mol, mole, moles,
+    cd, candela, candelas,
+    g, gram, grams,
+    mg, milligram, milligrams,
+    ug, microgram, micrograms,
+    t, tonne, metric_ton,
+    newton, newtons, N,
+    joule, joules, J,
+    watt, watts, W,
+    pascal, pascals, Pa, pa,
+    hertz, hz, Hz,
+    coulomb, coulombs, C,
+    volt, volts, v, V,
+    ohm, ohms,
+    siemens, S, mho, mhos,
+    farad, farads, F,
+    henry, henrys, H,
+    tesla, teslas, T,
+    weber, webers, Wb, wb,
+    optical_power, dioptre, D,
+    lux, lx,
+    katal, kat,
+    gray, Gy,
+    becquerel, Bq,
+    km, kilometer, kilometers,
+    dm, decimeter, decimeters,
+    cm, centimeter, centimeters,
+    mm, millimeter, millimeters,
+    um, micrometer, micrometers, micron, microns,
+    nm, nanometer, nanometers,
+    pm, picometer, picometers,
+    ft, foot, feet,
+    inch, inches,
+    yd, yard, yards,
+    mi, mile, miles,
+    nmi, nautical_mile, nautical_miles,
+    angstrom, angstroms,
+    ha, hectare,
+    l, L, liter, liters,
+    dl, dL, deciliter, deciliters,
+    cl, cL, centiliter, centiliters,
+    ml, mL, milliliter, milliliters,
+    ms, millisecond, milliseconds,
+    us, microsecond, microseconds,
+    ns, nanosecond, nanoseconds,
+    ps, picosecond, picoseconds,
+    minute, minutes,
+    h, hour, hours,
+    day, days,
+    anomalistic_year, anomalistic_years,
+    sidereal_year, sidereal_years,
+    tropical_year, tropical_years,
+    common_year, common_years,
+    julian_year, julian_years,
+    draconic_year, draconic_years,
+    gaussian_year, gaussian_years,
+    full_moon_cycle, full_moon_cycles,
+    year, years,
+    G, gravitational_constant,
+    c, speed_of_light,
+    elementary_charge,
+    hbar,
+    planck,
+    eV, electronvolt, electronvolts,
+    avogadro_number,
+    avogadro, avogadro_constant,
+    boltzmann, boltzmann_constant,
+    stefan, stefan_boltzmann_constant,
+    R, molar_gas_constant,
+    faraday_constant,
+    josephson_constant,
+    von_klitzing_constant,
+    Da, dalton, amu, amus, atomic_mass_unit, atomic_mass_constant,
+    me, electron_rest_mass,
+    gee, gees, acceleration_due_to_gravity,
+    u0, magnetic_constant, vacuum_permeability,
+    e0, electric_constant, vacuum_permittivity,
+    Z0, vacuum_impedance,
+    coulomb_constant, electric_force_constant,
+    atmosphere, atmospheres, atm,
+    kPa,
+    bar, bars,
+    pound, pounds,
+    psi,
+    dHg0,
+    mmHg, torr,
+    mmu, mmus, milli_mass_unit,
+    quart, quarts,
+    ly, lightyear, lightyears,
+    au, astronomical_unit, astronomical_units,
+    planck_mass,
+    planck_time,
+    planck_temperature,
+    planck_length,
+    planck_charge,
+    planck_area,
+    planck_volume,
+    planck_momentum,
+    planck_energy,
+    planck_force,
+    planck_power,
+    planck_density,
+    planck_energy_density,
+    planck_intensity,
+    planck_angular_frequency,
+    planck_pressure,
+    planck_current,
+    planck_voltage,
+    planck_impedance,
+    planck_acceleration,
+    bit, bits,
+    byte,
+    kibibyte, kibibytes,
+    mebibyte, mebibytes,
+    gibibyte, gibibytes,
+    tebibyte, tebibytes,
+    pebibyte, pebibytes,
+    exbibyte, exbibytes,
+)
+
+from .systems import (
+    mks, mksa, si
+)
+
+
+def find_unit(quantity, unit_system="SI"):
+    """
+    Return a list of matching units or dimension names.
+
+    - If ``quantity`` is a string -- units/dimensions containing the string
+    `quantity`.
+    - If ``quantity`` is a unit or dimension -- units having matching base
+    units or dimensions.
+
+    Examples
+    ========
+
+    >>> from sympy.physics import units as u
+    >>> u.find_unit('charge')
+    ['C', 'coulomb', 'coulombs', 'planck_charge', 'elementary_charge']
+    >>> u.find_unit(u.charge)
+    ['C', 'coulomb', 'coulombs', 'planck_charge', 'elementary_charge']
+    >>> u.find_unit("ampere")
+    ['ampere', 'amperes']
+    >>> u.find_unit('angstrom')
+    ['angstrom', 'angstroms']
+    >>> u.find_unit('volt')
+    ['volt', 'volts', 'electronvolt', 'electronvolts', 'planck_voltage']
+    >>> u.find_unit(u.inch**3)[:9]
+    ['L', 'l', 'cL', 'cl', 'dL', 'dl', 'mL', 'ml', 'liter']
+    """
+    unit_system = UnitSystem.get_unit_system(unit_system)
+
+    import sympy.physics.units as u
+    rv = []
+    if isinstance(quantity, str):
+        rv = [i for i in dir(u) if quantity in i and isinstance(getattr(u, i), Quantity)]
+        dim = getattr(u, quantity)
+        if isinstance(dim, Dimension):
+            rv.extend(find_unit(dim))
+    else:
+        for i in sorted(dir(u)):
+            other = getattr(u, i)
+            if not isinstance(other, Quantity):
+                continue
+            if isinstance(quantity, Quantity):
+                if quantity.dimension == other.dimension:
+                    rv.append(str(i))
+            elif isinstance(quantity, Dimension):
+                if other.dimension == quantity:
+                    rv.append(str(i))
+            elif other.dimension == Dimension(unit_system.get_dimensional_expr(quantity)):
+                rv.append(str(i))
+    return sorted(set(rv), key=lambda x: (len(x), x))
+
+# NOTE: the old units module had additional variables:
+# 'density', 'illuminance', 'resistance'.
+# They were not dimensions, but units (old Unit class).
+
+__all__ = [
+    'Dimension', 'DimensionSystem',
+    'UnitSystem',
+    'convert_to',
+    'Quantity',
+
+    'amount_of_substance', 'acceleration', 'action', 'area',
+    'capacitance', 'charge', 'conductance', 'current', 'energy',
+    'force', 'frequency', 'impedance', 'inductance', 'length',
+    'luminous_intensity', 'magnetic_density',
+    'magnetic_flux', 'mass', 'momentum', 'power', 'pressure', 'temperature', 'time',
+    'velocity', 'voltage', 'volume',
+
+    'Unit',
+
+    'speed',
+    'luminosity',
+    'magnetic_flux_density',
+    'amount',
+
+    'yotta',
+    'zetta',
+    'exa',
+    'peta',
+    'tera',
+    'giga',
+    'mega',
+    'kilo',
+    'hecto',
+    'deca',
+    'deci',
+    'centi',
+    'milli',
+    'micro',
+    'nano',
+    'pico',
+    'femto',
+    'atto',
+    'zepto',
+    'yocto',
+
+    'kibi',
+    'mebi',
+    'gibi',
+    'tebi',
+    'pebi',
+    'exbi',
+
+    'percent', 'percents',
+    'permille',
+    'rad', 'radian', 'radians',
+    'deg', 'degree', 'degrees',
+    'sr', 'steradian', 'steradians',
+    'mil', 'angular_mil', 'angular_mils',
+    'm', 'meter', 'meters',
+    'kg', 'kilogram', 'kilograms',
+    's', 'second', 'seconds',
+    'A', 'ampere', 'amperes',
+    'K', 'kelvin', 'kelvins',
+    'mol', 'mole', 'moles',
+    'cd', 'candela', 'candelas',
+    'g', 'gram', 'grams',
+    'mg', 'milligram', 'milligrams',
+    'ug', 'microgram', 'micrograms',
+    't', 'tonne', 'metric_ton',
+    'newton', 'newtons', 'N',
+    'joule', 'joules', 'J',
+    'watt', 'watts', 'W',
+    'pascal', 'pascals', 'Pa', 'pa',
+    'hertz', 'hz', 'Hz',
+    'coulomb', 'coulombs', 'C',
+    'volt', 'volts', 'v', 'V',
+    'ohm', 'ohms',
+    'siemens', 'S', 'mho', 'mhos',
+    'farad', 'farads', 'F',
+    'henry', 'henrys', 'H',
+    'tesla', 'teslas', 'T',
+    'weber', 'webers', 'Wb', 'wb',
+    'optical_power', 'dioptre', 'D',
+    'lux', 'lx',
+    'katal', 'kat',
+    'gray', 'Gy',
+    'becquerel', 'Bq',
+    'km', 'kilometer', 'kilometers',
+    'dm', 'decimeter', 'decimeters',
+    'cm', 'centimeter', 'centimeters',
+    'mm', 'millimeter', 'millimeters',
+    'um', 'micrometer', 'micrometers', 'micron', 'microns',
+    'nm', 'nanometer', 'nanometers',
+    'pm', 'picometer', 'picometers',
+    'ft', 'foot', 'feet',
+    'inch', 'inches',
+    'yd', 'yard', 'yards',
+    'mi', 'mile', 'miles',
+    'nmi', 'nautical_mile', 'nautical_miles',
+    'angstrom', 'angstroms',
+    'ha', 'hectare',
+    'l', 'L', 'liter', 'liters',
+    'dl', 'dL', 'deciliter', 'deciliters',
+    'cl', 'cL', 'centiliter', 'centiliters',
+    'ml', 'mL', 'milliliter', 'milliliters',
+    'ms', 'millisecond', 'milliseconds',
+    'us', 'microsecond', 'microseconds',
+    'ns', 'nanosecond', 'nanoseconds',
+    'ps', 'picosecond', 'picoseconds',
+    'minute', 'minutes',
+    'h', 'hour', 'hours',
+    'day', 'days',
+    'anomalistic_year', 'anomalistic_years',
+    'sidereal_year', 'sidereal_years',
+    'tropical_year', 'tropical_years',
+    'common_year', 'common_years',
+    'julian_year', 'julian_years',
+    'draconic_year', 'draconic_years',
+    'gaussian_year', 'gaussian_years',
+    'full_moon_cycle', 'full_moon_cycles',
+    'year', 'years',
+    'G', 'gravitational_constant',
+    'c', 'speed_of_light',
+    'elementary_charge',
+    'hbar',
+    'planck',
+    'eV', 'electronvolt', 'electronvolts',
+    'avogadro_number',
+    'avogadro', 'avogadro_constant',
+    'boltzmann', 'boltzmann_constant',
+    'stefan', 'stefan_boltzmann_constant',
+    'R', 'molar_gas_constant',
+    'faraday_constant',
+    'josephson_constant',
+    'von_klitzing_constant',
+    'Da', 'dalton', 'amu', 'amus', 'atomic_mass_unit', 'atomic_mass_constant',
+    'me', 'electron_rest_mass',
+    'gee', 'gees', 'acceleration_due_to_gravity',
+    'u0', 'magnetic_constant', 'vacuum_permeability',
+    'e0', 'electric_constant', 'vacuum_permittivity',
+    'Z0', 'vacuum_impedance',
+    'coulomb_constant', 'electric_force_constant',
+    'atmosphere', 'atmospheres', 'atm',
+    'kPa',
+    'bar', 'bars',
+    'pound', 'pounds',
+    'psi',
+    'dHg0',
+    'mmHg', 'torr',
+    'mmu', 'mmus', 'milli_mass_unit',
+    'quart', 'quarts',
+    'ly', 'lightyear', 'lightyears',
+    'au', 'astronomical_unit', 'astronomical_units',
+    'planck_mass',
+    'planck_time',
+    'planck_temperature',
+    'planck_length',
+    'planck_charge',
+    'planck_area',
+    'planck_volume',
+    'planck_momentum',
+    'planck_energy',
+    'planck_force',
+    'planck_power',
+    'planck_density',
+    'planck_energy_density',
+    'planck_intensity',
+    'planck_angular_frequency',
+    'planck_pressure',
+    'planck_current',
+    'planck_voltage',
+    'planck_impedance',
+    'planck_acceleration',
+    'bit', 'bits',
+    'byte',
+    'kibibyte', 'kibibytes',
+    'mebibyte', 'mebibytes',
+    'gibibyte', 'gibibytes',
+    'tebibyte', 'tebibytes',
+    'pebibyte', 'pebibytes',
+    'exbibyte', 'exbibytes',
+
+    'mks', 'mksa', 'si',
+]

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/definitions/__init__.py

@@ -0,0 +1,265 @@
+from .unit_definitions import (
+    percent, percents,
+    permille,
+    rad, radian, radians,
+    deg, degree, degrees,
+    sr, steradian, steradians,
+    mil, angular_mil, angular_mils,
+    m, meter, meters,
+    kg, kilogram, kilograms,
+    s, second, seconds,
+    A, ampere, amperes,
+    K, kelvin, kelvins,
+    mol, mole, moles,
+    cd, candela, candelas,
+    g, gram, grams,
+    mg, milligram, milligrams,
+    ug, microgram, micrograms,
+    t, tonne, metric_ton,
+    newton, newtons, N,
+    joule, joules, J,
+    watt, watts, W,
+    pascal, pascals, Pa, pa,
+    hertz, hz, Hz,
+    coulomb, coulombs, C,
+    volt, volts, v, V,
+    ohm, ohms,
+    siemens, S, mho, mhos,
+    farad, farads, F,
+    henry, henrys, H,
+    tesla, teslas, T,
+    weber, webers, Wb, wb,
+    optical_power, dioptre, D,
+    lux, lx,
+    katal, kat,
+    gray, Gy,
+    becquerel, Bq,
+    km, kilometer, kilometers,
+    dm, decimeter, decimeters,
+    cm, centimeter, centimeters,
+    mm, millimeter, millimeters,
+    um, micrometer, micrometers, micron, microns,
+    nm, nanometer, nanometers,
+    pm, picometer, picometers,
+    ft, foot, feet,
+    inch, inches,
+    yd, yard, yards,
+    mi, mile, miles,
+    nmi, nautical_mile, nautical_miles,
+    ha, hectare,
+    l, L, liter, liters,
+    dl, dL, deciliter, deciliters,
+    cl, cL, centiliter, centiliters,
+    ml, mL, milliliter, milliliters,
+    ms, millisecond, milliseconds,
+    us, microsecond, microseconds,
+    ns, nanosecond, nanoseconds,
+    ps, picosecond, picoseconds,
+    minute, minutes,
+    h, hour, hours,
+    day, days,
+    anomalistic_year, anomalistic_years,
+    sidereal_year, sidereal_years,
+    tropical_year, tropical_years,
+    common_year, common_years,
+    julian_year, julian_years,
+    draconic_year, draconic_years,
+    gaussian_year, gaussian_years,
+    full_moon_cycle, full_moon_cycles,
+    year, years,
+    G, gravitational_constant,
+    c, speed_of_light,
+    elementary_charge,
+    hbar,
+    planck,
+    eV, electronvolt, electronvolts,
+    avogadro_number,
+    avogadro, avogadro_constant,
+    boltzmann, boltzmann_constant,
+    stefan, stefan_boltzmann_constant,
+    R, molar_gas_constant,
+    faraday_constant,
+    josephson_constant,
+    von_klitzing_constant,
+    Da, dalton, amu, amus, atomic_mass_unit, atomic_mass_constant,
+    me, electron_rest_mass,
+    gee, gees, acceleration_due_to_gravity,
+    u0, magnetic_constant, vacuum_permeability,
+    e0, electric_constant, vacuum_permittivity,
+    Z0, vacuum_impedance,
+    coulomb_constant, coulombs_constant, electric_force_constant,
+    atmosphere, atmospheres, atm,
+    kPa, kilopascal,
+    bar, bars,
+    pound, pounds,
+    psi,
+    dHg0,
+    mmHg, torr,
+    mmu, mmus, milli_mass_unit,
+    quart, quarts,
+    angstrom, angstroms,
+    ly, lightyear, lightyears,
+    au, astronomical_unit, astronomical_units,
+    planck_mass,
+    planck_time,
+    planck_temperature,
+    planck_length,
+    planck_charge,
+    planck_area,
+    planck_volume,
+    planck_momentum,
+    planck_energy,
+    planck_force,
+    planck_power,
+    planck_density,
+    planck_energy_density,
+    planck_intensity,
+    planck_angular_frequency,
+    planck_pressure,
+    planck_current,
+    planck_voltage,
+    planck_impedance,
+    planck_acceleration,
+    bit, bits,
+    byte,
+    kibibyte, kibibytes,
+    mebibyte, mebibytes,
+    gibibyte, gibibytes,
+    tebibyte, tebibytes,
+    pebibyte, pebibytes,
+    exbibyte, exbibytes,
+    curie, rutherford
+)
+
+__all__ = [
+    'percent', 'percents',
+    'permille',
+    'rad', 'radian', 'radians',
+    'deg', 'degree', 'degrees',
+    'sr', 'steradian', 'steradians',
+    'mil', 'angular_mil', 'angular_mils',
+    'm', 'meter', 'meters',
+    'kg', 'kilogram', 'kilograms',
+    's', 'second', 'seconds',
+    'A', 'ampere', 'amperes',
+    'K', 'kelvin', 'kelvins',
+    'mol', 'mole', 'moles',
+    'cd', 'candela', 'candelas',
+    'g', 'gram', 'grams',
+    'mg', 'milligram', 'milligrams',
+    'ug', 'microgram', 'micrograms',
+    't', 'tonne', 'metric_ton',
+    'newton', 'newtons', 'N',
+    'joule', 'joules', 'J',
+    'watt', 'watts', 'W',
+    'pascal', 'pascals', 'Pa', 'pa',
+    'hertz', 'hz', 'Hz',
+    'coulomb', 'coulombs', 'C',
+    'volt', 'volts', 'v', 'V',
+    'ohm', 'ohms',
+    'siemens', 'S', 'mho', 'mhos',
+    'farad', 'farads', 'F',
+    'henry', 'henrys', 'H',
+    'tesla', 'teslas', 'T',
+    'weber', 'webers', 'Wb', 'wb',
+    'optical_power', 'dioptre', 'D',
+    'lux', 'lx',
+    'katal', 'kat',
+    'gray', 'Gy',
+    'becquerel', 'Bq',
+    'km', 'kilometer', 'kilometers',
+    'dm', 'decimeter', 'decimeters',
+    'cm', 'centimeter', 'centimeters',
+    'mm', 'millimeter', 'millimeters',
+    'um', 'micrometer', 'micrometers', 'micron', 'microns',
+    'nm', 'nanometer', 'nanometers',
+    'pm', 'picometer', 'picometers',
+    'ft', 'foot', 'feet',
+    'inch', 'inches',
+    'yd', 'yard', 'yards',
+    'mi', 'mile', 'miles',
+    'nmi', 'nautical_mile', 'nautical_miles',
+    'ha', 'hectare',
+    'l', 'L', 'liter', 'liters',
+    'dl', 'dL', 'deciliter', 'deciliters',
+    'cl', 'cL', 'centiliter', 'centiliters',
+    'ml', 'mL', 'milliliter', 'milliliters',
+    'ms', 'millisecond', 'milliseconds',
+    'us', 'microsecond', 'microseconds',
+    'ns', 'nanosecond', 'nanoseconds',
+    'ps', 'picosecond', 'picoseconds',
+    'minute', 'minutes',
+    'h', 'hour', 'hours',
+    'day', 'days',
+    'anomalistic_year', 'anomalistic_years',
+    'sidereal_year', 'sidereal_years',
+    'tropical_year', 'tropical_years',
+    'common_year', 'common_years',
+    'julian_year', 'julian_years',
+    'draconic_year', 'draconic_years',
+    'gaussian_year', 'gaussian_years',
+    'full_moon_cycle', 'full_moon_cycles',
+    'year', 'years',
+    'G', 'gravitational_constant',
+    'c', 'speed_of_light',
+    'elementary_charge',
+    'hbar',
+    'planck',
+    'eV', 'electronvolt', 'electronvolts',
+    'avogadro_number',
+    'avogadro', 'avogadro_constant',
+    'boltzmann', 'boltzmann_constant',
+    'stefan', 'stefan_boltzmann_constant',
+    'R', 'molar_gas_constant',
+    'faraday_constant',
+    'josephson_constant',
+    'von_klitzing_constant',
+    'Da', 'dalton', 'amu', 'amus', 'atomic_mass_unit', 'atomic_mass_constant',
+    'me', 'electron_rest_mass',
+    'gee', 'gees', 'acceleration_due_to_gravity',
+    'u0', 'magnetic_constant', 'vacuum_permeability',
+    'e0', 'electric_constant', 'vacuum_permittivity',
+    'Z0', 'vacuum_impedance',
+    'coulomb_constant', 'coulombs_constant', 'electric_force_constant',
+    'atmosphere', 'atmospheres', 'atm',
+    'kPa', 'kilopascal',
+    'bar', 'bars',
+    'pound', 'pounds',
+    'psi',
+    'dHg0',
+    'mmHg', 'torr',
+    'mmu', 'mmus', 'milli_mass_unit',
+    'quart', 'quarts',
+    'angstrom', 'angstroms',
+    'ly', 'lightyear', 'lightyears',
+    'au', 'astronomical_unit', 'astronomical_units',
+    'planck_mass',
+    'planck_time',
+    'planck_temperature',
+    'planck_length',
+    'planck_charge',
+    'planck_area',
+    'planck_volume',
+    'planck_momentum',
+    'planck_energy',
+    'planck_force',
+    'planck_power',
+    'planck_density',
+    'planck_energy_density',
+    'planck_intensity',
+    'planck_angular_frequency',
+    'planck_pressure',
+    'planck_current',
+    'planck_voltage',
+    'planck_impedance',
+    'planck_acceleration',
+    'bit', 'bits',
+    'byte',
+    'kibibyte', 'kibibytes',
+    'mebibyte', 'mebibytes',
+    'gibibyte', 'gibibytes',
+    'tebibyte', 'tebibytes',
+    'pebibyte', 'pebibytes',
+    'exbibyte', 'exbibytes',
+    'curie', 'rutherford',
+]

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/dimensions.py

@@ -0,0 +1,590 @@
+"""
+Definition of physical dimensions.
+
+Unit systems will be constructed on top of these dimensions.
+
+Most of the examples in the doc use MKS system and are presented from the
+computer point of view: from a human point, adding length to time is not legal
+in MKS but it is in natural system; for a computer in natural system there is
+no time dimension (but a velocity dimension instead) - in the basis - so the
+question of adding time to length has no meaning.
+"""
+
+from __future__ import annotations
+
+import collections
+from functools import reduce
+
+from sympy.core.basic import Basic
+from sympy.core.containers import (Dict, Tuple)
+from sympy.core.singleton import S
+from sympy.core.sorting import default_sort_key
+from sympy.core.symbol import Symbol
+from sympy.core.sympify import sympify
+from sympy.matrices.dense import Matrix
+from sympy.functions.elementary.trigonometric import TrigonometricFunction
+from sympy.core.expr import Expr
+from sympy.core.power import Pow
+
+
+class _QuantityMapper:
+
+    _quantity_scale_factors_global: dict[Expr, Expr] = {}
+    _quantity_dimensional_equivalence_map_global: dict[Expr, Expr] = {}
+    _quantity_dimension_global: dict[Expr, Expr] = {}
+
+    def __init__(self, *args, **kwargs):
+        self._quantity_dimension_map = {}
+        self._quantity_scale_factors = {}
+
+    def set_quantity_dimension(self, quantity, dimension):
+        """
+        Set the dimension for the quantity in a unit system.
+
+        If this relation is valid in every unit system, use
+        ``quantity.set_global_dimension(dimension)`` instead.
+        """
+        from sympy.physics.units import Quantity
+        dimension = sympify(dimension)
+        if not isinstance(dimension, Dimension):
+            if dimension == 1:
+                dimension = Dimension(1)
+            else:
+                raise ValueError("expected dimension or 1")
+        elif isinstance(dimension, Quantity):
+            dimension = self.get_quantity_dimension(dimension)
+        self._quantity_dimension_map[quantity] = dimension
+
+    def set_quantity_scale_factor(self, quantity, scale_factor):
+        """
+        Set the scale factor of a quantity relative to another quantity.
+
+        It should be used only once per quantity to just one other quantity,
+        the algorithm will then be able to compute the scale factors to all
+        other quantities.
+
+        In case the scale factor is valid in every unit system, please use
+        ``quantity.set_global_relative_scale_factor(scale_factor)`` instead.
+        """
+        from sympy.physics.units import Quantity
+        from sympy.physics.units.prefixes import Prefix
+        scale_factor = sympify(scale_factor)
+        # replace all prefixes by their ratio to canonical units:
+        scale_factor = scale_factor.replace(
+            lambda x: isinstance(x, Prefix),
+            lambda x: x.scale_factor
+        )
+        # replace all quantities by their ratio to canonical units:
+        scale_factor = scale_factor.replace(
+            lambda x: isinstance(x, Quantity),
+            lambda x: self.get_quantity_scale_factor(x)
+        )
+        self._quantity_scale_factors[quantity] = scale_factor
+
+    def get_quantity_dimension(self, unit):
+        from sympy.physics.units import Quantity
+        # First look-up the local dimension map, then the global one:
+        if unit in self._quantity_dimension_map:
+            return self._quantity_dimension_map[unit]
+        if unit in self._quantity_dimension_global:
+            return self._quantity_dimension_global[unit]
+        if unit in self._quantity_dimensional_equivalence_map_global:
+            dep_unit = self._quantity_dimensional_equivalence_map_global[unit]
+            if isinstance(dep_unit, Quantity):
+                return self.get_quantity_dimension(dep_unit)
+            else:
+                return Dimension(self.get_dimensional_expr(dep_unit))
+        if isinstance(unit, Quantity):
+            return Dimension(unit.name)
+        else:
+            return Dimension(1)
+
+    def get_quantity_scale_factor(self, unit):
+        if unit in self._quantity_scale_factors:
+            return self._quantity_scale_factors[unit]
+        if unit in self._quantity_scale_factors_global:
+            mul_factor, other_unit = self._quantity_scale_factors_global[unit]
+            return mul_factor*self.get_quantity_scale_factor(other_unit)
+        return S.One
+
+
+class Dimension(Expr):
+    """
+    This class represent the dimension of a physical quantities.
+
+    The ``Dimension`` constructor takes as parameters a name and an optional
+    symbol.
+
+    For example, in classical mechanics we know that time is different from
+    temperature and dimensions make this difference (but they do not provide
+    any measure of these quantites.
+
+        >>> from sympy.physics.units import Dimension
+        >>> length = Dimension('length')
+        >>> length
+        Dimension(length)
+        >>> time = Dimension('time')
+        >>> time
+        Dimension(time)
+
+    Dimensions can be composed using multiplication, division and
+    exponentiation (by a number) to give new dimensions. Addition and
+    subtraction is defined only when the two objects are the same dimension.
+
+        >>> velocity = length / time
+        >>> velocity
+        Dimension(length/time)
+
+    It is possible to use a dimension system object to get the dimensionsal
+    dependencies of a dimension, for example the dimension system used by the
+    SI units convention can be used:
+
+        >>> from sympy.physics.units.systems.si import dimsys_SI
+        >>> dimsys_SI.get_dimensional_dependencies(velocity)
+        {Dimension(length, L): 1, Dimension(time, T): -1}
+        >>> length + length
+        Dimension(length)
+        >>> l2 = length**2
+        >>> l2
+        Dimension(length**2)
+        >>> dimsys_SI.get_dimensional_dependencies(l2)
+        {Dimension(length, L): 2}
+
+    """
+
+    _op_priority = 13.0
+
+    # XXX: This doesn't seem to be used anywhere...
+    _dimensional_dependencies = {}  # type: ignore
+
+    is_commutative = True
+    is_number = False
+    # make sqrt(M**2) --> M
+    is_positive = True
+    is_real = True
+
+    def __new__(cls, name, symbol=None):
+
+        if isinstance(name, str):
+            name = Symbol(name)
+        else:
+            name = sympify(name)
+
+        if not isinstance(name, Expr):
+            raise TypeError("Dimension name needs to be a valid math expression")
+
+        if isinstance(symbol, str):
+            symbol = Symbol(symbol)
+        elif symbol is not None:
+            assert isinstance(symbol, Symbol)
+
+        obj = Expr.__new__(cls, name)
+
+        obj._name = name
+        obj._symbol = symbol
+        return obj
+
+    @property
+    def name(self):
+        return self._name
+
+    @property
+    def symbol(self):
+        return self._symbol
+
+    def __str__(self):
+        """
+        Display the string representation of the dimension.
+        """
+        if self.symbol is None:
+            return "Dimension(%s)" % (self.name)
+        else:
+            return "Dimension(%s, %s)" % (self.name, self.symbol)
+
+    def __repr__(self):
+        return self.__str__()
+
+    def __neg__(self):
+        return self
+
+    def __add__(self, other):
+        from sympy.physics.units.quantities import Quantity
+        other = sympify(other)
+        if isinstance(other, Basic):
+            if other.has(Quantity):
+                raise TypeError("cannot sum dimension and quantity")
+            if isinstance(other, Dimension) and self == other:
+                return self
+            return super().__add__(other)
+        return self
+
+    def __radd__(self, other):
+        return self.__add__(other)
+
+    def __sub__(self, other):
+        # there is no notion of ordering (or magnitude) among dimension,
+        # subtraction is equivalent to addition when the operation is legal
+        return self + other
+
+    def __rsub__(self, other):
+        # there is no notion of ordering (or magnitude) among dimension,
+        # subtraction is equivalent to addition when the operation is legal
+        return self + other
+
+    def __pow__(self, other):
+        return self._eval_power(other)
+
+    def _eval_power(self, other):
+        other = sympify(other)
+        return Dimension(self.name**other)
+
+    def __mul__(self, other):
+        from sympy.physics.units.quantities import Quantity
+        if isinstance(other, Basic):
+            if other.has(Quantity):
+                raise TypeError("cannot sum dimension and quantity")
+            if isinstance(other, Dimension):
+                return Dimension(self.name*other.name)
+            if not other.free_symbols:  # other.is_number cannot be used
+                return self
+            return super().__mul__(other)
+        return self
+
+    def __rmul__(self, other):
+        return self.__mul__(other)
+
+    def __truediv__(self, other):
+        return self*Pow(other, -1)
+
+    def __rtruediv__(self, other):
+        return other * pow(self, -1)
+
+    @classmethod
+    def _from_dimensional_dependencies(cls, dependencies):
+        return reduce(lambda x, y: x * y, (
+            d**e for d, e in dependencies.items()
+        ), 1)
+
+    def has_integer_powers(self, dim_sys):
+        """
+        Check if the dimension object has only integer powers.
+
+        All the dimension powers should be integers, but rational powers may
+        appear in intermediate steps. This method may be used to check that the
+        final result is well-defined.
+        """
+
+        return all(dpow.is_Integer for dpow in dim_sys.get_dimensional_dependencies(self).values())
+
+
+# Create dimensions according to the base units in MKSA.
+# For other unit systems, they can be derived by transforming the base
+# dimensional dependency dictionary.
+
+
+class DimensionSystem(Basic, _QuantityMapper):
+    r"""
+    DimensionSystem represents a coherent set of dimensions.
+
+    The constructor takes three parameters:
+
+    - base dimensions;
+    - derived dimensions: these are defined in terms of the base dimensions
+      (for example velocity is defined from the division of length by time);
+    - dependency of dimensions: how the derived dimensions depend
+      on the base dimensions.
+
+    Optionally either the ``derived_dims`` or the ``dimensional_dependencies``
+    may be omitted.
+    """
+
+    def __new__(cls, base_dims, derived_dims=(), dimensional_dependencies={}):
+        dimensional_dependencies = dict(dimensional_dependencies)
+
+        def parse_dim(dim):
+            if isinstance(dim, str):
+                dim = Dimension(Symbol(dim))
+            elif isinstance(dim, Dimension):
+                pass
+            elif isinstance(dim, Symbol):
+                dim = Dimension(dim)
+            else:
+                raise TypeError("%s wrong type" % dim)
+            return dim
+
+        base_dims = [parse_dim(i) for i in base_dims]
+        derived_dims = [parse_dim(i) for i in derived_dims]
+
+        for dim in base_dims:
+            if (dim in dimensional_dependencies
+                and (len(dimensional_dependencies[dim]) != 1 or
+                dimensional_dependencies[dim].get(dim, None) != 1)):
+                raise IndexError("Repeated value in base dimensions")
+            dimensional_dependencies[dim] = Dict({dim: 1})
+
+        def parse_dim_name(dim):
+            if isinstance(dim, Dimension):
+                return dim
+            elif isinstance(dim, str):
+                return Dimension(Symbol(dim))
+            elif isinstance(dim, Symbol):
+                return Dimension(dim)
+            else:
+                raise TypeError("unrecognized type %s for %s" % (type(dim), dim))
+
+        for dim in dimensional_dependencies.keys():
+            dim = parse_dim(dim)
+            if (dim not in derived_dims) and (dim not in base_dims):
+                derived_dims.append(dim)
+
+        def parse_dict(d):
+            return Dict({parse_dim_name(i): j for i, j in d.items()})
+
+        # Make sure everything is a SymPy type:
+        dimensional_dependencies = {parse_dim_name(i): parse_dict(j) for i, j in
+                                    dimensional_dependencies.items()}
+
+        for dim in derived_dims:
+            if dim in base_dims:
+                raise ValueError("Dimension %s both in base and derived" % dim)
+            if dim not in dimensional_dependencies:
+                # TODO: should this raise a warning?
+                dimensional_dependencies[dim] = Dict({dim: 1})
+
+        base_dims.sort(key=default_sort_key)
+        derived_dims.sort(key=default_sort_key)
+
+        base_dims = Tuple(*base_dims)
+        derived_dims = Tuple(*derived_dims)
+        dimensional_dependencies = Dict({i: Dict(j) for i, j in dimensional_dependencies.items()})
+        obj = Basic.__new__(cls, base_dims, derived_dims, dimensional_dependencies)
+        return obj
+
+    @property
+    def base_dims(self):
+        return self.args[0]
+
+    @property
+    def derived_dims(self):
+        return self.args[1]
+
+    @property
+    def dimensional_dependencies(self):
+        return self.args[2]
+
+    def _get_dimensional_dependencies_for_name(self, dimension):
+        if isinstance(dimension, str):
+            dimension = Dimension(Symbol(dimension))
+        elif not isinstance(dimension, Dimension):
+            dimension = Dimension(dimension)
+
+        if dimension.name.is_Symbol:
+            # Dimensions not included in the dependencies are considered
+            # as base dimensions:
+            return dict(self.dimensional_dependencies.get(dimension, {dimension: 1}))
+
+        if dimension.name.is_number or dimension.name.is_NumberSymbol:
+            return {}
+
+        get_for_name = self._get_dimensional_dependencies_for_name
+
+        if dimension.name.is_Mul:
+            ret = collections.defaultdict(int)
+            dicts = [get_for_name(i) for i in dimension.name.args]
+            for d in dicts:
+                for k, v in d.items():
+                    ret[k] += v
+            return {k: v for (k, v) in ret.items() if v != 0}
+
+        if dimension.name.is_Add:
+            dicts = [get_for_name(i) for i in dimension.name.args]
+            if all(d == dicts[0] for d in dicts[1:]):
+                return dicts[0]
+            raise TypeError("Only equivalent dimensions can be added or subtracted.")
+
+        if dimension.name.is_Pow:
+            dim_base = get_for_name(dimension.name.base)
+            dim_exp = get_for_name(dimension.name.exp)
+            if dim_exp == {} or dimension.name.exp.is_Symbol:
+                return {k: v * dimension.name.exp for (k, v) in dim_base.items()}
+            else:
+                raise TypeError("The exponent for the power operator must be a Symbol or dimensionless.")
+
+        if dimension.name.is_Function:
+            args = (Dimension._from_dimensional_dependencies(
+                get_for_name(arg)) for arg in dimension.name.args)
+            result = dimension.name.func(*args)
+
+            dicts = [get_for_name(i) for i in dimension.name.args]
+
+            if isinstance(result, Dimension):
+                return self.get_dimensional_dependencies(result)
+            elif result.func == dimension.name.func:
+                if isinstance(dimension.name, TrigonometricFunction):
+                    if dicts[0] in ({}, {Dimension('angle'): 1}):
+                        return {}
+                    else:
+                        raise TypeError("The input argument for the function {} must be dimensionless or have dimensions of angle.".format(dimension.func))
+                else:
+                    if all(item == {} for item in dicts):
+                        return {}
+                    else:
+                        raise TypeError("The input arguments for the function {} must be dimensionless.".format(dimension.func))
+            else:
+                return get_for_name(result)
+
+        raise TypeError("Type {} not implemented for get_dimensional_dependencies".format(type(dimension.name)))
+
+    def get_dimensional_dependencies(self, name, mark_dimensionless=False):
+        dimdep = self._get_dimensional_dependencies_for_name(name)
+        if mark_dimensionless and dimdep == {}:
+            return {Dimension(1): 1}
+        return dict(dimdep.items())
+
+    def equivalent_dims(self, dim1, dim2):
+        deps1 = self.get_dimensional_dependencies(dim1)
+        deps2 = self.get_dimensional_dependencies(dim2)
+        return deps1 == deps2
+
+    def extend(self, new_base_dims, new_derived_dims=(), new_dim_deps=None):
+        deps = dict(self.dimensional_dependencies)
+        if new_dim_deps:
+            deps.update(new_dim_deps)
+
+        new_dim_sys = DimensionSystem(
+            tuple(self.base_dims) + tuple(new_base_dims),
+            tuple(self.derived_dims) + tuple(new_derived_dims),
+            deps
+        )
+        new_dim_sys._quantity_dimension_map.update(self._quantity_dimension_map)
+        new_dim_sys._quantity_scale_factors.update(self._quantity_scale_factors)
+        return new_dim_sys
+
+    def is_dimensionless(self, dimension):
+        """
+        Check if the dimension object really has a dimension.
+
+        A dimension should have at least one component with non-zero power.
+        """
+        if dimension.name == 1:
+            return True
+        return self.get_dimensional_dependencies(dimension) == {}
+
+    @property
+    def list_can_dims(self):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+        List all canonical dimension names.
+        """
+        dimset = set()
+        for i in self.base_dims:
+            dimset.update(set(self.get_dimensional_dependencies(i).keys()))
+        return tuple(sorted(dimset, key=str))
+
+    @property
+    def inv_can_transf_matrix(self):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+        Compute the inverse transformation matrix from the base to the
+        canonical dimension basis.
+
+        It corresponds to the matrix where columns are the vector of base
+        dimensions in canonical basis.
+
+        This matrix will almost never be used because dimensions are always
+        defined with respect to the canonical basis, so no work has to be done
+        to get them in this basis. Nonetheless if this matrix is not square
+        (or not invertible) it means that we have chosen a bad basis.
+        """
+        matrix = reduce(lambda x, y: x.row_join(y),
+                        [self.dim_can_vector(d) for d in self.base_dims])
+        return matrix
+
+    @property
+    def can_transf_matrix(self):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+        Return the canonical transformation matrix from the canonical to the
+        base dimension basis.
+
+        It is the inverse of the matrix computed with inv_can_transf_matrix().
+        """
+
+        #TODO: the inversion will fail if the system is inconsistent, for
+        #      example if the matrix is not a square
+        return reduce(lambda x, y: x.row_join(y),
+                      [self.dim_can_vector(d) for d in sorted(self.base_dims, key=str)]
+                      ).inv()
+
+    def dim_can_vector(self, dim):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+        Dimensional representation in terms of the canonical base dimensions.
+        """
+
+        vec = []
+        for d in self.list_can_dims:
+            vec.append(self.get_dimensional_dependencies(dim).get(d, 0))
+        return Matrix(vec)
+
+    def dim_vector(self, dim):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+
+        Vector representation in terms of the base dimensions.
+        """
+        return self.can_transf_matrix * Matrix(self.dim_can_vector(dim))
+
+    def print_dim_base(self, dim):
+        """
+        Give the string expression of a dimension in term of the basis symbols.
+        """
+        dims = self.dim_vector(dim)
+        symbols = [i.symbol if i.symbol is not None else i.name for i in self.base_dims]
+        res = S.One
+        for (s, p) in zip(symbols, dims):
+            res *= s**p
+        return res
+
+    @property
+    def dim(self):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+        Give the dimension of the system.
+
+        That is return the number of dimensions forming the basis.
+        """
+        return len(self.base_dims)
+
+    @property
+    def is_consistent(self):
+        """
+        Useless method, kept for compatibility with previous versions.
+
+        DO NOT USE.
+
+        Check if the system is well defined.
+        """
+
+        # not enough or too many base dimensions compared to independent
+        # dimensions
+        # in vector language: the set of vectors do not form a basis
+        return self.inv_can_transf_matrix.is_square

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/quantities.py

@@ -0,0 +1,152 @@
+"""
+Physical quantities.
+"""
+
+from sympy.core.expr import AtomicExpr
+from sympy.core.symbol import Symbol
+from sympy.core.sympify import sympify
+from sympy.physics.units.dimensions import _QuantityMapper
+from sympy.physics.units.prefixes import Prefix
+
+
+class Quantity(AtomicExpr):
+    """
+    Physical quantity: can be a unit of measure, a constant or a generic quantity.
+    """
+
+    is_commutative = True
+    is_real = True
+    is_number = False
+    is_nonzero = True
+    is_physical_constant = False
+    _diff_wrt = True
+
+    def __new__(cls, name, abbrev=None,
+                latex_repr=None, pretty_unicode_repr=None,
+                pretty_ascii_repr=None, mathml_presentation_repr=None,
+                is_prefixed=False,
+                **assumptions):
+
+        if not isinstance(name, Symbol):
+            name = Symbol(name)
+
+        if abbrev is None:
+            abbrev = name
+        elif isinstance(abbrev, str):
+            abbrev = Symbol(abbrev)
+
+        # HACK: These are here purely for type checking. They actually get assigned below.
+        cls._is_prefixed = is_prefixed
+
+        obj = AtomicExpr.__new__(cls, name, abbrev)
+        obj._name = name
+        obj._abbrev = abbrev
+        obj._latex_repr = latex_repr
+        obj._unicode_repr = pretty_unicode_repr
+        obj._ascii_repr = pretty_ascii_repr
+        obj._mathml_repr = mathml_presentation_repr
+        obj._is_prefixed = is_prefixed
+        return obj
+
+    def set_global_dimension(self, dimension):
+        _QuantityMapper._quantity_dimension_global[self] = dimension
+
+    def set_global_relative_scale_factor(self, scale_factor, reference_quantity):
+        """
+        Setting a scale factor that is valid across all unit system.
+        """
+        from sympy.physics.units import UnitSystem
+        scale_factor = sympify(scale_factor)
+        if isinstance(scale_factor, Prefix):
+            self._is_prefixed = True
+        # replace all prefixes by their ratio to canonical units:
+        scale_factor = scale_factor.replace(
+            lambda x: isinstance(x, Prefix),
+            lambda x: x.scale_factor
+        )
+        scale_factor = sympify(scale_factor)
+        UnitSystem._quantity_scale_factors_global[self] = (scale_factor, reference_quantity)
+        UnitSystem._quantity_dimensional_equivalence_map_global[self] = reference_quantity
+
+    @property
+    def name(self):
+        return self._name
+
+    @property
+    def dimension(self):
+        from sympy.physics.units import UnitSystem
+        unit_system = UnitSystem.get_default_unit_system()
+        return unit_system.get_quantity_dimension(self)
+
+    @property
+    def abbrev(self):
+        """
+        Symbol representing the unit name.
+
+        Prepend the abbreviation with the prefix symbol if it is defines.
+        """
+        return self._abbrev
+
+    @property
+    def scale_factor(self):
+        """
+        Overall magnitude of the quantity as compared to the canonical units.
+        """
+        from sympy.physics.units import UnitSystem
+        unit_system = UnitSystem.get_default_unit_system()
+        return unit_system.get_quantity_scale_factor(self)
+
+    def _eval_is_positive(self):
+        return True
+
+    def _eval_is_constant(self):
+        return True
+
+    def _eval_Abs(self):
+        return self
+
+    def _eval_subs(self, old, new):
+        if isinstance(new, Quantity) and self != old:
+            return self
+
+    def _latex(self, printer):
+        if self._latex_repr:
+            return self._latex_repr
+        else:
+            return r'\text{{{}}}'.format(self.args[1] \
+                          if len(self.args) >= 2 else self.args[0])
+
+    def convert_to(self, other, unit_system="SI"):
+        """
+        Convert the quantity to another quantity of same dimensions.
+
+        Examples
+        ========
+
+        >>> from sympy.physics.units import speed_of_light, meter, second
+        >>> speed_of_light
+        speed_of_light
+        >>> speed_of_light.convert_to(meter/second)
+        299792458*meter/second
+
+        >>> from sympy.physics.units import liter
+        >>> liter.convert_to(meter**3)
+        meter**3/1000
+        """
+        from .util import convert_to
+        return convert_to(self, other, unit_system)
+
+    @property
+    def free_symbols(self):
+        """Return free symbols from quantity."""
+        return set()
+
+    @property
+    def is_prefixed(self):
+        """Whether or not the quantity is prefixed. Eg. `kilogram` is prefixed, but `gram` is not."""
+        return self._is_prefixed
+
+class PhysicalConstant(Quantity):
+    """Represents a physical constant, eg. `speed_of_light` or `avogadro_constant`."""
+
+    is_physical_constant = True

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/systems/cgs.py

@@ -0,0 +1,82 @@
+from sympy.core.singleton import S
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.units import UnitSystem, centimeter, gram, second, coulomb, charge, speed_of_light, current, mass, \
+    length, voltage, magnetic_density, magnetic_flux
+from sympy.physics.units.definitions import coulombs_constant
+from sympy.physics.units.definitions.unit_definitions import statcoulomb, statampere, statvolt, volt, tesla, gauss, \
+    weber, maxwell, debye, oersted, ohm, farad, henry, erg, ampere, coulomb_constant
+from sympy.physics.units.systems.mks import dimsys_length_weight_time
+
+One = S.One
+
+dimsys_cgs = dimsys_length_weight_time.extend(
+    [],
+    new_dim_deps={
+        # Dimensional dependencies for derived dimensions
+        "impedance": {"time": 1, "length": -1},
+        "conductance": {"time": -1, "length": 1},
+        "capacitance": {"length": 1},
+        "inductance": {"time": 2, "length": -1},
+        "charge": {"mass": S.Half, "length": S(3)/2, "time": -1},
+        "current": {"mass": One/2, "length": 3*One/2, "time": -2},
+        "voltage": {"length": -One/2, "mass": One/2, "time": -1},
+        "magnetic_density": {"length": -One/2, "mass": One/2, "time": -1},
+        "magnetic_flux": {"length": 3*One/2, "mass": One/2, "time": -1},
+    }
+)
+
+cgs_gauss = UnitSystem(
+    base_units=[centimeter, gram, second],
+    units=[],
+    name="cgs_gauss",
+    dimension_system=dimsys_cgs)
+
+
+cgs_gauss.set_quantity_scale_factor(coulombs_constant, 1)
+
+cgs_gauss.set_quantity_dimension(statcoulomb, charge)
+cgs_gauss.set_quantity_scale_factor(statcoulomb, centimeter**(S(3)/2)*gram**(S.Half)/second)
+
+cgs_gauss.set_quantity_dimension(coulomb, charge)
+
+cgs_gauss.set_quantity_dimension(statampere, current)
+cgs_gauss.set_quantity_scale_factor(statampere, statcoulomb/second)
+
+cgs_gauss.set_quantity_dimension(statvolt, voltage)
+cgs_gauss.set_quantity_scale_factor(statvolt, erg/statcoulomb)
+
+cgs_gauss.set_quantity_dimension(volt, voltage)
+
+cgs_gauss.set_quantity_dimension(gauss, magnetic_density)
+cgs_gauss.set_quantity_scale_factor(gauss, sqrt(gram/centimeter)/second)
+
+cgs_gauss.set_quantity_dimension(tesla, magnetic_density)
+
+cgs_gauss.set_quantity_dimension(maxwell, magnetic_flux)
+cgs_gauss.set_quantity_scale_factor(maxwell, sqrt(centimeter**3*gram)/second)
+
+# SI units expressed in CGS-gaussian units:
+cgs_gauss.set_quantity_scale_factor(coulomb, 10*speed_of_light*statcoulomb)
+cgs_gauss.set_quantity_scale_factor(ampere, 10*speed_of_light*statcoulomb/second)
+cgs_gauss.set_quantity_scale_factor(volt, 10**6/speed_of_light*statvolt)
+cgs_gauss.set_quantity_scale_factor(weber, 10**8*maxwell)
+cgs_gauss.set_quantity_scale_factor(tesla, 10**4*gauss)
+cgs_gauss.set_quantity_scale_factor(debye, One/10**18*statcoulomb*centimeter)
+cgs_gauss.set_quantity_scale_factor(oersted, sqrt(gram/centimeter)/second)
+cgs_gauss.set_quantity_scale_factor(ohm, 10**5/speed_of_light**2*second/centimeter)
+cgs_gauss.set_quantity_scale_factor(farad, One/10**5*speed_of_light**2*centimeter)
+cgs_gauss.set_quantity_scale_factor(henry, 10**5/speed_of_light**2/centimeter*second**2)
+
+# Coulomb's constant:
+cgs_gauss.set_quantity_dimension(coulomb_constant, 1)
+cgs_gauss.set_quantity_scale_factor(coulomb_constant, 1)
+
+__all__ = [
+    'ohm', 'tesla', 'maxwell', 'speed_of_light', 'volt', 'second', 'voltage',
+    'debye', 'dimsys_length_weight_time', 'centimeter', 'coulomb_constant',
+    'farad', 'sqrt', 'UnitSystem', 'current', 'charge', 'weber', 'gram',
+    'statcoulomb', 'gauss', 'S', 'statvolt', 'oersted', 'statampere',
+    'dimsys_cgs', 'coulomb', 'magnetic_density', 'magnetic_flux', 'One',
+    'length', 'erg', 'mass', 'coulombs_constant', 'henry', 'ampere',
+    'cgs_gauss',
+]

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/systems/length_weight_time.py

@@ -0,0 +1,156 @@
+from sympy.core.singleton import S
+
+from sympy.core.numbers import pi
+
+from sympy.physics.units import DimensionSystem, hertz, kilogram
+from sympy.physics.units.definitions import (
+    G, Hz, J, N, Pa, W, c, g, kg, m, s, meter, gram, second, newton,
+    joule, watt, pascal)
+from sympy.physics.units.definitions.dimension_definitions import (
+    acceleration, action, energy, force, frequency, momentum,
+    power, pressure, velocity, length, mass, time)
+from sympy.physics.units.prefixes import PREFIXES, prefix_unit
+from sympy.physics.units.prefixes import (
+    kibi, mebi, gibi, tebi, pebi, exbi
+)
+from sympy.physics.units.definitions import (
+    cd, K, coulomb, volt, ohm, siemens, farad, henry, tesla, weber, dioptre,
+    lux, katal, gray, becquerel, inch, hectare, liter, julian_year,
+    gravitational_constant, speed_of_light, elementary_charge, planck, hbar,
+    electronvolt, avogadro_number, avogadro_constant, boltzmann_constant,
+    stefan_boltzmann_constant, atomic_mass_constant, molar_gas_constant,
+    faraday_constant, josephson_constant, von_klitzing_constant,
+    acceleration_due_to_gravity, magnetic_constant, vacuum_permittivity,
+    vacuum_impedance, coulomb_constant, atmosphere, bar, pound, psi, mmHg,
+    milli_mass_unit, quart, lightyear, astronomical_unit, planck_mass,
+    planck_time, planck_temperature, planck_length, planck_charge,
+    planck_area, planck_volume, planck_momentum, planck_energy, planck_force,
+    planck_power, planck_density, planck_energy_density, planck_intensity,
+    planck_angular_frequency, planck_pressure, planck_current, planck_voltage,
+    planck_impedance, planck_acceleration, bit, byte, kibibyte, mebibyte,
+    gibibyte, tebibyte, pebibyte, exbibyte, curie, rutherford, radian, degree,
+    steradian, angular_mil, atomic_mass_unit, gee, kPa, ampere, u0, kelvin,
+    mol, mole, candela, electric_constant, boltzmann, angstrom
+)
+
+
+dimsys_length_weight_time = DimensionSystem([
+    # Dimensional dependencies for MKS base dimensions
+    length,
+    mass,
+    time,
+], dimensional_dependencies={
+    # Dimensional dependencies for derived dimensions
+    "velocity": {"length": 1, "time": -1},
+    "acceleration": {"length": 1, "time": -2},
+    "momentum": {"mass": 1, "length": 1, "time": -1},
+    "force": {"mass": 1, "length": 1, "time": -2},
+    "energy": {"mass": 1, "length": 2, "time": -2},
+    "power": {"length": 2, "mass": 1, "time": -3},
+    "pressure": {"mass": 1, "length": -1, "time": -2},
+    "frequency": {"time": -1},
+    "action": {"length": 2, "mass": 1, "time": -1},
+    "area": {"length": 2},
+    "volume": {"length": 3},
+})
+
+
+One = S.One
+
+
+# Base units:
+dimsys_length_weight_time.set_quantity_dimension(meter, length)
+dimsys_length_weight_time.set_quantity_scale_factor(meter, One)
+
+# gram; used to define its prefixed units
+dimsys_length_weight_time.set_quantity_dimension(gram, mass)
+dimsys_length_weight_time.set_quantity_scale_factor(gram, One)
+
+dimsys_length_weight_time.set_quantity_dimension(second, time)
+dimsys_length_weight_time.set_quantity_scale_factor(second, One)
+
+# derived units
+
+dimsys_length_weight_time.set_quantity_dimension(newton, force)
+dimsys_length_weight_time.set_quantity_scale_factor(newton, kilogram*meter/second**2)
+
+dimsys_length_weight_time.set_quantity_dimension(joule, energy)
+dimsys_length_weight_time.set_quantity_scale_factor(joule, newton*meter)
+
+dimsys_length_weight_time.set_quantity_dimension(watt, power)
+dimsys_length_weight_time.set_quantity_scale_factor(watt, joule/second)
+
+dimsys_length_weight_time.set_quantity_dimension(pascal, pressure)
+dimsys_length_weight_time.set_quantity_scale_factor(pascal, newton/meter**2)
+
+dimsys_length_weight_time.set_quantity_dimension(hertz, frequency)
+dimsys_length_weight_time.set_quantity_scale_factor(hertz, One)
+
+# Other derived units:
+
+dimsys_length_weight_time.set_quantity_dimension(dioptre, 1 / length)
+dimsys_length_weight_time.set_quantity_scale_factor(dioptre, 1/meter)
+
+# Common volume and area units
+
+dimsys_length_weight_time.set_quantity_dimension(hectare, length**2)
+dimsys_length_weight_time.set_quantity_scale_factor(hectare, (meter**2)*(10000))
+
+dimsys_length_weight_time.set_quantity_dimension(liter, length**3)
+dimsys_length_weight_time.set_quantity_scale_factor(liter, meter**3/1000)
+
+
+# Newton constant
+# REF: NIST SP 959 (June 2019)
+
+dimsys_length_weight_time.set_quantity_dimension(gravitational_constant, length ** 3 * mass ** -1 * time ** -2)
+dimsys_length_weight_time.set_quantity_scale_factor(gravitational_constant, 6.67430e-11*m**3/(kg*s**2))
+
+# speed of light
+
+dimsys_length_weight_time.set_quantity_dimension(speed_of_light, velocity)
+dimsys_length_weight_time.set_quantity_scale_factor(speed_of_light, 299792458*meter/second)
+
+
+# Planck constant
+# REF: NIST SP 959 (June 2019)
+
+dimsys_length_weight_time.set_quantity_dimension(planck, action)
+dimsys_length_weight_time.set_quantity_scale_factor(planck, 6.62607015e-34*joule*second)
+
+# Reduced Planck constant
+# REF: NIST SP 959 (June 2019)
+
+dimsys_length_weight_time.set_quantity_dimension(hbar, action)
+dimsys_length_weight_time.set_quantity_scale_factor(hbar, planck / (2 * pi))
+
+
+__all__ = [
+    'mmHg', 'atmosphere', 'newton', 'meter', 'vacuum_permittivity', 'pascal',
+    'magnetic_constant', 'angular_mil', 'julian_year', 'weber', 'exbibyte',
+    'liter', 'molar_gas_constant', 'faraday_constant', 'avogadro_constant',
+    'planck_momentum', 'planck_density', 'gee', 'mol', 'bit', 'gray', 'kibi',
+    'bar', 'curie', 'prefix_unit', 'PREFIXES', 'planck_time', 'gram',
+    'candela', 'force', 'planck_intensity', 'energy', 'becquerel',
+    'planck_acceleration', 'speed_of_light', 'dioptre', 'second', 'frequency',
+    'Hz', 'power', 'lux', 'planck_current', 'momentum', 'tebibyte',
+    'planck_power', 'degree', 'mebi', 'K', 'planck_volume',
+    'quart', 'pressure', 'W', 'joule', 'boltzmann_constant', 'c', 'g',
+    'planck_force', 'exbi', 's', 'watt', 'action', 'hbar', 'gibibyte',
+    'DimensionSystem', 'cd', 'volt', 'planck_charge', 'angstrom',
+    'dimsys_length_weight_time', 'pebi', 'vacuum_impedance', 'planck',
+    'farad', 'gravitational_constant', 'u0', 'hertz', 'tesla', 'steradian',
+    'josephson_constant', 'planck_area', 'stefan_boltzmann_constant',
+    'astronomical_unit', 'J', 'N', 'planck_voltage', 'planck_energy',
+    'atomic_mass_constant', 'rutherford', 'elementary_charge', 'Pa',
+    'planck_mass', 'henry', 'planck_angular_frequency', 'ohm', 'pound',
+    'planck_pressure', 'G', 'avogadro_number', 'psi', 'von_klitzing_constant',
+    'planck_length', 'radian', 'mole', 'acceleration',
+    'planck_energy_density', 'mebibyte', 'length',
+    'acceleration_due_to_gravity', 'planck_temperature', 'tebi', 'inch',
+    'electronvolt', 'coulomb_constant', 'kelvin', 'kPa', 'boltzmann',
+    'milli_mass_unit', 'gibi', 'planck_impedance', 'electric_constant', 'kg',
+    'coulomb', 'siemens', 'byte', 'atomic_mass_unit', 'm', 'kibibyte',
+    'kilogram', 'lightyear', 'mass', 'time', 'pebibyte', 'velocity',
+    'ampere', 'katal',
+]

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/systems/mks.py

@@ -0,0 +1,46 @@
+"""
+MKS unit system.
+
+MKS stands for "meter, kilogram, second".
+"""
+
+from sympy.physics.units import UnitSystem
+from sympy.physics.units.definitions import gravitational_constant, hertz, joule, newton, pascal, watt, speed_of_light, gram, kilogram, meter, second
+from sympy.physics.units.definitions.dimension_definitions import (
+    acceleration, action, energy, force, frequency, momentum,
+    power, pressure, velocity, length, mass, time)
+from sympy.physics.units.prefixes import PREFIXES, prefix_unit
+from sympy.physics.units.systems.length_weight_time import dimsys_length_weight_time
+
+dims = (velocity, acceleration, momentum, force, energy, power, pressure,
+        frequency, action)
+
+units = [meter, gram, second, joule, newton, watt, pascal, hertz]
+all_units = []
+
+# Prefixes of units like gram, joule, newton etc get added using `prefix_unit`
+# in the for loop, but the actual units have to be added manually.
+all_units.extend([gram, joule, newton, watt, pascal, hertz])
+
+for u in units:
+    all_units.extend(prefix_unit(u, PREFIXES))
+all_units.extend([gravitational_constant, speed_of_light])
+
+# unit system
+MKS = UnitSystem(base_units=(meter, kilogram, second), units=all_units, name="MKS", dimension_system=dimsys_length_weight_time, derived_units={
+    power: watt,
+    time: second,
+    pressure: pascal,
+    length: meter,
+    frequency: hertz,
+    mass: kilogram,
+    force: newton,
+    energy: joule,
+    velocity: meter/second,
+    acceleration: meter/(second**2),
+})
+
+
+__all__ = [
+    'MKS', 'units', 'all_units', 'dims',
+]

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/systems/mksa.py

@@ -0,0 +1,54 @@
+"""
+MKS unit system.
+
+MKS stands for "meter, kilogram, second, ampere".
+"""
+
+from __future__ import annotations
+
+from sympy.physics.units.definitions import Z0, ampere, coulomb, farad, henry, siemens, tesla, volt, weber, ohm
+from sympy.physics.units.definitions.dimension_definitions import (
+    capacitance, charge, conductance, current, impedance, inductance,
+    magnetic_density, magnetic_flux, voltage)
+from sympy.physics.units.prefixes import PREFIXES, prefix_unit
+from sympy.physics.units.systems.mks import MKS, dimsys_length_weight_time
+from sympy.physics.units.quantities import Quantity
+
+dims = (voltage, impedance, conductance, current, capacitance, inductance, charge,
+        magnetic_density, magnetic_flux)
+
+units = [ampere, volt, ohm, siemens, farad, henry, coulomb, tesla, weber]
+
+all_units: list[Quantity] = []
+for u in units:
+    all_units.extend(prefix_unit(u, PREFIXES))
+all_units.extend(units)
+
+all_units.append(Z0)
+
+dimsys_MKSA = dimsys_length_weight_time.extend([
+    # Dimensional dependencies for base dimensions (MKSA not in MKS)
+    current,
+], new_dim_deps={
+    # Dimensional dependencies for derived dimensions
+    "voltage": {"mass": 1, "length": 2, "current": -1, "time": -3},
+    "impedance": {"mass": 1, "length": 2, "current": -2, "time": -3},
+    "conductance": {"mass": -1, "length": -2, "current": 2, "time": 3},
+    "capacitance": {"mass": -1, "length": -2, "current": 2, "time": 4},
+    "inductance": {"mass": 1, "length": 2, "current": -2, "time": -2},
+    "charge": {"current": 1, "time": 1},
+    "magnetic_density": {"mass": 1, "current": -1, "time": -2},
+    "magnetic_flux": {"length": 2, "mass": 1, "current": -1, "time": -2},
+})
+
+MKSA = MKS.extend(base=(ampere,), units=all_units, name='MKSA', dimension_system=dimsys_MKSA, derived_units={
+    magnetic_flux: weber,
+    impedance: ohm,
+    current: ampere,
+    voltage: volt,
+    inductance: henry,
+    conductance: siemens,
+    magnetic_density: tesla,
+    charge: coulomb,
+    capacitance: farad,
+})

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/systems/natural.py

@@ -0,0 +1,27 @@
+"""
+Naturalunit system.
+
+The natural system comes from "setting c = 1, hbar = 1". From the computer
+point of view it means that we use velocity and action instead of length and
+time. Moreover instead of mass we use energy.
+"""
+
+from sympy.physics.units import DimensionSystem
+from sympy.physics.units.definitions import c, eV, hbar
+from sympy.physics.units.definitions.dimension_definitions import (
+    action, energy, force, frequency, length, mass, momentum,
+    power, time, velocity)
+from sympy.physics.units.prefixes import PREFIXES, prefix_unit
+from sympy.physics.units.unitsystem import UnitSystem
+
+
+# dimension system
+_natural_dim = DimensionSystem(
+    base_dims=(action, energy, velocity),
+    derived_dims=(length, mass, time, momentum, force, power, frequency)
+)
+
+units = prefix_unit(eV, PREFIXES)
+
+# unit system
+natural = UnitSystem(base_units=(hbar, eV, c), units=units, name="Natural system")

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/systems/si.py

@@ -0,0 +1,377 @@
+"""
+SI unit system.
+Based on MKSA, which stands for "meter, kilogram, second, ampere".
+Added kelvin, candela and mole.
+
+"""
+
+from __future__ import annotations
+
+from sympy.physics.units import DimensionSystem, Dimension, dHg0
+
+from sympy.physics.units.quantities import Quantity
+
+from sympy.core.numbers import (Rational, pi)
+from sympy.core.singleton import S
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.units.definitions.dimension_definitions import (
+    acceleration, action, current, impedance, length, mass, time, velocity,
+    amount_of_substance, temperature, information, frequency, force, pressure,
+    energy, power, charge, voltage, capacitance, conductance, magnetic_flux,
+    magnetic_density, inductance, luminous_intensity
+)
+from sympy.physics.units.definitions import (
+    kilogram, newton, second, meter, gram, cd, K, joule, watt, pascal, hertz,
+    coulomb, volt, ohm, siemens, farad, henry, tesla, weber, dioptre, lux,
+    katal, gray, becquerel, inch, liter, julian_year, gravitational_constant,
+    speed_of_light, elementary_charge, planck, hbar, electronvolt,
+    avogadro_number, avogadro_constant, boltzmann_constant, electron_rest_mass,
+    stefan_boltzmann_constant, Da, atomic_mass_constant, molar_gas_constant,
+    faraday_constant, josephson_constant, von_klitzing_constant,
+    acceleration_due_to_gravity, magnetic_constant, vacuum_permittivity,
+    vacuum_impedance, coulomb_constant, atmosphere, bar, pound, psi, mmHg,
+    milli_mass_unit, quart, lightyear, astronomical_unit, planck_mass,
+    planck_time, planck_temperature, planck_length, planck_charge, planck_area,
+    planck_volume, planck_momentum, planck_energy, planck_force, planck_power,
+    planck_density, planck_energy_density, planck_intensity,
+    planck_angular_frequency, planck_pressure, planck_current, planck_voltage,
+    planck_impedance, planck_acceleration, bit, byte, kibibyte, mebibyte,
+    gibibyte, tebibyte, pebibyte, exbibyte, curie, rutherford, radian, degree,
+    steradian, angular_mil, atomic_mass_unit, gee, kPa, ampere, u0, c, kelvin,
+    mol, mole, candela, m, kg, s, electric_constant, G, boltzmann
+)
+from sympy.physics.units.prefixes import PREFIXES, prefix_unit
+from sympy.physics.units.systems.mksa import MKSA, dimsys_MKSA
+
+derived_dims = (frequency, force, pressure, energy, power, charge, voltage,
+                capacitance, conductance, magnetic_flux,
+                magnetic_density, inductance, luminous_intensity)
+base_dims = (amount_of_substance, luminous_intensity, temperature)
+
+units = [mol, cd, K, lux, hertz, newton, pascal, joule, watt, coulomb, volt,
+        farad, ohm, siemens, weber, tesla, henry, candela, lux, becquerel,
+        gray, katal]
+
+all_units: list[Quantity] = []
+for u in units:
+    all_units.extend(prefix_unit(u, PREFIXES))
+
+all_units.extend(units)
+all_units.extend([mol, cd, K, lux])
+
+
+dimsys_SI = dimsys_MKSA.extend(
+    [
+        # Dimensional dependencies for other base dimensions:
+        temperature,
+        amount_of_substance,
+        luminous_intensity,
+    ])
+
+dimsys_default = dimsys_SI.extend(
+    [information],
+)
+
+SI = MKSA.extend(base=(mol, cd, K), units=all_units, name='SI', dimension_system=dimsys_SI, derived_units={
+    power: watt,
+    magnetic_flux: weber,
+    time: second,
+    impedance: ohm,
+    pressure: pascal,
+    current: ampere,
+    voltage: volt,
+    length: meter,
+    frequency: hertz,
+    inductance: henry,
+    temperature: kelvin,
+    amount_of_substance: mole,
+    luminous_intensity: candela,
+    conductance: siemens,
+    mass: kilogram,
+    magnetic_density: tesla,
+    charge: coulomb,
+    force: newton,
+    capacitance: farad,
+    energy: joule,
+    velocity: meter/second,
+})
+
+One = S.One
+
+SI.set_quantity_dimension(radian, One)
+
+SI.set_quantity_scale_factor(ampere, One)
+
+SI.set_quantity_scale_factor(kelvin, One)
+
+SI.set_quantity_scale_factor(mole, One)
+
+SI.set_quantity_scale_factor(candela, One)
+
+# MKSA extension to MKS: derived units
+
+SI.set_quantity_scale_factor(coulomb, One)
+
+SI.set_quantity_scale_factor(volt, joule/coulomb)
+
+SI.set_quantity_scale_factor(ohm, volt/ampere)
+
+SI.set_quantity_scale_factor(siemens, ampere/volt)
+
+SI.set_quantity_scale_factor(farad, coulomb/volt)
+
+SI.set_quantity_scale_factor(henry, volt*second/ampere)
+
+SI.set_quantity_scale_factor(tesla, volt*second/meter**2)
+
+SI.set_quantity_scale_factor(weber, joule/ampere)
+
+
+SI.set_quantity_dimension(lux, luminous_intensity / length ** 2)
+SI.set_quantity_scale_factor(lux, steradian*candela/meter**2)
+
+# katal is the SI unit of catalytic activity
+
+SI.set_quantity_dimension(katal, amount_of_substance / time)
+SI.set_quantity_scale_factor(katal, mol/second)
+
+# gray is the SI unit of absorbed dose
+
+SI.set_quantity_dimension(gray, energy / mass)
+SI.set_quantity_scale_factor(gray, meter**2/second**2)
+
+# becquerel is the SI unit of radioactivity
+
+SI.set_quantity_dimension(becquerel, 1 / time)
+SI.set_quantity_scale_factor(becquerel, 1/second)
+
+#### CONSTANTS ####
+
+# elementary charge
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(elementary_charge, charge)
+SI.set_quantity_scale_factor(elementary_charge, 1.602176634e-19*coulomb)
+
+# Electronvolt
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(electronvolt, energy)
+SI.set_quantity_scale_factor(electronvolt, 1.602176634e-19*joule)
+
+# Avogadro number
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(avogadro_number, One)
+SI.set_quantity_scale_factor(avogadro_number, 6.02214076e23)
+
+# Avogadro constant
+
+SI.set_quantity_dimension(avogadro_constant, amount_of_substance ** -1)
+SI.set_quantity_scale_factor(avogadro_constant, avogadro_number / mol)
+
+# Boltzmann constant
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(boltzmann_constant, energy / temperature)
+SI.set_quantity_scale_factor(boltzmann_constant, 1.380649e-23*joule/kelvin)
+
+# Stefan-Boltzmann constant
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(stefan_boltzmann_constant, energy * time ** -1 * length ** -2 * temperature ** -4)
+SI.set_quantity_scale_factor(stefan_boltzmann_constant, pi**2 * boltzmann_constant**4 / (60 * hbar**3 * speed_of_light ** 2))
+
+# Atomic mass
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(atomic_mass_constant, mass)
+SI.set_quantity_scale_factor(atomic_mass_constant, 1.66053906660e-24*gram)
+
+# Molar gas constant
+# REF: NIST SP 959 (June 2019)
+
+SI.set_quantity_dimension(molar_gas_constant, energy / (temperature * amount_of_substance))
+SI.set_quantity_scale_factor(molar_gas_constant, boltzmann_constant * avogadro_constant)
+
+# Faraday constant
+
+SI.set_quantity_dimension(faraday_constant, charge / amount_of_substance)
+SI.set_quantity_scale_factor(faraday_constant, elementary_charge * avogadro_constant)
+
+# Josephson constant
+
+SI.set_quantity_dimension(josephson_constant, frequency / voltage)
+SI.set_quantity_scale_factor(josephson_constant, 0.5 * planck / elementary_charge)
+
+# Von Klitzing constant
+
+SI.set_quantity_dimension(von_klitzing_constant, voltage / current)
+SI.set_quantity_scale_factor(von_klitzing_constant, hbar / elementary_charge ** 2)
+
+# Acceleration due to gravity (on the Earth surface)
+
+SI.set_quantity_dimension(acceleration_due_to_gravity, acceleration)
+SI.set_quantity_scale_factor(acceleration_due_to_gravity, 9.80665*meter/second**2)
+
+# magnetic constant:
+
+SI.set_quantity_dimension(magnetic_constant, force / current ** 2)
+SI.set_quantity_scale_factor(magnetic_constant, 4*pi/10**7 * newton/ampere**2)
+
+# electric constant:
+
+SI.set_quantity_dimension(vacuum_permittivity, capacitance / length)
+SI.set_quantity_scale_factor(vacuum_permittivity, 1/(u0 * c**2))
+
+# vacuum impedance:
+
+SI.set_quantity_dimension(vacuum_impedance, impedance)
+SI.set_quantity_scale_factor(vacuum_impedance, u0 * c)
+
+# Electron rest mass
+SI.set_quantity_dimension(electron_rest_mass, mass)
+SI.set_quantity_scale_factor(electron_rest_mass, 9.1093837015e-31*kilogram)
+
+# Coulomb's constant:
+SI.set_quantity_dimension(coulomb_constant, force * length ** 2 / charge ** 2)
+SI.set_quantity_scale_factor(coulomb_constant, 1/(4*pi*vacuum_permittivity))
+
+SI.set_quantity_dimension(psi, pressure)
+SI.set_quantity_scale_factor(psi, pound * gee / inch ** 2)
+
+SI.set_quantity_dimension(mmHg, pressure)
+SI.set_quantity_scale_factor(mmHg, dHg0 * acceleration_due_to_gravity * kilogram / meter**2)
+
+SI.set_quantity_dimension(milli_mass_unit, mass)
+SI.set_quantity_scale_factor(milli_mass_unit, atomic_mass_unit/1000)
+
+SI.set_quantity_dimension(quart, length ** 3)
+SI.set_quantity_scale_factor(quart, Rational(231, 4) * inch**3)
+
+# Other convenient units and magnitudes
+
+SI.set_quantity_dimension(lightyear, length)
+SI.set_quantity_scale_factor(lightyear, speed_of_light*julian_year)
+
+SI.set_quantity_dimension(astronomical_unit, length)
+SI.set_quantity_scale_factor(astronomical_unit, 149597870691*meter)
+
+# Fundamental Planck units:
+
+SI.set_quantity_dimension(planck_mass, mass)
+SI.set_quantity_scale_factor(planck_mass, sqrt(hbar*speed_of_light/G))
+
+SI.set_quantity_dimension(planck_time, time)
+SI.set_quantity_scale_factor(planck_time, sqrt(hbar*G/speed_of_light**5))
+
+SI.set_quantity_dimension(planck_temperature, temperature)
+SI.set_quantity_scale_factor(planck_temperature, sqrt(hbar*speed_of_light**5/G/boltzmann**2))
+
+SI.set_quantity_dimension(planck_length, length)
+SI.set_quantity_scale_factor(planck_length, sqrt(hbar*G/speed_of_light**3))
+
+SI.set_quantity_dimension(planck_charge, charge)
+SI.set_quantity_scale_factor(planck_charge, sqrt(4*pi*electric_constant*hbar*speed_of_light))
+
+# Derived Planck units:
+
+SI.set_quantity_dimension(planck_area, length ** 2)
+SI.set_quantity_scale_factor(planck_area, planck_length**2)
+
+SI.set_quantity_dimension(planck_volume, length ** 3)
+SI.set_quantity_scale_factor(planck_volume, planck_length**3)
+
+SI.set_quantity_dimension(planck_momentum, mass * velocity)
+SI.set_quantity_scale_factor(planck_momentum, planck_mass * speed_of_light)
+
+SI.set_quantity_dimension(planck_energy, energy)
+SI.set_quantity_scale_factor(planck_energy, planck_mass * speed_of_light**2)
+
+SI.set_quantity_dimension(planck_force, force)
+SI.set_quantity_scale_factor(planck_force, planck_energy / planck_length)
+
+SI.set_quantity_dimension(planck_power, power)
+SI.set_quantity_scale_factor(planck_power, planck_energy / planck_time)
+
+SI.set_quantity_dimension(planck_density, mass / length ** 3)
+SI.set_quantity_scale_factor(planck_density, planck_mass / planck_length**3)
+
+SI.set_quantity_dimension(planck_energy_density, energy / length ** 3)
+SI.set_quantity_scale_factor(planck_energy_density, planck_energy / planck_length**3)
+
+SI.set_quantity_dimension(planck_intensity, mass * time ** (-3))
+SI.set_quantity_scale_factor(planck_intensity, planck_energy_density * speed_of_light)
+
+SI.set_quantity_dimension(planck_angular_frequency, 1 / time)
+SI.set_quantity_scale_factor(planck_angular_frequency, 1 / planck_time)
+
+SI.set_quantity_dimension(planck_pressure, pressure)
+SI.set_quantity_scale_factor(planck_pressure, planck_force / planck_length**2)
+
+SI.set_quantity_dimension(planck_current, current)
+SI.set_quantity_scale_factor(planck_current, planck_charge / planck_time)
+
+SI.set_quantity_dimension(planck_voltage, voltage)
+SI.set_quantity_scale_factor(planck_voltage, planck_energy / planck_charge)
+
+SI.set_quantity_dimension(planck_impedance, impedance)
+SI.set_quantity_scale_factor(planck_impedance, planck_voltage / planck_current)
+
+SI.set_quantity_dimension(planck_acceleration, acceleration)
+SI.set_quantity_scale_factor(planck_acceleration, speed_of_light / planck_time)
+
+# Older units for radioactivity
+
+SI.set_quantity_dimension(curie, 1 / time)
+SI.set_quantity_scale_factor(curie, 37000000000*becquerel)
+
+SI.set_quantity_dimension(rutherford, 1 / time)
+SI.set_quantity_scale_factor(rutherford, 1000000*becquerel)
+
+
+# check that scale factors are the right SI dimensions:
+for _scale_factor, _dimension in zip(
+    SI._quantity_scale_factors.values(),
+    SI._quantity_dimension_map.values()
+):
+    dimex = SI.get_dimensional_expr(_scale_factor)
+    if dimex != 1:
+        # XXX: equivalent_dims is an instance method taking two arguments in
+        # addition to self so this can not work:
+        if not DimensionSystem.equivalent_dims(_dimension, Dimension(dimex)):  # type: ignore
+            raise ValueError("quantity value and dimension mismatch")
+del _scale_factor, _dimension
+
+__all__ = [
+    'mmHg', 'atmosphere', 'inductance', 'newton', 'meter',
+    'vacuum_permittivity', 'pascal', 'magnetic_constant', 'voltage',
+    'angular_mil', 'luminous_intensity', 'all_units',
+    'julian_year', 'weber', 'exbibyte', 'liter',
+    'molar_gas_constant', 'faraday_constant', 'avogadro_constant',
+    'lightyear', 'planck_density', 'gee', 'mol', 'bit', 'gray',
+    'planck_momentum', 'bar', 'magnetic_density', 'prefix_unit', 'PREFIXES',
+    'planck_time', 'dimex', 'gram', 'candela', 'force', 'planck_intensity',
+    'energy', 'becquerel', 'planck_acceleration', 'speed_of_light',
+    'conductance', 'frequency', 'coulomb_constant', 'degree', 'lux', 'planck',
+    'current', 'planck_current', 'tebibyte', 'planck_power', 'MKSA', 'power',
+    'K', 'planck_volume', 'quart', 'pressure', 'amount_of_substance',
+    'joule', 'boltzmann_constant', 'Dimension', 'c', 'planck_force', 'length',
+    'watt', 'action', 'hbar', 'gibibyte', 'DimensionSystem', 'cd', 'volt',
+    'planck_charge', 'dioptre', 'vacuum_impedance', 'dimsys_default', 'farad',
+    'charge', 'gravitational_constant', 'temperature', 'u0', 'hertz',
+    'capacitance', 'tesla', 'steradian', 'planck_mass', 'josephson_constant',
+    'planck_area', 'stefan_boltzmann_constant', 'base_dims',
+    'astronomical_unit', 'radian', 'planck_voltage', 'impedance',
+    'planck_energy', 'Da', 'atomic_mass_constant', 'rutherford', 'second', 'inch',
+    'elementary_charge', 'SI', 'electronvolt', 'dimsys_SI', 'henry',
+    'planck_angular_frequency', 'ohm', 'pound', 'planck_pressure', 'G', 'psi',
+    'dHg0', 'von_klitzing_constant', 'planck_length', 'avogadro_number',
+    'mole', 'acceleration', 'information', 'planck_energy_density',
+    'mebibyte', 's', 'acceleration_due_to_gravity', 'electron_rest_mass',
+    'planck_temperature', 'units', 'mass', 'dimsys_MKSA', 'kelvin', 'kPa',
+    'boltzmann', 'milli_mass_unit', 'planck_impedance', 'electric_constant',
+    'derived_dims', 'kg', 'coulomb', 'siemens', 'byte', 'magnetic_flux',
+    'atomic_mass_unit', 'm', 'kibibyte', 'kilogram', 'One', 'curie', 'u',
+    'time', 'pebibyte', 'velocity', 'ampere', 'katal',
+]

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/tests/test_dimensions.py

@@ -0,0 +1,150 @@
+from sympy.physics.units.systems.si import dimsys_SI
+
+from sympy.core.numbers import pi
+from sympy.core.singleton import S
+from sympy.core.symbol import Symbol
+from sympy.functions.elementary.complexes import Abs
+from sympy.functions.elementary.exponential import log
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.functions.elementary.trigonometric import (acos, atan2, cos)
+from sympy.physics.units.dimensions import Dimension
+from sympy.physics.units.definitions.dimension_definitions import (
+    length, time, mass, force, pressure, angle
+)
+from sympy.physics.units import foot
+from sympy.testing.pytest import raises
+
+
+def test_Dimension_definition():
+    assert dimsys_SI.get_dimensional_dependencies(length) == {length: 1}
+    assert length.name == Symbol("length")
+    assert length.symbol == Symbol("L")
+
+    halflength = sqrt(length)
+    assert dimsys_SI.get_dimensional_dependencies(halflength) == {length: S.Half}
+
+
+def test_Dimension_error_definition():
+    # tuple with more or less than two entries
+    raises(TypeError, lambda: Dimension(("length", 1, 2)))
+    raises(TypeError, lambda: Dimension(["length"]))
+
+    # non-number power
+    raises(TypeError, lambda: Dimension({"length": "a"}))
+
+    # non-number with named argument
+    raises(TypeError, lambda: Dimension({"length": (1, 2)}))
+
+    # symbol should by Symbol or str
+    raises(AssertionError, lambda: Dimension("length", symbol=1))
+
+
+def test_str():
+    assert str(Dimension("length")) == "Dimension(length)"
+    assert str(Dimension("length", "L")) == "Dimension(length, L)"
+
+
+def test_Dimension_properties():
+    assert dimsys_SI.is_dimensionless(length) is False
+    assert dimsys_SI.is_dimensionless(length/length) is True
+    assert dimsys_SI.is_dimensionless(Dimension("undefined")) is False
+
+    assert length.has_integer_powers(dimsys_SI) is True
+    assert (length**(-1)).has_integer_powers(dimsys_SI) is True
+    assert (length**1.5).has_integer_powers(dimsys_SI) is False
+
+
+def test_Dimension_add_sub():
+    assert length + length == length
+    assert length - length == length
+    assert -length == length
+
+    raises(TypeError, lambda: length + foot)
+    raises(TypeError, lambda: foot + length)
+    raises(TypeError, lambda: length - foot)
+    raises(TypeError, lambda: foot - length)
+
+    # issue 14547 - only raise error for dimensional args; allow
+    # others to pass
+    x = Symbol('x')
+    e = length + x
+    assert e == x + length and e.is_Add and set(e.args) == {length, x}
+    e = length + 1
+    assert e == 1 + length == 1 - length and e.is_Add and set(e.args) == {length, 1}
+
+    assert dimsys_SI.get_dimensional_dependencies(mass * length / time**2 + force) == \
+            {length: 1, mass: 1, time: -2}
+    assert dimsys_SI.get_dimensional_dependencies(mass * length / time**2 + force -
+                                                   pressure * length**2) == \
+            {length: 1, mass: 1, time: -2}
+
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(mass * length / time**2 + pressure))
+
+def test_Dimension_mul_div_exp():
+    assert 2*length == length*2 == length/2 == length
+    assert 2/length == 1/length
+    x = Symbol('x')
+    m = x*length
+    assert m == length*x and m.is_Mul and set(m.args) == {x, length}
+    d = x/length
+    assert d == x*length**-1 and d.is_Mul and set(d.args) == {x, 1/length}
+    d = length/x
+    assert d == length*x**-1 and d.is_Mul and set(d.args) == {1/x, length}
+
+    velo = length / time
+
+    assert (length * length) == length ** 2
+
+    assert dimsys_SI.get_dimensional_dependencies(length * length) == {length: 2}
+    assert dimsys_SI.get_dimensional_dependencies(length ** 2) == {length: 2}
+    assert dimsys_SI.get_dimensional_dependencies(length * time) == {length: 1, time: 1}
+    assert dimsys_SI.get_dimensional_dependencies(velo) == {length: 1, time: -1}
+    assert dimsys_SI.get_dimensional_dependencies(velo ** 2) == {length: 2, time: -2}
+
+    assert dimsys_SI.get_dimensional_dependencies(length / length) == {}
+    assert dimsys_SI.get_dimensional_dependencies(velo / length * time) == {}
+    assert dimsys_SI.get_dimensional_dependencies(length ** -1) == {length: -1}
+    assert dimsys_SI.get_dimensional_dependencies(velo ** -1.5) == {length: -1.5, time: 1.5}
+
+    length_a = length**"a"
+    assert dimsys_SI.get_dimensional_dependencies(length_a) == {length: Symbol("a")}
+
+    assert dimsys_SI.get_dimensional_dependencies(length**pi) == {length: pi}
+    assert dimsys_SI.get_dimensional_dependencies(length**(length/length)) == {length: Dimension(1)}
+
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(length**length))
+
+    assert length != 1
+    assert length / length != 1
+
+    length_0 = length ** 0
+    assert dimsys_SI.get_dimensional_dependencies(length_0) == {}
+
+    # issue 18738
+    a = Symbol('a')
+    b = Symbol('b')
+    c = sqrt(a**2 + b**2)
+    c_dim = c.subs({a: length, b: length})
+    assert dimsys_SI.equivalent_dims(c_dim, length)
+
+def test_Dimension_functions():
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(cos(length)))
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(acos(angle)))
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(atan2(length, time)))
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(log(length)))
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(log(100, length)))
+    raises(TypeError, lambda: dimsys_SI.get_dimensional_dependencies(log(length, 10)))
+
+    assert dimsys_SI.get_dimensional_dependencies(pi) == {}
+
+    assert dimsys_SI.get_dimensional_dependencies(cos(1)) == {}
+    assert dimsys_SI.get_dimensional_dependencies(cos(angle)) == {}
+
+    assert dimsys_SI.get_dimensional_dependencies(atan2(length, length)) == {}
+
+    assert dimsys_SI.get_dimensional_dependencies(log(length / length, length / length)) == {}
+
+    assert dimsys_SI.get_dimensional_dependencies(Abs(length)) == {length: 1}
+    assert dimsys_SI.get_dimensional_dependencies(Abs(length / length)) == {}
+
+    assert dimsys_SI.get_dimensional_dependencies(sqrt(-1)) == {}

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/tests/test_prefixes.py

@@ -0,0 +1,86 @@
+from sympy.core.mul import Mul
+from sympy.core.numbers import Rational
+from sympy.core.singleton import S
+from sympy.core.symbol import (Symbol, symbols)
+from sympy.physics.units import Quantity, length, meter, W
+from sympy.physics.units.prefixes import PREFIXES, Prefix, prefix_unit, kilo, \
+    kibi
+from sympy.physics.units.systems import SI
+
+x = Symbol('x')
+
+
+def test_prefix_operations():
+    m = PREFIXES['m']
+    k = PREFIXES['k']
+    M = PREFIXES['M']
+
+    dodeca = Prefix('dodeca', 'dd', 1, base=12)
+
+    assert m * k is S.One
+    assert m * W == W / 1000
+    assert k * k == M
+    assert 1 / m == k
+    assert k / m == M
+
+    assert dodeca * dodeca == 144
+    assert 1 / dodeca == S.One / 12
+    assert k / dodeca == S(1000) / 12
+    assert dodeca / dodeca is S.One
+
+    m = Quantity("fake_meter")
+    SI.set_quantity_dimension(m, S.One)
+    SI.set_quantity_scale_factor(m, S.One)
+
+    assert dodeca * m == 12 * m
+    assert dodeca / m == 12 / m
+
+    expr1 = kilo * 3
+    assert isinstance(expr1, Mul)
+    assert expr1.args == (3, kilo)
+
+    expr2 = kilo * x
+    assert isinstance(expr2, Mul)
+    assert expr2.args == (x, kilo)
+
+    expr3 = kilo / 3
+    assert isinstance(expr3, Mul)
+    assert expr3.args == (Rational(1, 3), kilo)
+    assert expr3.args == (S.One/3, kilo)
+
+    expr4 = kilo / x
+    assert isinstance(expr4, Mul)
+    assert expr4.args == (1/x, kilo)
+
+
+def test_prefix_unit():
+    m = Quantity("fake_meter", abbrev="m")
+    m.set_global_relative_scale_factor(1, meter)
+
+    pref = {"m": PREFIXES["m"], "c": PREFIXES["c"], "d": PREFIXES["d"]}
+
+    q1 = Quantity("millifake_meter", abbrev="mm")
+    q2 = Quantity("centifake_meter", abbrev="cm")
+    q3 = Quantity("decifake_meter", abbrev="dm")
+
+    SI.set_quantity_dimension(q1, length)
+
+    SI.set_quantity_scale_factor(q1, PREFIXES["m"])
+    SI.set_quantity_scale_factor(q1, PREFIXES["c"])
+    SI.set_quantity_scale_factor(q1, PREFIXES["d"])
+
+    res = [q1, q2, q3]
+
+    prefs = prefix_unit(m, pref)
+    assert set(prefs) == set(res)
+    assert {v.abbrev for v in prefs} == set(symbols("mm,cm,dm"))
+
+
+def test_bases():
+    assert kilo.base == 10
+    assert kibi.base == 2
+
+
+def test_repr():
+    assert eval(repr(kilo)) == kilo
+    assert eval(repr(kibi)) == kibi

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/tests/test_unit_system_cgs_gauss.py

@@ -0,0 +1,55 @@
+from sympy.concrete.tests.test_sums_products import NS
+
+from sympy.core.singleton import S
+from sympy.functions.elementary.miscellaneous import sqrt
+from sympy.physics.units import convert_to, coulomb_constant, elementary_charge, gravitational_constant, planck
+from sympy.physics.units.definitions.unit_definitions import angstrom, statcoulomb, coulomb, second, gram, centimeter, erg, \
+    newton, joule, dyne, speed_of_light, meter, farad, henry, statvolt, volt, ohm
+from sympy.physics.units.systems import SI
+from sympy.physics.units.systems.cgs import cgs_gauss
+
+
+def test_conversion_to_from_si():
+    assert convert_to(statcoulomb, coulomb, cgs_gauss) == coulomb/2997924580
+    assert convert_to(coulomb, statcoulomb, cgs_gauss) == 2997924580*statcoulomb
+    assert convert_to(statcoulomb, sqrt(gram*centimeter**3)/second, cgs_gauss) == centimeter**(S(3)/2)*sqrt(gram)/second
+    assert convert_to(coulomb, sqrt(gram*centimeter**3)/second, cgs_gauss) == 2997924580*centimeter**(S(3)/2)*sqrt(gram)/second
+
+    # SI units have an additional base unit, no conversion in case of electromagnetism:
+    assert convert_to(coulomb, statcoulomb, SI) == coulomb
+    assert convert_to(statcoulomb, coulomb, SI) == statcoulomb
+
+    # SI without electromagnetism:
+    assert convert_to(erg, joule, SI) == joule/10**7
+    assert convert_to(erg, joule, cgs_gauss) == joule/10**7
+    assert convert_to(joule, erg, SI) == 10**7*erg
+    assert convert_to(joule, erg, cgs_gauss) == 10**7*erg
+
+
+    assert convert_to(dyne, newton, SI) == newton/10**5
+    assert convert_to(dyne, newton, cgs_gauss) == newton/10**5
+    assert convert_to(newton, dyne, SI) == 10**5*dyne
+    assert convert_to(newton, dyne, cgs_gauss) == 10**5*dyne
+
+
+def test_cgs_gauss_convert_constants():
+
+    assert convert_to(speed_of_light, centimeter/second, cgs_gauss) == 29979245800*centimeter/second
+
+    assert convert_to(coulomb_constant, 1, cgs_gauss) == 1
+    assert convert_to(coulomb_constant, newton*meter**2/coulomb**2, cgs_gauss) == 22468879468420441*meter**2*newton/(2500000*coulomb**2)
+    assert convert_to(coulomb_constant, newton*meter**2/coulomb**2, SI) == 22468879468420441*meter**2*newton/(2500000*coulomb**2)
+    assert convert_to(coulomb_constant, dyne*centimeter**2/statcoulomb**2, cgs_gauss) == centimeter**2*dyne/statcoulomb**2
+    assert convert_to(coulomb_constant, 1, SI) == coulomb_constant
+    assert NS(convert_to(coulomb_constant, newton*meter**2/coulomb**2, SI)) == '8987551787.36818*meter**2*newton/coulomb**2'
+
+    assert convert_to(elementary_charge, statcoulomb, cgs_gauss)
+    assert convert_to(angstrom, centimeter, cgs_gauss) == 1*centimeter/10**8
+    assert convert_to(gravitational_constant, dyne*centimeter**2/gram**2, cgs_gauss)
+    assert NS(convert_to(planck, erg*second, cgs_gauss)) == '6.62607015e-27*erg*second'
+
+    spc = 25000*second/(22468879468420441*centimeter)
+    assert convert_to(ohm, second/centimeter, cgs_gauss) == spc
+    assert convert_to(henry, second**2/centimeter, cgs_gauss) == spc*second
+    assert convert_to(volt, statvolt, cgs_gauss) == 10**6*statvolt/299792458
+    assert convert_to(farad, centimeter, cgs_gauss) == 299792458**2*centimeter/10**5

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/tests/test_unitsystem.py

@@ -0,0 +1,86 @@
+from sympy.physics.units import DimensionSystem, joule, second, ampere
+
+from sympy.core.numbers import Rational
+from sympy.core.singleton import S
+from sympy.physics.units.definitions import c, kg, m, s
+from sympy.physics.units.definitions.dimension_definitions import length, time
+from sympy.physics.units.quantities import Quantity
+from sympy.physics.units.unitsystem import UnitSystem
+from sympy.physics.units.util import convert_to
+
+
+def test_definition():
+    # want to test if the system can have several units of the same dimension
+    dm = Quantity("dm")
+    base = (m, s)
+    # base_dim = (m.dimension, s.dimension)
+    ms = UnitSystem(base, (c, dm), "MS", "MS system")
+    ms.set_quantity_dimension(dm, length)
+    ms.set_quantity_scale_factor(dm, Rational(1, 10))
+
+    assert set(ms._base_units) == set(base)
+    assert set(ms._units) == {m, s, c, dm}
+    # assert ms._units == DimensionSystem._sort_dims(base + (velocity,))
+    assert ms.name == "MS"
+    assert ms.descr == "MS system"
+
+
+def test_str_repr():
+    assert str(UnitSystem((m, s), name="MS")) == "MS"
+    assert str(UnitSystem((m, s))) == "UnitSystem((meter, second))"
+
+    assert repr(UnitSystem((m, s))) == "<UnitSystem: (%s, %s)>" % (m, s)
+
+
+def test_convert_to():
+    A = Quantity("A")
+    A.set_global_relative_scale_factor(S.One, ampere)
+
+    Js = Quantity("Js")
+    Js.set_global_relative_scale_factor(S.One, joule*second)
+
+    mksa = UnitSystem((m, kg, s, A), (Js,))
+    assert convert_to(Js, mksa._base_units) == m**2*kg*s**-1/1000
+
+
+def test_extend():
+    ms = UnitSystem((m, s), (c,))
+    Js = Quantity("Js")
+    Js.set_global_relative_scale_factor(1, joule*second)
+    mks = ms.extend((kg,), (Js,))
+
+    res = UnitSystem((m, s, kg), (c, Js))
+    assert set(mks._base_units) == set(res._base_units)
+    assert set(mks._units) == set(res._units)
+
+
+def test_dim():
+    dimsys = UnitSystem((m, kg, s), (c,))
+    assert dimsys.dim == 3
+
+
+def test_is_consistent():
+    dimension_system = DimensionSystem([length, time])
+    us = UnitSystem([m, s], dimension_system=dimension_system)
+    assert us.is_consistent == True
+
+
+def test_get_units_non_prefixed():
+    from sympy.physics.units import volt, ohm
+    unit_system = UnitSystem.get_unit_system("SI")
+    units = unit_system.get_units_non_prefixed()
+    for prefix in ["giga", "tera", "peta", "exa", "zetta", "yotta", "kilo", "hecto", "deca", "deci", "centi", "milli", "micro", "nano", "pico", "femto", "atto", "zepto", "yocto"]:
+        for unit in units:
+            assert isinstance(unit, Quantity), f"{unit} must be a Quantity, not {type(unit)}"
+            assert not unit.is_prefixed, f"{unit} is marked as prefixed"
+            assert not unit.is_physical_constant, f"{unit} is marked as physics constant"
+            assert not unit.name.name.startswith(prefix), f"Unit {unit.name} has prefix {prefix}"
+    assert volt in units
+    assert ohm in units
+
+def test_derived_units_must_exist_in_unit_system():
+    for unit_system in UnitSystem._unit_systems.values():
+        for preferred_unit in unit_system.derived_units.values():
+            units = preferred_unit.atoms(Quantity)
+            for unit in units:
+                assert unit in unit_system._units, f"Unit {unit} is not in unit system {unit_system}"

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/tests/test_util.py

@@ -0,0 +1,178 @@
+from sympy.core.containers import Tuple
+from sympy.core.numbers import pi
+from sympy.core.power import Pow
+from sympy.core.symbol import symbols
+from sympy.core.sympify import sympify
+from sympy.printing.str import sstr
+from sympy.physics.units import (
+    G, centimeter, coulomb, day, degree, gram, hbar, hour, inch, joule, kelvin,
+    kilogram, kilometer, length, meter, mile, minute, newton, planck,
+    planck_length, planck_mass, planck_temperature, planck_time, radians,
+    second, speed_of_light, steradian, time, km)
+from sympy.physics.units.util import convert_to, check_dimensions
+from sympy.testing.pytest import raises
+from sympy.functions.elementary.miscellaneous import sqrt
+
+
+def NS(e, n=15, **options):
+    return sstr(sympify(e).evalf(n, **options), full_prec=True)
+
+
+L = length
+T = time
+
+
+def test_dim_simplify_add():
+    # assert Add(L, L) == L
+    assert L + L == L
+
+
+def test_dim_simplify_mul():
+    # assert Mul(L, T) == L*T
+    assert L*T == L*T
+
+
+def test_dim_simplify_pow():
+    assert Pow(L, 2) == L**2
+
+
+def test_dim_simplify_rec():
+    # assert Mul(Add(L, L), T) == L*T
+    assert (L + L) * T == L*T
+
+
+def test_convert_to_quantities():
+    assert convert_to(3, meter) == 3
+
+    assert convert_to(mile, kilometer) == 25146*kilometer/15625
+    assert convert_to(meter/second, speed_of_light) == speed_of_light/299792458
+    assert convert_to(299792458*meter/second, speed_of_light) == speed_of_light
+    assert convert_to(2*299792458*meter/second, speed_of_light) == 2*speed_of_light
+    assert convert_to(speed_of_light, meter/second) == 299792458*meter/second
+    assert convert_to(2*speed_of_light, meter/second) == 599584916*meter/second
+    assert convert_to(day, second) == 86400*second
+    assert convert_to(2*hour, minute) == 120*minute
+    assert convert_to(mile, meter) == 201168*meter/125
+    assert convert_to(mile/hour, kilometer/hour) == 25146*kilometer/(15625*hour)
+    assert convert_to(3*newton, meter/second) == 3*newton
+    assert convert_to(3*newton, kilogram*meter/second**2) == 3*meter*kilogram/second**2
+    assert convert_to(kilometer + mile, meter) == 326168*meter/125
+    assert convert_to(2*kilometer + 3*mile, meter) == 853504*meter/125
+    assert convert_to(inch**2, meter**2) == 16129*meter**2/25000000
+    assert convert_to(3*inch**2, meter) == 48387*meter**2/25000000
+    assert convert_to(2*kilometer/hour + 3*mile/hour, meter/second) == 53344*meter/(28125*second)
+    assert convert_to(2*kilometer/hour + 3*mile/hour, centimeter/second) == 213376*centimeter/(1125*second)
+    assert convert_to(kilometer * (mile + kilometer), meter) == 2609344 * meter ** 2
+
+    assert convert_to(steradian, coulomb) == steradian
+    assert convert_to(radians, degree) == 180*degree/pi
+    assert convert_to(radians, [meter, degree]) == 180*degree/pi
+    assert convert_to(pi*radians, degree) == 180*degree
+    assert convert_to(pi, degree) == 180*degree
+
+    # https://github.com/sympy/sympy/issues/26263
+    assert convert_to(sqrt(meter**2 + meter**2.0), meter) == sqrt(meter**2 + meter**2.0)
+    assert convert_to((meter**2 + meter**2.0)**2, meter) == (meter**2 + meter**2.0)**2
+
+
+def test_convert_to_tuples_of_quantities():
+    from sympy.core.symbol import symbols
+
+    alpha, beta = symbols('alpha beta')
+
+    assert convert_to(speed_of_light, [meter, second]) == 299792458 * meter / second
+    assert convert_to(speed_of_light, (meter, second)) == 299792458 * meter / second
+    assert convert_to(speed_of_light, Tuple(meter, second)) == 299792458 * meter / second
+    assert convert_to(joule, [meter, kilogram, second]) == kilogram*meter**2/second**2
+    assert convert_to(joule, [centimeter, gram, second]) == 10000000*centimeter**2*gram/second**2
+    assert convert_to(299792458*meter/second, [speed_of_light]) == speed_of_light
+    assert convert_to(speed_of_light / 2, [meter, second, kilogram]) == meter/second*299792458 / 2
+    # This doesn't make physically sense, but let's keep it as a conversion test:
+    assert convert_to(2 * speed_of_light, [meter, second, kilogram]) == 2 * 299792458 * meter / second
+    assert convert_to(G, [G, speed_of_light, planck]) == 1.0*G
+
+    assert NS(convert_to(meter, [G, speed_of_light, hbar]), n=7) == '6.187142e+34*gravitational_constant**0.5000000*hbar**0.5000000/speed_of_light**1.500000'
+    assert NS(convert_to(planck_mass, kilogram), n=7) == '2.176434e-8*kilogram'
+    assert NS(convert_to(planck_length, meter), n=7) == '1.616255e-35*meter'
+    assert NS(convert_to(planck_time, second), n=6) == '5.39125e-44*second'
+    assert NS(convert_to(planck_temperature, kelvin), n=7) == '1.416784e+32*kelvin'
+    assert NS(convert_to(convert_to(meter, [G, speed_of_light, planck]), meter), n=10) == '1.000000000*meter'
+
+    # similar to https://github.com/sympy/sympy/issues/26263
+    assert convert_to(sqrt(meter**2 + second**2.0), [meter, second]) == sqrt(meter**2 + second**2.0)
+    assert convert_to((meter**2 + second**2.0)**2, [meter, second]) == (meter**2 + second**2.0)**2
+
+    # similar to https://github.com/sympy/sympy/issues/21463
+    assert convert_to(1/(beta*meter + meter), 1/meter) == 1/(beta*meter + meter)
+    assert convert_to(1/(beta*meter + alpha*meter), 1/kilometer) == (1/(kilometer*beta/1000 + alpha*kilometer/1000))
+
+def test_eval_simplify():
+    from sympy.physics.units import cm, mm, km, m, K, kilo
+    from sympy.core.symbol import symbols
+
+    x, y = symbols('x y')
+
+    assert (cm/mm).simplify() == 10
+    assert (km/m).simplify() == 1000
+    assert (km/cm).simplify() == 100000
+    assert (10*x*K*km**2/m/cm).simplify() == 1000000000*x*kelvin
+    assert (cm/km/m).simplify() == 1/(10000000*centimeter)
+
+    assert (3*kilo*meter).simplify() == 3000*meter
+    assert (4*kilo*meter/(2*kilometer)).simplify() == 2
+    assert (4*kilometer**2/(kilo*meter)**2).simplify() == 4
+
+
+def test_quantity_simplify():
+    from sympy.physics.units.util import quantity_simplify
+    from sympy.physics.units import kilo, foot
+    from sympy.core.symbol import symbols
+
+    x, y = symbols('x y')
+
+    assert quantity_simplify(x*(8*kilo*newton*meter + y)) == x*(8000*meter*newton + y)
+    assert quantity_simplify(foot*inch*(foot + inch)) == foot**2*(foot + foot/12)/12
+    assert quantity_simplify(foot*inch*(foot*foot + inch*(foot + inch))) == foot**2*(foot**2 + foot/12*(foot + foot/12))/12
+    assert quantity_simplify(2**(foot/inch*kilo/1000)*inch) == 4096*foot/12
+    assert quantity_simplify(foot**2*inch + inch**2*foot) == 13*foot**3/144
+
+def test_quantity_simplify_across_dimensions():
+    from sympy.physics.units.util import quantity_simplify
+    from sympy.physics.units import ampere, ohm, volt, joule, pascal, farad, second, watt, siemens, henry, tesla, weber, hour, newton
+
+    assert quantity_simplify(ampere*ohm, across_dimensions=True, unit_system="SI") == volt
+    assert quantity_simplify(6*ampere*ohm, across_dimensions=True, unit_system="SI") == 6*volt
+    assert quantity_simplify(volt/ampere, across_dimensions=True, unit_system="SI") == ohm
+    assert quantity_simplify(volt/ohm, across_dimensions=True, unit_system="SI") == ampere
+    assert quantity_simplify(joule/meter**3, across_dimensions=True, unit_system="SI") == pascal
+    assert quantity_simplify(farad*ohm, across_dimensions=True, unit_system="SI") == second
+    assert quantity_simplify(joule/second, across_dimensions=True, unit_system="SI") == watt
+    assert quantity_simplify(meter**3/second, across_dimensions=True, unit_system="SI") == meter**3/second
+    assert quantity_simplify(joule/second, across_dimensions=True, unit_system="SI") == watt
+
+    assert quantity_simplify(joule/coulomb, across_dimensions=True, unit_system="SI") == volt
+    assert quantity_simplify(volt/ampere, across_dimensions=True, unit_system="SI") == ohm
+    assert quantity_simplify(ampere/volt, across_dimensions=True, unit_system="SI") == siemens
+    assert quantity_simplify(coulomb/volt, across_dimensions=True, unit_system="SI") == farad
+    assert quantity_simplify(volt*second/ampere, across_dimensions=True, unit_system="SI") == henry
+    assert quantity_simplify(volt*second/meter**2, across_dimensions=True, unit_system="SI") == tesla
+    assert quantity_simplify(joule/ampere, across_dimensions=True, unit_system="SI") == weber
+
+    assert quantity_simplify(5*kilometer/hour, across_dimensions=True, unit_system="SI") == 25*meter/(18*second)
+    assert quantity_simplify(5*kilogram*meter/second**2, across_dimensions=True, unit_system="SI") == 5*newton
+
+def test_check_dimensions():
+    x = symbols('x')
+    assert check_dimensions(inch + x) == inch + x
+    assert check_dimensions(length + x) == length + x
+    # after subs we get 2*length; check will clear the constant
+    assert check_dimensions((length + x).subs(x, length)) == length
+    assert check_dimensions(newton*meter + joule) == joule + meter*newton
+    raises(ValueError, lambda: check_dimensions(inch + 1))
+    raises(ValueError, lambda: check_dimensions(length + 1))
+    raises(ValueError, lambda: check_dimensions(length + time))
+    raises(ValueError, lambda: check_dimensions(meter + second))
+    raises(ValueError, lambda: check_dimensions(2 * meter + second))
+    raises(ValueError, lambda: check_dimensions(2 * meter + 3 * second))
+    raises(ValueError, lambda: check_dimensions(1 / second + 1 / meter))
+    raises(ValueError, lambda: check_dimensions(2 * meter*(mile + centimeter) + km))

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/unitsystem.py

@@ -0,0 +1,205 @@
+"""
+Unit system for physical quantities; include definition of constants.
+"""
+
+from typing import Dict as tDict, Set as tSet
+
+from sympy.core.add import Add
+from sympy.core.function import (Derivative, Function)
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.singleton import S
+from sympy.physics.units.dimensions import _QuantityMapper
+from sympy.physics.units.quantities import Quantity
+
+from .dimensions import Dimension
+
+
+class UnitSystem(_QuantityMapper):
+    """
+    UnitSystem represents a coherent set of units.
+
+    A unit system is basically a dimension system with notions of scales. Many
+    of the methods are defined in the same way.
+
+    It is much better if all base units have a symbol.
+    """
+
+    _unit_systems = {}  # type: tDict[str, UnitSystem]
+
+    def __init__(self, base_units, units=(), name="", descr="", dimension_system=None, derived_units: tDict[Dimension, Quantity]={}):
+
+        UnitSystem._unit_systems[name] = self
+
+        self.name = name
+        self.descr = descr
+
+        self._base_units = base_units
+        self._dimension_system = dimension_system
+        self._units = tuple(set(base_units) | set(units))
+        self._base_units = tuple(base_units)
+        self._derived_units = derived_units
+
+        super().__init__()
+
+    def __str__(self):
+        """
+        Return the name of the system.
+
+        If it does not exist, then it makes a list of symbols (or names) of
+        the base dimensions.
+        """
+
+        if self.name != "":
+            return self.name
+        else:
+            return "UnitSystem((%s))" % ", ".join(
+                str(d) for d in self._base_units)
+
+    def __repr__(self):
+        return '<UnitSystem: %s>' % repr(self._base_units)
+
+    def extend(self, base, units=(), name="", description="", dimension_system=None, derived_units: tDict[Dimension, Quantity]={}):
+        """Extend the current system into a new one.
+
+        Take the base and normal units of the current system to merge
+        them to the base and normal units given in argument.
+        If not provided, name and description are overridden by empty strings.
+        """
+
+        base = self._base_units + tuple(base)
+        units = self._units + tuple(units)
+
+        return UnitSystem(base, units, name, description, dimension_system, {**self._derived_units, **derived_units})
+
+    def get_dimension_system(self):
+        return self._dimension_system
+
+    def get_quantity_dimension(self, unit):
+        qdm = self.get_dimension_system()._quantity_dimension_map
+        if unit in qdm:
+            return qdm[unit]
+        return super().get_quantity_dimension(unit)
+
+    def get_quantity_scale_factor(self, unit):
+        qsfm = self.get_dimension_system()._quantity_scale_factors
+        if unit in qsfm:
+            return qsfm[unit]
+        return super().get_quantity_scale_factor(unit)
+
+    @staticmethod
+    def get_unit_system(unit_system):
+        if isinstance(unit_system, UnitSystem):
+            return unit_system
+
+        if unit_system not in UnitSystem._unit_systems:
+            raise ValueError(
+                "Unit system is not supported. Currently"
+                "supported unit systems are {}".format(
+                    ", ".join(sorted(UnitSystem._unit_systems))
+                )
+            )
+
+        return UnitSystem._unit_systems[unit_system]
+
+    @staticmethod
+    def get_default_unit_system():
+        return UnitSystem._unit_systems["SI"]
+
+    @property
+    def dim(self):
+        """
+        Give the dimension of the system.
+
+        That is return the number of units forming the basis.
+        """
+        return len(self._base_units)
+
+    @property
+    def is_consistent(self):
+        """
+        Check if the underlying dimension system is consistent.
+        """
+        # test is performed in DimensionSystem
+        return self.get_dimension_system().is_consistent
+
+    @property
+    def derived_units(self) -> tDict[Dimension, Quantity]:
+        return self._derived_units
+
+    def get_dimensional_expr(self, expr):
+        from sympy.physics.units import Quantity
+        if isinstance(expr, Mul):
+            return Mul(*[self.get_dimensional_expr(i) for i in expr.args])
+        elif isinstance(expr, Pow):
+            return self.get_dimensional_expr(expr.base) ** expr.exp
+        elif isinstance(expr, Add):
+            return self.get_dimensional_expr(expr.args[0])
+        elif isinstance(expr, Derivative):
+            dim = self.get_dimensional_expr(expr.expr)
+            for independent, count in expr.variable_count:
+                dim /= self.get_dimensional_expr(independent)**count
+            return dim
+        elif isinstance(expr, Function):
+            args = [self.get_dimensional_expr(arg) for arg in expr.args]
+            if all(i == 1 for i in args):
+                return S.One
+            return expr.func(*args)
+        elif isinstance(expr, Quantity):
+            return self.get_quantity_dimension(expr).name
+        return S.One
+
+    def _collect_factor_and_dimension(self, expr):
+        """
+        Return tuple with scale factor expression and dimension expression.
+        """
+        from sympy.physics.units import Quantity
+        if isinstance(expr, Quantity):
+            return expr.scale_factor, expr.dimension
+        elif isinstance(expr, Mul):
+            factor = 1
+            dimension = Dimension(1)
+            for arg in expr.args:
+                arg_factor, arg_dim = self._collect_factor_and_dimension(arg)
+                factor *= arg_factor
+                dimension *= arg_dim
+            return factor, dimension
+        elif isinstance(expr, Pow):
+            factor, dim = self._collect_factor_and_dimension(expr.base)
+            exp_factor, exp_dim = self._collect_factor_and_dimension(expr.exp)
+            if self.get_dimension_system().is_dimensionless(exp_dim):
+                exp_dim = 1
+            return factor ** exp_factor, dim ** (exp_factor * exp_dim)
+        elif isinstance(expr, Add):
+            factor, dim = self._collect_factor_and_dimension(expr.args[0])
+            for addend in expr.args[1:]:
+                addend_factor, addend_dim = \
+                    self._collect_factor_and_dimension(addend)
+                if not self.get_dimension_system().equivalent_dims(dim, addend_dim):
+                    raise ValueError(
+                        'Dimension of "{}" is {}, '
+                        'but it should be {}'.format(
+                            addend, addend_dim, dim))
+                factor += addend_factor
+            return factor, dim
+        elif isinstance(expr, Derivative):
+            factor, dim = self._collect_factor_and_dimension(expr.args[0])
+            for independent, count in expr.variable_count:
+                ifactor, idim = self._collect_factor_and_dimension(independent)
+                factor /= ifactor**count
+                dim /= idim**count
+            return factor, dim
+        elif isinstance(expr, Function):
+            fds = [self._collect_factor_and_dimension(arg) for arg in expr.args]
+            dims = [Dimension(1) if self.get_dimension_system().is_dimensionless(d[1]) else d[1] for d in fds]
+            return (expr.func(*(f[0] for f in fds)), *dims)
+        elif isinstance(expr, Dimension):
+            return S.One, expr
+        else:
+            return expr, Dimension(1)
+
+    def get_units_non_prefixed(self) -> tSet[Quantity]:
+        """
+        Return the units of the system that do not have a prefix.
+        """
+        return set(filter(lambda u: not u.is_prefixed and not u.is_physical_constant, self._units))

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/units/util.py

@@ -0,0 +1,265 @@
+"""
+Several methods to simplify expressions involving unit objects.
+"""
+from functools import reduce
+from collections.abc import Iterable
+from typing import Optional
+
+from sympy import default_sort_key
+from sympy.core.add import Add
+from sympy.core.containers import Tuple
+from sympy.core.mul import Mul
+from sympy.core.power import Pow
+from sympy.core.sorting import ordered
+from sympy.core.sympify import sympify
+from sympy.core.function import Function
+from sympy.matrices.exceptions import NonInvertibleMatrixError
+from sympy.physics.units.dimensions import Dimension, DimensionSystem
+from sympy.physics.units.prefixes import Prefix
+from sympy.physics.units.quantities import Quantity
+from sympy.physics.units.unitsystem import UnitSystem
+from sympy.utilities.iterables import sift
+
+
+def _get_conversion_matrix_for_expr(expr, target_units, unit_system):
+    from sympy.matrices.dense import Matrix
+
+    dimension_system = unit_system.get_dimension_system()
+
+    expr_dim = Dimension(unit_system.get_dimensional_expr(expr))
+    dim_dependencies = dimension_system.get_dimensional_dependencies(expr_dim, mark_dimensionless=True)
+    target_dims = [Dimension(unit_system.get_dimensional_expr(x)) for x in target_units]
+    canon_dim_units = [i for x in target_dims for i in dimension_system.get_dimensional_dependencies(x, mark_dimensionless=True)]
+    canon_expr_units = set(dim_dependencies)
+
+    if not canon_expr_units.issubset(set(canon_dim_units)):
+        return None
+
+    seen = set()
+    canon_dim_units = [i for i in canon_dim_units if not (i in seen or seen.add(i))]
+
+    camat = Matrix([[dimension_system.get_dimensional_dependencies(i, mark_dimensionless=True).get(j, 0) for i in target_dims] for j in canon_dim_units])
+    exprmat = Matrix([dim_dependencies.get(k, 0) for k in canon_dim_units])
+
+    try:
+        res_exponents = camat.solve(exprmat)
+    except NonInvertibleMatrixError:
+        return None
+
+    return res_exponents
+
+
+def convert_to(expr, target_units, unit_system="SI"):
+    """
+    Convert ``expr`` to the same expression with all of its units and quantities
+    represented as factors of ``target_units``, whenever the dimension is compatible.
+
+    ``target_units`` may be a single unit/quantity, or a collection of
+    units/quantities.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.units import speed_of_light, meter, gram, second, day
+    >>> from sympy.physics.units import mile, newton, kilogram, atomic_mass_constant
+    >>> from sympy.physics.units import kilometer, centimeter
+    >>> from sympy.physics.units import gravitational_constant, hbar
+    >>> from sympy.physics.units import convert_to
+    >>> convert_to(mile, kilometer)
+    25146*kilometer/15625
+    >>> convert_to(mile, kilometer).n()
+    1.609344*kilometer
+    >>> convert_to(speed_of_light, meter/second)
+    299792458*meter/second
+    >>> convert_to(day, second)
+    86400*second
+    >>> 3*newton
+    3*newton
+    >>> convert_to(3*newton, kilogram*meter/second**2)
+    3*kilogram*meter/second**2
+    >>> convert_to(atomic_mass_constant, gram)
+    1.660539060e-24*gram
+
+    Conversion to multiple units:
+
+    >>> convert_to(speed_of_light, [meter, second])
+    299792458*meter/second
+    >>> convert_to(3*newton, [centimeter, gram, second])
+    300000*centimeter*gram/second**2
+
+    Conversion to Planck units:
+
+    >>> convert_to(atomic_mass_constant, [gravitational_constant, speed_of_light, hbar]).n()
+    7.62963087839509e-20*hbar**0.5*speed_of_light**0.5/gravitational_constant**0.5
+
+    """
+    from sympy.physics.units import UnitSystem
+    unit_system = UnitSystem.get_unit_system(unit_system)
+
+    if not isinstance(target_units, (Iterable, Tuple)):
+        target_units = [target_units]
+
+    def handle_Adds(expr):
+        return Add.fromiter(convert_to(i, target_units, unit_system)
+            for i in expr.args)
+
+    if isinstance(expr, Add):
+        return handle_Adds(expr)
+    elif isinstance(expr, Pow) and isinstance(expr.base, Add):
+        return handle_Adds(expr.base) ** expr.exp
+
+    expr = sympify(expr)
+    target_units = sympify(target_units)
+
+    if isinstance(expr, Function):
+        expr = expr.together()
+
+    if not isinstance(expr, Quantity) and expr.has(Quantity):
+        expr = expr.replace(lambda x: isinstance(x, Quantity),
+            lambda x: x.convert_to(target_units, unit_system))
+
+    def get_total_scale_factor(expr):
+        if isinstance(expr, Mul):
+            return reduce(lambda x, y: x * y,
+                [get_total_scale_factor(i) for i in expr.args])
+        elif isinstance(expr, Pow):
+            return get_total_scale_factor(expr.base) ** expr.exp
+        elif isinstance(expr, Quantity):
+            return unit_system.get_quantity_scale_factor(expr)
+        return expr
+
+    depmat = _get_conversion_matrix_for_expr(expr, target_units, unit_system)
+    if depmat is None:
+        return expr
+
+    expr_scale_factor = get_total_scale_factor(expr)
+    return expr_scale_factor * Mul.fromiter(
+        (1/get_total_scale_factor(u)*u)**p for u, p in
+        zip(target_units, depmat))
+
+
+def quantity_simplify(expr, across_dimensions: bool=False, unit_system=None):
+    """Return an equivalent expression in which prefixes are replaced
+    with numerical values and all units of a given dimension are the
+    unified in a canonical manner by default. `across_dimensions` allows
+    for units of different dimensions to be simplified together.
+
+    `unit_system` must be specified if `across_dimensions` is True.
+
+    Examples
+    ========
+
+    >>> from sympy.physics.units.util import quantity_simplify
+    >>> from sympy.physics.units.prefixes import kilo
+    >>> from sympy.physics.units import foot, inch, joule, coulomb
+    >>> quantity_simplify(kilo*foot*inch)
+    250*foot**2/3
+    >>> quantity_simplify(foot - 6*inch)
+    foot/2
+    >>> quantity_simplify(5*joule/coulomb, across_dimensions=True, unit_system="SI")
+    5*volt
+    """
+
+    if expr.is_Atom or not expr.has(Prefix, Quantity):
+        return expr
+
+    # replace all prefixes with numerical values
+    p = expr.atoms(Prefix)
+    expr = expr.xreplace({p: p.scale_factor for p in p})
+
+    # replace all quantities of given dimension with a canonical
+    # quantity, chosen from those in the expression
+    d = sift(expr.atoms(Quantity), lambda i: i.dimension)
+    for k in d:
+        if len(d[k]) == 1:
+            continue
+        v = list(ordered(d[k]))
+        ref = v[0]/v[0].scale_factor
+        expr = expr.xreplace({vi: ref*vi.scale_factor for vi in v[1:]})
+
+    if across_dimensions:
+        # combine quantities of different dimensions into a single
+        # quantity that is equivalent to the original expression
+
+        if unit_system is None:
+            raise ValueError("unit_system must be specified if across_dimensions is True")
+
+        unit_system = UnitSystem.get_unit_system(unit_system)
+        dimension_system: DimensionSystem = unit_system.get_dimension_system()
+        dim_expr = unit_system.get_dimensional_expr(expr)
+        dim_deps = dimension_system.get_dimensional_dependencies(dim_expr, mark_dimensionless=True)
+
+        target_dimension: Optional[Dimension] = None
+        for ds_dim, ds_dim_deps in dimension_system.dimensional_dependencies.items():
+            if ds_dim_deps == dim_deps:
+                target_dimension = ds_dim
+                break
+
+        if target_dimension is None:
+            # if we can't find a target dimension, we can't do anything. unsure how to handle this case.
+            return expr
+
+        target_unit = unit_system.derived_units.get(target_dimension)
+        if target_unit:
+            expr = convert_to(expr, target_unit, unit_system)
+
+    return expr
+
+
+def check_dimensions(expr, unit_system="SI"):
+    """Return expr if units in addends have the same
+    base dimensions, else raise a ValueError."""
+    # the case of adding a number to a dimensional quantity
+    # is ignored for the sake of SymPy core routines, so this
+    # function will raise an error now if such an addend is
+    # found.
+    # Also, when doing substitutions, multiplicative constants
+    # might be introduced, so remove those now
+
+    from sympy.physics.units import UnitSystem
+    unit_system = UnitSystem.get_unit_system(unit_system)
+
+    def addDict(dict1, dict2):
+        """Merge dictionaries by adding values of common keys and
+        removing keys with value of 0."""
+        dict3 = {**dict1, **dict2}
+        for key, value in dict3.items():
+            if key in dict1 and key in dict2:
+                   dict3[key] = value + dict1[key]
+        return {key:val for key, val in dict3.items() if val != 0}
+
+    adds = expr.atoms(Add)
+    DIM_OF = unit_system.get_dimension_system().get_dimensional_dependencies
+    for a in adds:
+        deset = set()
+        for ai in a.args:
+            if ai.is_number:
+                deset.add(())
+                continue
+            dims = []
+            skip = False
+            dimdict = {}
+            for i in Mul.make_args(ai):
+                if i.has(Quantity):
+                    i = Dimension(unit_system.get_dimensional_expr(i))
+                if i.has(Dimension):
+                    dimdict = addDict(dimdict, DIM_OF(i))
+                elif i.free_symbols:
+                    skip = True
+                    break
+            dims.extend(dimdict.items())
+            if not skip:
+                deset.add(tuple(sorted(dims, key=default_sort_key)))
+                if len(deset) > 1:
+                    raise ValueError(
+                        "addends have incompatible dimensions: {}".format(deset))
+
+    # clear multiplicative constants on Dimensions which may be
+    # left after substitution
+    reps = {}
+    for m in expr.atoms(Mul):
+        if any(isinstance(i, Dimension) for i in m.args):
+            reps[m] = m.func(*[
+                i for i in m.args if not i.is_number])
+
+    return expr.xreplace(reps)

tuning-competition-baseline/.venv/lib/python3.11/site-packages/sympy/physics/vector/tests/test_vector.py

@@ -0,0 +1,274 @@
+from sympy.core.numbers import (Float, pi)
+from sympy.core.symbol import symbols
+from sympy.core.sorting import ordered
+from sympy.functions.elementary.trigonometric import (cos, sin)
+from sympy.matrices.immutable import ImmutableDenseMatrix as Matrix
+from sympy.physics.vector import ReferenceFrame, Vector, dynamicsymbols, dot
+from sympy.physics.vector.vector import VectorTypeError
+from sympy.abc import x, y, z
+from sympy.testing.pytest import raises
+
+A = ReferenceFrame('A')
+
+
+def test_free_dynamicsymbols():
+    A, B, C, D = symbols('A, B, C, D', cls=ReferenceFrame)
+    a, b, c, d, e, f = dynamicsymbols('a, b, c, d, e, f')
+    B.orient_axis(A, a, A.x)
+    C.orient_axis(B, b, B.y)
+    D.orient_axis(C, c, C.x)
+
+    v = d*D.x + e*D.y + f*D.z
+
+    assert set(ordered(v.free_dynamicsymbols(A))) == {a, b, c, d, e, f}
+    assert set(ordered(v.free_dynamicsymbols(B))) == {b, c, d, e, f}
+    assert set(ordered(v.free_dynamicsymbols(C))) == {c, d, e, f}
+    assert set(ordered(v.free_dynamicsymbols(D))) == {d, e, f}
+
+
+def test_Vector():
+    assert A.x != A.y
+    assert A.y != A.z
+    assert A.z != A.x
+
+    assert A.x + 0 == A.x
+
+    v1 = x*A.x + y*A.y + z*A.z
+    v2 = x**2*A.x + y**2*A.y + z**2*A.z
+    v3 = v1 + v2
+    v4 = v1 - v2
+
+    assert isinstance(v1, Vector)
+    assert dot(v1, A.x) == x
+    assert dot(v1, A.y) == y
+    assert dot(v1, A.z) == z
+
+    assert isinstance(v2, Vector)
+    assert dot(v2, A.x) == x**2
+    assert dot(v2, A.y) == y**2
+    assert dot(v2, A.z) == z**2
+
+    assert isinstance(v3, Vector)
+    # We probably shouldn't be using simplify in dot...
+    assert dot(v3, A.x) == x**2 + x
+    assert dot(v3, A.y) == y**2 + y
+    assert dot(v3, A.z) == z**2 + z
+
+    assert isinstance(v4, Vector)
+    # We probably shouldn't be using simplify in dot...
+    assert dot(v4, A.x) == x - x**2
+    assert dot(v4, A.y) == y - y**2
+    assert dot(v4, A.z) == z - z**2
+
+    assert v1.to_matrix(A) == Matrix([[x], [y], [z]])
+    q = symbols('q')
+    B = A.orientnew('B', 'Axis', (q, A.x))
+    assert v1.to_matrix(B) == Matrix([[x],
+                                      [ y * cos(q) + z * sin(q)],
+                                      [-y * sin(q) + z * cos(q)]])
+
+    #Test the separate method
+    B = ReferenceFrame('B')
+    v5 = x*A.x + y*A.y + z*B.z
+    assert Vector(0).separate() == {}
+    assert v1.separate() == {A: v1}
+    assert v5.separate() == {A: x*A.x + y*A.y, B: z*B.z}
+
+    #Test the free_symbols property
+    v6 = x*A.x + y*A.y + z*A.z
+    assert v6.free_symbols(A) == {x,y,z}
+
+    raises(TypeError, lambda: v3.applyfunc(v1))
+
+
+def test_Vector_diffs():
+    q1, q2, q3, q4 = dynamicsymbols('q1 q2 q3 q4')
+    q1d, q2d, q3d, q4d = dynamicsymbols('q1 q2 q3 q4', 1)
+    q1dd, q2dd, q3dd, q4dd = dynamicsymbols('q1 q2 q3 q4', 2)
+    N = ReferenceFrame('N')
+    A = N.orientnew('A', 'Axis', [q3, N.z])
+    B = A.orientnew('B', 'Axis', [q2, A.x])
+    v1 = q2 * A.x + q3 * N.y
+    v2 = q3 * B.x + v1
+    v3 = v1.dt(B)
+    v4 = v2.dt(B)
+    v5 = q1*A.x + q2*A.y + q3*A.z
+
+    assert v1.dt(N) == q2d * A.x + q2 * q3d * A.y + q3d * N.y
+    assert v1.dt(A) == q2d * A.x + q3 * q3d * N.x + q3d * N.y
+    assert v1.dt(B) == (q2d * A.x + q3 * q3d * N.x + q3d *
+                        N.y - q3 * cos(q3) * q2d * N.z)
+    assert v2.dt(N) == (q2d * A.x + (q2 + q3) * q3d * A.y + q3d * B.x + q3d *
+                        N.y)
+    assert v2.dt(A) == q2d * A.x + q3d * B.x + q3 * q3d * N.x + q3d * N.y
+    assert v2.dt(B) == (q2d * A.x + q3d * B.x + q3 * q3d * N.x + q3d * N.y -
+                        q3 * cos(q3) * q2d * N.z)
+    assert v3.dt(N) == (q2dd * A.x + q2d * q3d * A.y + (q3d**2 + q3 * q3dd) *
+                        N.x + q3dd * N.y + (q3 * sin(q3) * q2d * q3d -
+                        cos(q3) * q2d * q3d - q3 * cos(q3) * q2dd) * N.z)
+    assert v3.dt(A) == (q2dd * A.x + (2 * q3d**2 + q3 * q3dd) * N.x + (q3dd -
+                        q3 * q3d**2) * N.y + (q3 * sin(q3) * q2d * q3d -
+                        cos(q3) * q2d * q3d - q3 * cos(q3) * q2dd) * N.z)
+    assert (v3.dt(B) - (q2dd*A.x - q3*cos(q3)*q2d**2*A.y + (2*q3d**2 +
+        q3*q3dd)*N.x + (q3dd - q3*q3d**2)*N.y + (2*q3*sin(q3)*q2d*q3d -
+        2*cos(q3)*q2d*q3d - q3*cos(q3)*q2dd)*N.z)).express(B).simplify() == 0
+    assert v4.dt(N) == (q2dd * A.x + q3d * (q2d + q3d) * A.y + q3dd * B.x +
+                        (q3d**2 + q3 * q3dd) * N.x + q3dd * N.y + (q3 *
+                        sin(q3) * q2d * q3d - cos(q3) * q2d * q3d - q3 *
+                        cos(q3) * q2dd) * N.z)
+    assert v4.dt(A) == (q2dd * A.x + q3dd * B.x + (2 * q3d**2 + q3 * q3dd) *
+                        N.x + (q3dd - q3 * q3d**2) * N.y + (q3 * sin(q3) *
+                        q2d * q3d - cos(q3) * q2d * q3d - q3 * cos(q3) *
+                        q2dd) * N.z)
+    assert (v4.dt(B) - (q2dd*A.x - q3*cos(q3)*q2d**2*A.y + q3dd*B.x +
+                        (2*q3d**2 + q3*q3dd)*N.x + (q3dd - q3*q3d**2)*N.y +
+                        (2*q3*sin(q3)*q2d*q3d - 2*cos(q3)*q2d*q3d -
+                         q3*cos(q3)*q2dd)*N.z)).express(B).simplify() == 0
+    assert v5.dt(B) == q1d*A.x + (q3*q2d + q2d)*A.y + (-q2*q2d + q3d)*A.z
+    assert v5.dt(A) == q1d*A.x + q2d*A.y + q3d*A.z
+    assert v5.dt(N) == (-q2*q3d + q1d)*A.x + (q1*q3d + q2d)*A.y + q3d*A.z
+    assert v3.diff(q1d, N) == 0
+    assert v3.diff(q2d, N) == A.x - q3 * cos(q3) * N.z
+    assert v3.diff(q3d, N) == q3 * N.x + N.y
+    assert v3.diff(q1d, A) == 0
+    assert v3.diff(q2d, A) == A.x - q3 * cos(q3) * N.z
+    assert v3.diff(q3d, A) == q3 * N.x + N.y
+    assert v3.diff(q1d, B) == 0
+    assert v3.diff(q2d, B) == A.x - q3 * cos(q3) * N.z
+    assert v3.diff(q3d, B) == q3 * N.x + N.y
+    assert v4.diff(q1d, N) == 0
+    assert v4.diff(q2d, N) == A.x - q3 * cos(q3) * N.z
+    assert v4.diff(q3d, N) == B.x + q3 * N.x + N.y
+    assert v4.diff(q1d, A) == 0
+    assert v4.diff(q2d, A) == A.x - q3 * cos(q3) * N.z
+    assert v4.diff(q3d, A) == B.x + q3 * N.x + N.y
+    assert v4.diff(q1d, B) == 0
+    assert v4.diff(q2d, B) == A.x - q3 * cos(q3) * N.z
+    assert v4.diff(q3d, B) == B.x + q3 * N.x + N.y
+
+    # diff() should only express vector components in the derivative frame if
+    # the orientation of the component's frame depends on the variable
+    v6 = q2**2*N.y + q2**2*A.y + q2**2*B.y
+    # already expressed in N
+    n_measy = 2*q2
+    # A_C_N does not depend on q2, so don't express in N
+    a_measy = 2*q2
+    # B_C_N depends on q2, so express in N
+    b_measx = (q2**2*B.y).dot(N.x).diff(q2)
+    b_measy = (q2**2*B.y).dot(N.y).diff(q2)
+    b_measz = (q2**2*B.y).dot(N.z).diff(q2)
+    n_comp, a_comp = v6.diff(q2, N).args
+    assert len(v6.diff(q2, N).args) == 2  # only N and A parts
+    assert n_comp[1] == N
+    assert a_comp[1] == A
+    assert n_comp[0] == Matrix([b_measx, b_measy + n_measy, b_measz])
+    assert a_comp[0] == Matrix([0, a_measy, 0])
+
+
+def test_vector_var_in_dcm():
+
+    N = ReferenceFrame('N')
+    A = ReferenceFrame('A')
+    B = ReferenceFrame('B')
+    u1, u2, u3, u4 = dynamicsymbols('u1 u2 u3 u4')
+
+    v = u1 * u2 * A.x + u3 * N.y + u4**2 * N.z
+
+    assert v.diff(u1, N, var_in_dcm=False) == u2 * A.x
+    assert v.diff(u1, A, var_in_dcm=False) == u2 * A.x
+    assert v.diff(u3, N, var_in_dcm=False) == N.y
+    assert v.diff(u3, A, var_in_dcm=False) == N.y
+    assert v.diff(u3, B, var_in_dcm=False) == N.y
+    assert v.diff(u4, N, var_in_dcm=False) == 2 * u4 * N.z
+
+    raises(ValueError, lambda: v.diff(u1, N))
+
+
+def test_vector_simplify():
+    x, y, z, k, n, m, w, f, s, A = symbols('x, y, z, k, n, m, w, f, s, A')
+    N = ReferenceFrame('N')
+
+    test1 = (1 / x + 1 / y) * N.x
+    assert (test1 & N.x) != (x + y) / (x * y)
+    test1 = test1.simplify()
+    assert (test1 & N.x) == (x + y) / (x * y)
+
+    test2 = (A**2 * s**4 / (4 * pi * k * m**3)) * N.x
+    test2 = test2.simplify()
+    assert (test2 & N.x) == (A**2 * s**4 / (4 * pi * k * m**3))
+
+    test3 = ((4 + 4 * x - 2 * (2 + 2 * x)) / (2 + 2 * x)) * N.x
+    test3 = test3.simplify()
+    assert (test3 & N.x) == 0
+
+    test4 = ((-4 * x * y**2 - 2 * y**3 - 2 * x**2 * y) / (x + y)**2) * N.x
+    test4 = test4.simplify()
+    assert (test4 & N.x) == -2 * y
+
+
+def test_vector_evalf():
+    a, b = symbols('a b')
+    v = pi * A.x
+    assert v.evalf(2) == Float('3.1416', 2) * A.x
+    v = pi * A.x + 5 * a * A.y - b * A.z
+    assert v.evalf(3) == Float('3.1416', 3) * A.x + Float('5', 3) * a * A.y - b * A.z
+    assert v.evalf(5, subs={a: 1.234, b:5.8973}) == Float('3.1415926536', 5) * A.x + Float('6.17', 5) * A.y - Float('5.8973', 5) * A.z
+
+
+def test_vector_angle():
+    A = ReferenceFrame('A')
+    v1 = A.x + A.y
+    v2 = A.z
+    assert v1.angle_between(v2) == pi/2
+    B = ReferenceFrame('B')
+    B.orient_axis(A, A.x, pi)
+    v3 = A.x
+    v4 = B.x
+    assert v3.angle_between(v4) == 0
+
+
+def test_vector_xreplace():
+    x, y, z = symbols('x y z')
+    v = x**2 * A.x + x*y * A.y + x*y*z * A.z
+    assert v.xreplace({x : cos(x)}) == cos(x)**2 * A.x + y*cos(x) * A.y + y*z*cos(x) * A.z
+    assert v.xreplace({x*y : pi}) == x**2 * A.x + pi * A.y + x*y*z * A.z
+    assert v.xreplace({x*y*z : 1}) == x**2*A.x + x*y*A.y + A.z
+    assert v.xreplace({x:1, z:0}) == A.x + y * A.y
+    raises(TypeError, lambda: v.xreplace())
+    raises(TypeError, lambda: v.xreplace([x, y]))
+
+def test_issue_23366():
+    u1 = dynamicsymbols('u1')
+    N = ReferenceFrame('N')
+    N_v_A = u1*N.x
+    raises(VectorTypeError, lambda: N_v_A.diff(N, u1))
+
+
+def test_vector_outer():
+    a, b, c, d, e, f = symbols('a, b, c, d, e, f')
+    N = ReferenceFrame('N')
+    v1 = a*N.x + b*N.y + c*N.z
+    v2 = d*N.x + e*N.y + f*N.z
+    v1v2 = Matrix([[a*d, a*e, a*f],
+                   [b*d, b*e, b*f],
+                   [c*d, c*e, c*f]])
+    assert v1.outer(v2).to_matrix(N) == v1v2
+    assert (v1 | v2).to_matrix(N) == v1v2
+    v2v1 = Matrix([[d*a, d*b, d*c],
+                   [e*a, e*b, e*c],
+                   [f*a, f*b, f*c]])
+    assert v2.outer(v1).to_matrix(N) == v2v1
+    assert (v2 | v1).to_matrix(N) == v2v1
+
+
+def test_overloaded_operators():
+    a, b, c, d, e, f = symbols('a, b, c, d, e, f')
+    N = ReferenceFrame('N')
+    v1 = a*N.x + b*N.y + c*N.z
+    v2 = d*N.x + e*N.y + f*N.z
+
+    assert v1 + v2 == v2 + v1
+    assert v1 - v2 == -v2 + v1
+    assert v1 & v2 == v2 & v1
+    assert v1 ^ v2 == v1.cross(v2)
+    assert v2 ^ v1 == v2.cross(v1)