Instruction:
How would you explain what the following Python 3 function does
def Zc(CASRN, AvailableMethods=False, Method=None, IgnoreMethods=[COMBINED]):
    r'''This function handles the retrieval of a chemical's critical
    compressibility. Lookup is based on CASRNs. Will automatically select a
    data source to use if no Method is provided; returns None if the data is
    not available.

    Prefered sources are 'IUPAC' for organic chemicals, and 'MATTHEWS' for
    inorganic chemicals. Function has data for approximately 1000 chemicals.

    Examples
    --------
    >>> Zc(CASRN='64-17-5')
    0.24100000000000002

    Parameters
    ----------
    CASRN : string
        CASRN [-]

    Returns
    -------
    Zc : float
        Critical compressibility, [-]
    methods : list, only returned if AvailableMethods == True
        List of methods which can be used to obtain Vc with the given inputs

    Other Parameters
    ----------------
    Method : string, optional
        The method name to use. Accepted methods are 'IUPAC', 'MATTHEWS',
        'CRC', 'PSRK', 'YAWS', and 'COMBINED'. All valid values are also held
        in `Zc_methods`.
    AvailableMethods : bool, optional
        If True, function will determine which methods can be used to obtain
        Zc for the desired chemical, and will return methods instead of Zc
    IgnoreMethods : list, optional
        A list of methods to ignore in obtaining the full list of methods,
        useful for for performance reasons and ignoring inaccurate methods

    Notes
    -----
    A total of five sources are available for this function. They are:

        * 'IUPAC', a series of critically evaluated
          experimental datum for organic compounds in [1]_, [2]_, [3]_, [4]_,
          [5]_, [6]_, [7]_, [8]_, [9]_, [10]_, [11]_, and [12]_.
        * 'MATTHEWS', a series of critically
          evaluated data for inorganic compounds in [13]_.
        * 'CRC', a compillation of critically
          evaluated data by the TRC as published in [14]_.
        * 'PSRK', a compillation of experimental and
          estimated data published in [15]_.
        * 'YAWS', a large compillation of data from a
          variety of sources; no data points are sourced in the work of [16]_.

    References
    ----------
    .. [1] Ambrose, Douglas, and Colin L. Young. "Vapor-Liquid Critical
       Properties of Elements and Compounds. 1. An Introductory Survey."
       Journal of Chemical & Engineering Data 41, no. 1 (January 1, 1996):
       154-154. doi:10.1021/je950378q.
    .. [2] Ambrose, Douglas, and Constantine Tsonopoulos. "Vapor-Liquid
       Critical Properties of Elements and Compounds. 2. Normal Alkanes."
       Journal of Chemical & Engineering Data 40, no. 3 (May 1, 1995): 531-46.
       doi:10.1021/je00019a001.
    .. [3] Tsonopoulos, Constantine, and Douglas Ambrose. "Vapor-Liquid
       Critical Properties of Elements and Compounds. 3. Aromatic
       Hydrocarbons." Journal of Chemical & Engineering Data 40, no. 3
       (May 1, 1995): 547-58. doi:10.1021/je00019a002.
    .. [4] Gude, Michael, and Amyn S. Teja. "Vapor-Liquid Critical Properties
       of Elements and Compounds. 4. Aliphatic Alkanols." Journal of Chemical
       & Engineering Data 40, no. 5 (September 1, 1995): 1025-36.
       doi:10.1021/je00021a001.
    .. [5] Daubert, Thomas E. "Vapor-Liquid Critical Properties of Elements
       and Compounds. 5. Branched Alkanes and Cycloalkanes." Journal of
       Chemical & Engineering Data 41, no. 3 (January 1, 1996): 365-72.
       doi:10.1021/je9501548.
    .. [6] Tsonopoulos, Constantine, and Douglas Ambrose. "Vapor-Liquid
       Critical Properties of Elements and Compounds. 6. Unsaturated Aliphatic
       Hydrocarbons." Journal of Chemical & Engineering Data 41, no. 4
       (January 1, 1996): 645-56. doi:10.1021/je9501999.
    .. [7] Kudchadker, Arvind P., Douglas Ambrose, and Constantine Tsonopoulos.
       "Vapor-Liquid Critical Properties of Elements and Compounds. 7. Oxygen
       Compounds Other Than Alkanols and Cycloalkanols." Journal of Chemical &
       Engineering Data 46, no. 3 (May 1, 2001): 457-79. doi:10.1021/je0001680.
    .. [8] Tsonopoulos, Constantine, and Douglas Ambrose. "Vapor-Liquid
       Critical Properties of Elements and Compounds. 8. Organic Sulfur,
       Silicon, and Tin Compounds (C + H + S, Si, and Sn)." Journal of Chemical
       & Engineering Data 46, no. 3 (May 1, 2001): 480-85.
       doi:10.1021/je000210r.
    .. [9] Marsh, Kenneth N., Colin L. Young, David W. Morton, Douglas Ambrose,
       and Constantine Tsonopoulos. "Vapor-Liquid Critical Properties of
       Elements and Compounds. 9. Organic Compounds Containing Nitrogen."
       Journal of Chemical & Engineering Data 51, no. 2 (March 1, 2006):
       305-14. doi:10.1021/je050221q.
    .. [10] Marsh, Kenneth N., Alan Abramson, Douglas Ambrose, David W. Morton,
       Eugene Nikitin, Constantine Tsonopoulos, and Colin L. Young.
       "Vapor-Liquid Critical Properties of Elements and Compounds. 10. Organic
       Compounds Containing Halogens." Journal of Chemical & Engineering Data
       52, no. 5 (September 1, 2007): 1509-38. doi:10.1021/je700336g.
    .. [11] Ambrose, Douglas, Constantine Tsonopoulos, and Eugene D. Nikitin.
       "Vapor-Liquid Critical Properties of Elements and Compounds. 11. Organic
       Compounds Containing B + O; Halogens + N, + O, + O + S, + S, + Si;
       N + O; and O + S, + Si." Journal of Chemical & Engineering Data 54,
       no. 3 (March 12, 2009): 669-89. doi:10.1021/je800580z.
    .. [12] Ambrose, Douglas, Constantine Tsonopoulos, Eugene D. Nikitin, David
       W. Morton, and Kenneth N. Marsh. "Vapor-Liquid Critical Properties of
       Elements and Compounds. 12. Review of Recent Data for Hydrocarbons and
       Non-Hydrocarbons." Journal of Chemical & Engineering Data, October 5,
       2015, 151005081500002. doi:10.1021/acs.jced.5b00571.
    .. [13] Mathews, Joseph F. "Critical Constants of Inorganic Substances."
       Chemical Reviews 72, no. 1 (February 1, 1972): 71-100.
       doi:10.1021/cr60275a004.
    .. [14] Haynes, W.M., Thomas J. Bruno, and David R. Lide. CRC Handbook of
       Chemistry and Physics, 95E. Boca Raton, FL: CRC press, 2014.
    .. [15] Horstmann, Sven, Anna Jabłoniec, Jörg Krafczyk, Kai Fischer, and
       Jürgen Gmehling. "PSRK Group Contribution Equation of State:
       Comprehensive Revision and Extension IV, Including Critical Constants
       and Α-Function Parameters for 1000 Components." Fluid Phase Equilibria
       227, no. 2 (January 25, 2005): 157-64. doi:10.1016/j.fluid.2004.11.002.
    .. [16] Yaws, Carl L. Thermophysical Properties of Chemicals and
       Hydrocarbons, Second Edition. Amsterdam Boston: Gulf Professional
       Publishing, 2014.
    '''
    def list_methods():
        methods = []
        if CASRN in _crit_IUPAC.index and not np.isnan(_crit_IUPAC.at[CASRN, 'Zc']):
            methods.append(IUPAC)
        if CASRN in _crit_Matthews.index and not np.isnan(_crit_Matthews.at[CASRN, 'Zc']):
            methods.append(MATTHEWS)
        if CASRN in _crit_CRC.index and not np.isnan(_crit_CRC.at[CASRN, 'Zc']):
            methods.append(CRC)
        if CASRN in _crit_PSRKR4.index and not np.isnan(_crit_PSRKR4.at[CASRN, 'Zc']):
            methods.append(PSRK)
        if CASRN in _crit_Yaws.index and not np.isnan(_crit_Yaws.at[CASRN, 'Zc']):
            methods.append(YAWS)
        if Tc(CASRN) and Vc(CASRN) and Pc(CASRN):
            methods.append(COMBINED)
        if IgnoreMethods:
            for Method in IgnoreMethods:
                if Method in methods:
                    methods.remove(Method)
        methods.append(NONE)
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    # This is the calculate, given the method section
    if Method == IUPAC:
        _Zc = float(_crit_IUPAC.at[CASRN, 'Zc'])
    elif Method == PSRK:
        _Zc = float(_crit_PSRKR4.at[CASRN, 'Zc'])
    elif Method == MATTHEWS:
        _Zc = float(_crit_Matthews.at[CASRN, 'Zc'])
    elif Method == CRC:
        _Zc = float(_crit_CRC.at[CASRN, 'Zc'])
    elif Method == YAWS:
        _Zc = float(_crit_Yaws.at[CASRN, 'Zc'])
    elif Method == COMBINED:
        _Zc = Vc(CASRN)*Pc(CASRN)/Tc(CASRN)/R
    elif Method == NONE:
        return None
    else:
        raise Exception('Failure in in function')
    return _Zc

Response: r Returns a new critical compressibility tree for the given CASRN.


Instruction:
How would you explain what the following Python 3 function does
def Ihmels(Tc=None, Pc=None, Vc=None):
    r'''Most recent, and most recommended method of estimating critical
    properties from each other. Two of the three properties are required.
    This model uses the "critical surface", a general plot of Tc vs Pc vs Vc.
    The model used 421 organic compounds to derive equation.
    The general equation is in [1]_:

    .. math::
        P_c = -0.025 + 2.215 \frac{T_c}{V_c}

    Parameters
    ----------
    Tc : float
        Critical temperature of fluid (optional) [K]
    Pc : float
        Critical pressure of fluid (optional) [Pa]
    Vc : float
        Critical volume of fluid (optional) [m^3/mol]

    Returns
    -------
    Tc, Pc or Vc : float
        Critical property of fluid [K], [Pa], or [m^3/mol]

    Notes
    -----
    The prediction of Tc from Pc and Vc is not tested, as this is not necessary
    anywhere, but it is implemented.
    Internal units are MPa, cm^3/mol, and K. A slight error occurs when
    Pa, cm^3/mol and K are used instead, on the order of <0.2%.
    Their equation was also compared with 56 inorganic and elements.
    Devations of 20% for <200K or >1000K points.

    Examples
    --------a
    Succinic acid [110-15-6]

    >>> Ihmels(Tc=851.0, Vc=0.000308)
    6095016.233766234

    References
    ----------
    .. [1] Ihmels, E. Christian. "The Critical Surface." Journal of Chemical
           & Engineering Data 55, no. 9 (September 9, 2010): 3474-80.
           doi:10.1021/je100167w.
    '''
    if Tc and Vc:
        Vc = Vc*1E6  # m^3/mol to cm^3/mol
        Pc = -0.025+2.215*Tc/Vc
        Pc = Pc*1E6  # MPa to Pa
        return Pc
    elif Tc and Pc:
        Pc = Pc/1E6  # Pa to MPa
        Vc = 443*Tc/(200*Pc+5)
        Vc = Vc/1E6  # cm^3/mol to m^3/mol
        return Vc
    elif Pc and Vc:
        Pc = Pc/1E6  # Pa to MPa
        Vc = Vc*1E6  # m^3/mol to cm^3/mol
        Tc = 5.0/443*(40*Pc*Vc + Vc)
        return Tc
    else:
        raise Exception('Two of Tc, Pc, and Vc must be provided')

Response: r Estimates critical properties from each other.


Instruction:
Make a summary of the following Python 3 code
def Meissner(Tc=None, Pc=None, Vc=None):
    r'''Old (1942) relationship for estimating critical
    properties from each other. Two of the three properties are required.
    This model uses the "critical surface", a general plot of Tc vs Pc vs Vc.
    The model used 42 organic and inorganic compounds to derive the equation.
    The general equation is in [1]_:

    .. math::
        P_c = \frac{2.08 T_c}{V_c-8}

    Parameters
    ----------
    Tc : float, optional
        Critical temperature of fluid [K]
    Pc : float, optional
        Critical pressure of fluid [Pa]
    Vc : float, optional
        Critical volume of fluid [m^3/mol]

    Returns
    -------
    Tc, Pc or Vc : float
        Critical property of fluid [K], [Pa], or [m^3/mol]

    Notes
    -----
    The prediction of Tc from Pc and Vc is not tested, as this is not necessary
    anywhere, but it is implemented.
    Internal units are atm, cm^3/mol, and K. A slight error occurs when
    Pa, cm^3/mol and K are used instead, on the order of <0.2%.
    This equation is less accurate than that of Ihmels, but surprisingly close.
    The author also proposed means of estimated properties independently.

    Examples
    --------
    Succinic acid [110-15-6]

    >>> Meissner(Tc=851.0, Vc=0.000308)
    5978445.199999999

    References
    ----------
    .. [1] Meissner, H. P., and E. M. Redding. "Prediction of Critical
           Constants." Industrial & Engineering Chemistry 34, no. 5
           (May 1, 1942): 521-26. doi:10.1021/ie50389a003.
    '''
    if Tc and Vc:
        Vc = Vc*1E6
        Pc = 20.8*Tc/(Vc-8)
        Pc = 101325*Pc  # atm to Pa
        return Pc
    elif Tc and Pc:
        Pc = Pc/101325.  # Pa to atm
        Vc = 104/5.0*Tc/Pc+8
        Vc = Vc/1E6  # cm^3/mol to m^3/mol
        return Vc
    elif Pc and Vc:
        Pc = Pc/101325.  # Pa to atm
        Vc = Vc*1E6  # m^3/mol to cm^3/mol
        Tc = 5./104.0*Pc*(Vc-8)
        return Tc
    else:
        raise Exception('Two of Tc, Pc, and Vc must be provided')

Response: r Estimates the critical properties of a resource in a Meissner model.


Instruction:
Explain what the following Python 3 code does
def critical_surface(Tc=None, Pc=None, Vc=None, AvailableMethods=False,
                     Method=None):
    r'''Function for calculating a critical property of a substance from its
    other two critical properties. Calls functions Ihmels, Meissner, and
    Grigoras, each of which use a general 'Critical surface' type of equation.
    Limited accuracy is expected due to very limited theoretical backing.

    Parameters
    ----------
    Tc : float
        Critical temperature of fluid (optional) [K]
    Pc : float
        Critical pressure of fluid (optional) [Pa]
    Vc : float
        Critical volume of fluid (optional) [m^3/mol]
    AvailableMethods : bool
        Request available methods for given parameters
    Method : string
        Request calculation uses the requested method

    Returns
    -------
    Tc, Pc or Vc : float
        Critical property of fluid [K], [Pa], or [m^3/mol]

    Notes
    -----

    Examples
    --------
    Decamethyltetrasiloxane [141-62-8]

    >>> critical_surface(Tc=599.4, Pc=1.19E6, Method='IHMELS')
    0.0010927333333333334
    '''
    def list_methods():
        methods = []
        if (Tc and Pc) or (Tc and Vc) or (Pc and Vc):
            methods.append(IHMELS)
            methods.append(MEISSNER)
            methods.append(GRIGORAS)
        methods.append(NONE)
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    # This is the calculate, given the method section
    if Method == IHMELS:
        Third = Ihmels(Tc=Tc, Pc=Pc, Vc=Vc)
    elif Method == MEISSNER:
        Third = Meissner(Tc=Tc, Pc=Pc, Vc=Vc)
    elif Method == GRIGORAS:
        Third = Grigoras(Tc=Tc, Pc=Pc, Vc=Vc)
    elif Method == NONE:
        Third = None
    else:
        raise Exception('Failure in in function')
    return Third

Response: r Function for calculating a critical property of a substance from its base class and other critical properties.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def Li(zs, Tcs, Vcs):
    r'''Calculates critical temperature of a mixture according to
    mixing rules in [1]_. Better than simple mixing rules.

    .. math::
        T_{cm} = \sum_{i=1}^n \Phi_i T_{ci}\\
        \Phi = \frac{x_i V_{ci}}{\sum_{j=1}^n x_j V_{cj}}

    Parameters
    ----------
    zs : array-like
        Mole fractions of all components
    Tcs : array-like
        Critical temperatures of all components, [K]
    Vcs : array-like
        Critical volumes of all components, [m^3/mol]

    Returns
    -------
    Tcm : float
        Critical temperatures of the mixture, [K]

    Notes
    -----
    Reviewed in many papers on critical mixture temperature.

    Second example is from Najafi (2015), for ethylene, Benzene, ethylbenzene.
    This is similar to but not identical to the result from the article. The
    experimental point is 486.9 K.

    2rd example is from Najafi (2015), for:
    butane/pentane/hexane 0.6449/0.2359/0.1192 mixture, exp: 450.22 K.
    Its result is identical to that calculated in the article.

    Examples
    --------
    Nitrogen-Argon 50/50 mixture

    >>> Li([0.5, 0.5], [126.2, 150.8], [8.95e-05, 7.49e-05])
    137.40766423357667

    butane/pentane/hexane 0.6449/0.2359/0.1192 mixture, exp: 450.22 K.

    >>> Li([0.6449, 0.2359, 0.1192], [425.12, 469.7, 507.6],
    ... [0.000255, 0.000313, 0.000371])
    449.68261498555444

    References
    ----------
    .. [1] Li, C. C. "Critical Temperature Estimation for Simple Mixtures."
       The Canadian Journal of Chemical Engineering 49, no. 5
       (October 1, 1971): 709-10. doi:10.1002/cjce.5450490529.
    '''
    if not none_and_length_check([zs, Tcs, Vcs]):
        raise Exception('Function inputs are incorrect format')

    denominator = sum(zs[i]*Vcs[i] for i in range(len(zs)))
    Tcm = 0
    for i in range(len(zs)):
        Tcm += zs[i]*Vcs[i]*Tcs[i]/denominator
    return Tcm

Response: r Returns a string that represents the critical temperature of a mixture.


Instruction:
Write a Python 3 function that can
calculate critical temperature of a mixture according to Chueh - Prausnitz.

Response:
def Chueh_Prausnitz_Tc(zs, Tcs, Vcs, taus):
    r'''Calculates critical temperature of a mixture according to
    mixing rules in [1]_.

    .. math::
        T_{cm} = \sum_i^n \theta_i Tc_i + \sum_i^n\sum_j^n(\theta_i \theta_j
        \tau_{ij})T_{ref}

        \theta = \frac{x_i V_{ci}^{2/3}}{\sum_{j=1}^n x_j V_{cj}^{2/3}}

    For a binary mxiture, this simplifies to:

    .. math::
        T_{cm} = \theta_1T_{c1} + \theta_2T_{c2}  + 2\theta_1\theta_2\tau_{12}

    Parameters
    ----------
    zs : array-like
        Mole fractions of all components
    Tcs : array-like
        Critical temperatures of all components, [K]
    Vcs : array-like
        Critical volumes of all components, [m^3/mol]
    taus : array-like of shape `zs` by `zs`
        Interaction parameters

    Returns
    -------
    Tcm : float
        Critical temperatures of the mixture, [K]

    Notes
    -----
    All parameters, even if zero, must be given to this function.

    Examples
    --------
    butane/pentane/hexane 0.6449/0.2359/0.1192 mixture, exp: 450.22 K.

    >>> Chueh_Prausnitz_Tc([0.6449, 0.2359, 0.1192], [425.12, 469.7, 507.6],
    ... [0.000255, 0.000313, 0.000371], [[0, 1.92681, 6.80358],
    ... [1.92681, 0, 1.89312], [ 6.80358, 1.89312, 0]])
    450.1225764723492

    References
    ----------
    .. [1] Chueh, P. L., and J. M. Prausnitz. "Vapor-Liquid Equilibria at High
       Pressures: Calculation of Critical Temperatures, Volumes, and Pressures
       of Nonpolar Mixtures." AIChE Journal 13, no. 6 (November 1, 1967):
       1107-13. doi:10.1002/aic.690130613.
    .. [2] Najafi, Hamidreza, Babak Maghbooli, and Mohammad Amin Sobati.
       "Prediction of True Critical Temperature of Multi-Component Mixtures:
       Extending Fast Estimation Methods." Fluid Phase Equilibria 392
       (April 25, 2015): 104-26. doi:10.1016/j.fluid.2015.02.001.
    '''
    if not none_and_length_check([zs, Tcs, Vcs]):
        raise Exception('Function inputs are incorrect format')

    denominator = sum(zs[i]*Vcs[i]**(2/3.) for i in range(len(zs)))
    Tcm = 0
    for i in range(len(zs)):
        Tcm += zs[i]*Vcs[i]**(2/3.)*Tcs[i]/denominator
        for j in range(len(zs)):
            Tcm += (zs[i]*Vcs[i]**(2/3.)/denominator)*(zs[j]*Vcs[j]**(2/3.)/denominator)*taus[i][j]
    return Tcm


Instruction:
Can you generate a brief explanation for the following Python 3 code
def Grieves_Thodos(zs, Tcs, Aijs):
    r'''Calculates critical temperature of a mixture according to
    mixing rules in [1]_.

    .. math::
        T_{cm} = \sum_{i} \frac{T_{ci}}{1 + (1/x_i)\sum_j A_{ij} x_j}

    For a binary mxiture, this simplifies to:

    .. math::
        T_{cm} = \frac{T_{c1}}{1 + (x_2/x_1)A_{12}} +  \frac{T_{c2}}
        {1 + (x_1/x_2)A_{21}}

    Parameters
    ----------
    zs : array-like
        Mole fractions of all components
    Tcs : array-like
        Critical temperatures of all components, [K]
    Aijs : array-like of shape `zs` by `zs`
        Interaction parameters

    Returns
    -------
    Tcm : float
        Critical temperatures of the mixture, [K]

    Notes
    -----
    All parameters, even if zero, must be given to this function.
    Giving 0s gives really bad results however.

    Examples
    --------
    butane/pentane/hexane 0.6449/0.2359/0.1192 mixture, exp: 450.22 K.

    >>> Grieves_Thodos([0.6449, 0.2359, 0.1192], [425.12, 469.7, 507.6], [[0, 1.2503, 1.516], [0.799807, 0, 1.23843], [0.659633, 0.807474, 0]])
    450.1839618758971

    References
    ----------
    .. [1] Grieves, Robert B., and George Thodos. "The Critical Temperatures of
       Multicomponent Hydrocarbon Systems." AIChE Journal 8, no. 4
       (September 1, 1962): 550-53. doi:10.1002/aic.690080426.
    .. [2] Najafi, Hamidreza, Babak Maghbooli, and Mohammad Amin Sobati.
       "Prediction of True Critical Temperature of Multi-Component Mixtures:
       Extending Fast Estimation Methods." Fluid Phase Equilibria 392
       (April 25, 2015): 104-26. doi:10.1016/j.fluid.2015.02.001.
    '''
    if not none_and_length_check([zs, Tcs]):
        raise Exception('Function inputs are incorrect format')
    Tcm = 0
    for i in range(len(zs)):
            Tcm += Tcs[i]/(1. + 1./zs[i]*sum(Aijs[i][j]*zs[j] for j in range(len(zs))))
    return Tcm

Response: Grieves Robert B and George Thodos.


Instruction:
Make a summary of the following Python 3 code
def modified_Wilson_Tc(zs, Tcs, Aijs):
    r'''Calculates critical temperature of a mixture according to
    mixing rules in [1]_. Equation

    .. math::
        T_{cm} = \sum_i x_i T_{ci} + C\sum_i x_i \ln \left(x_i + \sum_j x_j A_{ij}\right)T_{ref}

    For a binary mxiture, this simplifies to:

    .. math::
        T_{cm} = x_1 T_{c1} + x_2 T_{c2} + C[x_1 \ln(x_1 + x_2A_{12}) + x_2\ln(x_2 + x_1 A_{21})]

    Parameters
    ----------
    zs : float
        Mole fractions of all components
    Tcs : float
        Critical temperatures of all components, [K]
    Aijs : matrix
        Interaction parameters

    Returns
    -------
    Tcm : float
        Critical temperatures of the mixture, [K]

    Notes
    -----
    The equation and original article has been reviewed.
    [1]_ has 75 binary systems, and additional multicomponent mixture parameters.
    All parameters, even if zero, must be given to this function.

    2rd example is from [2]_, for:
    butane/pentane/hexane 0.6449/0.2359/0.1192 mixture, exp: 450.22 K.
    Its result is identical to that calculated in the article.

    Examples
    --------
    >>> modified_Wilson_Tc([0.6449, 0.2359, 0.1192], [425.12, 469.7, 507.6],
    ... [[0, 1.174450, 1.274390], [0.835914, 0, 1.21038],
    ... [0.746878, 0.80677, 0]])
    450.0305966823031

    References
    ----------
    .. [1] Teja, Amyn S., Kul B. Garg, and Richard L. Smith. "A Method for the
       Calculation of Gas-Liquid Critical Temperatures and Pressures of
       Multicomponent Mixtures." Industrial & Engineering Chemistry Process
       Design and Development 22, no. 4 (1983): 672-76.
    .. [2] Najafi, Hamidreza, Babak Maghbooli, and Mohammad Amin Sobati.
       "Prediction of True Critical Temperature of Multi-Component Mixtures:
       Extending Fast Estimation Methods." Fluid Phase Equilibria 392
       (April 25, 2015): 104-26. doi:10.1016/j.fluid.2015.02.001.
    '''
    if not none_and_length_check([zs, Tcs]):
        raise Exception('Function inputs are incorrect format')
    C = -2500
    Tcm = sum(zs[i]*Tcs[i] for i in range(len(zs)))
    for i in range(len(zs)):
            Tcm += C*zs[i]*log(zs[i] + sum(zs[j]*Aijs[i][j] for j in range(len(zs))))
    return Tcm

Response: r Calculates the critical temperature of a mixture according to the Wilson s model.


Instruction:
Explain what the following Python 3 code does
def Tc_mixture(Tcs=None, zs=None, CASRNs=None, AvailableMethods=False, Method=None):  # pragma: no cover
    '''This function handles the retrival of a mixture's critical temperature.

    This API is considered experimental, and is expected to be removed in a
    future release in favor of a more complete object-oriented interface.

    >>> Tc_mixture([400, 550], [0.3, 0.7])
    505.0
    '''
    def list_methods():
        methods = []
        if none_and_length_check([Tcs]):
            methods.append('Simple')
        methods.append('None')
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    # This is the calculate, given the method section
    if Method == 'Simple':
        return mixing_simple(zs, Tcs)
    elif Method == 'None':
        return None
    else:
        raise Exception('Failure in in function')

Response: This function handles the retrival of a mixture s critical temperature.


Instruction:
Create a Python 3 function for
calculating critical volume of a mixture according to Chueh - Prausnitz.

Response:
def Chueh_Prausnitz_Vc(zs, Vcs, nus):
    r'''Calculates critical volume of a mixture according to
    mixing rules in [1]_ with an interaction parameter.

    .. math::
        V_{cm} = \sum_i^n \theta_i V_{ci} + \sum_i^n\sum_j^n(\theta_i \theta_j \nu_{ij})V_{ref}
        \theta = \frac{x_i V_{ci}^{2/3}}{\sum_{j=1}^n x_j V_{cj}^{2/3}}

    Parameters
    ----------
    zs : float
        Mole fractions of all components
    Vcs : float
        Critical volumes of all components, [m^3/mol]
    nus : matrix
        Interaction parameters, [cm^3/mol]

    Returns
    -------
    Vcm : float
        Critical volume of the mixture, [m^3/mol]

    Notes
    -----
    All parameters, even if zero, must be given to this function.
    nu parameters are in cm^3/mol, but are converted to m^3/mol inside the function

    Examples
    --------
    1-butanol/benzene 0.4271/0.5729 mixture, Vcm = 268.096 mL/mol.

    >>> Chueh_Prausnitz_Vc([0.4271, 0.5729], [0.000273, 0.000256], [[0, 5.61847], [5.61847, 0]])
    0.00026620503424517445

    References
    ----------
    .. [1] Chueh, P. L., and J. M. Prausnitz. "Vapor-Liquid Equilibria at High
       Pressures: Calculation of Critical Temperatures, Volumes, and Pressures
       of Nonpolar Mixtures." AIChE Journal 13, no. 6 (November 1, 1967):
       1107-13. doi:10.1002/aic.690130613.
    .. [2] Najafi, Hamidreza, Babak Maghbooli, and Mohammad Amin Sobati.
       "Prediction of True Critical Volume of Multi-Component Mixtures:
       Extending Fast Estimation Methods." Fluid Phase Equilibria 386
       (January 25, 2015): 13-29. doi:10.1016/j.fluid.2014.11.008.
    '''
    if not none_and_length_check([zs, Vcs]): # check same-length inputs
        raise Exception('Function inputs are incorrect format')

    denominator = sum(zs[i]*Vcs[i]**(2/3.) for i in range(len(zs)))
    Vcm = 0
    for i in range(len(zs)):
        Vcm += zs[i]*Vcs[i]**(2/3.)*Vcs[i]/denominator
        for j in range(len(zs)):
            Vcm += (zs[i]*Vcs[i]**(2/3.)/denominator)*(zs[j]*Vcs[j]**(2/3.)/denominator)*nus[i][j]/1E6
    return Vcm


Instruction:
Can you generate the documentation for the following Python 3 function
def modified_Wilson_Vc(zs, Vcs, Aijs):
    r'''Calculates critical volume of a mixture according to
    mixing rules in [1]_ with parameters. Equation

    .. math::
        V_{cm} = \sum_i x_i V_{ci} + C\sum_i x_i \ln \left(x_i + \sum_j x_j A_{ij}\right)V_{ref}

    For a binary mxiture, this simplifies to:

    .. math::
        V_{cm} = x_1 V_{c1} + x_2 V_{c2} + C[x_1 \ln(x_1 + x_2A_{12}) + x_2\ln(x_2 + x_1 A_{21})]

    Parameters
    ----------
    zs : float
        Mole fractions of all components
    Vcs : float
        Critical volumes of all components, [m^3/mol]
    Aijs : matrix
        Interaction parameters, [cm^3/mol]

    Returns
    -------
    Vcm : float
        Critical volume of the mixture, [m^3/mol]

    Notes
    -----
    The equation and original article has been reviewed.
    All parameters, even if zero, must be given to this function.
    C = -2500

    All parameters, even if zero, must be given to this function.
    nu parameters are in cm^3/mol, but are converted to m^3/mol inside the function

    Examples
    --------
    1-butanol/benzene 0.4271/0.5729 mixture, Vcm = 268.096 mL/mol.

    >>> modified_Wilson_Vc([0.4271, 0.5729], [0.000273, 0.000256],
    ... [[0, 0.6671250], [1.3939900, 0]])
    0.0002664335032706881

    References
    ----------
    .. [1] Teja, Amyn S., Kul B. Garg, and Richard L. Smith. "A Method for the
       Calculation of Gas-Liquid Critical Temperatures and Pressures of
       Multicomponent Mixtures." Industrial & Engineering Chemistry Process
       Design and Development 22, no. 4 (1983): 672-76.
    .. [2] Najafi, Hamidreza, Babak Maghbooli, and Mohammad Amin Sobati.
       "Prediction of True Critical Temperature of Multi-Component Mixtures:
       Extending Fast Estimation Methods." Fluid Phase Equilibria 392
       (April 25, 2015): 104-26. doi:10.1016/j.fluid.2015.02.001.
    '''
    if not none_and_length_check([zs, Vcs]): # check same-length inputs
        raise Exception('Function inputs are incorrect format')
    C = -2500
    Vcm = sum(zs[i]*Vcs[i] for i in range(len(zs)))
    for i in range(len(zs)):
            Vcm += C*zs[i]*log(zs[i] + sum(zs[j]*Aijs[i][j] for j in range(len(zs))))/1E6
    return Vcm

Response: r Calculates the critical volume of a mixture according to the mixing rules in [ 1 ] _.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def Vc_mixture(Vcs=None, zs=None, CASRNs=None, AvailableMethods=False, Method=None):  # pragma: no cover
    '''This function handles the retrival of a mixture's critical temperature.

    This API is considered experimental, and is expected to be removed in a
    future release in favor of a more complete object-oriented interface.

    >>> Vc_mixture([5.6E-5, 2E-4], [0.3, 0.7])
    0.0001568
    '''
    def list_methods():
        methods = []
        if none_and_length_check([Vcs]):
            methods.append('Simple')
        methods.append('None')
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    # This is the calculate, given the method section
    if Method == 'Simple':
        return mixing_simple(zs, Vcs)
    elif Method == 'None':
        return None
    else:
        raise Exception('Failure in in function')

Response: This function handles the retrival of a mixture s critical temperature.


Instruction:
Create a Python 3 function to
look up the CAS number of a chemical by searching and testing for the string being any of the following types of chemical identifiers: * Name, in IUPAC form or common form or a synonym registered in PubChem * InChI name, prefixed by 'InChI=1S/' or 'InChI=1/' * InChI key, prefixed by 'InChIKey=' * PubChem CID, prefixed by 'PubChem=' * SMILES (prefix with 'SMILES=' to ensure smiles parsing; ex. 'C' will return Carbon as it is an element whereas the SMILES interpretation for 'C' is methane) * CAS number (obsolete numbers may point to the current number) If the input is an ID representing an element, the following additional inputs may be specified as * Atomic symbol (ex 'Na') * Atomic number (as a string) Parameters ---------- ID : str One of the name formats described above Returns ------- CASRN : string A three-piece, dash-separated set of numbers Notes ----- An exception is raised if the name cannot be identified. The PubChem database includes a wide variety of other synonyms, but these may not be present for all chemcials. Examples -------- >>> CAS_from_any('water') '7732-18-5' >>> CAS_from_any('InChI=1S/C2H6O/c1-2-3/h3H,2H2,1H3') '64-17-5' >>> CAS_from_any('CCCCCCCCCC') '124-18-5' >>> CAS_from_any('InChIKey=LFQSCWFLJHTTHZ-UHFFFAOYSA-N') '64-17-5' >>> CAS_from_any('pubchem=702') '64-17-5' >>> CAS_from_any('O') # only elements can be specified by symbol '17778-80-2'

Response:
def CAS_from_any(ID, autoload=False):
    '''Looks up the CAS number of a chemical by searching and testing for the
    string being any of the following types of chemical identifiers:

    * Name, in IUPAC form or common form or a synonym registered in PubChem
    * InChI name, prefixed by 'InChI=1S/' or 'InChI=1/'
    * InChI key, prefixed by 'InChIKey='
    * PubChem CID, prefixed by 'PubChem='
    * SMILES (prefix with 'SMILES=' to ensure smiles parsing; ex.
      'C' will return Carbon as it is an element whereas the SMILES
      interpretation for 'C' is methane)
    * CAS number (obsolete numbers may point to the current number)

    If the input is an ID representing an element, the following additional
    inputs may be specified as

    * Atomic symbol (ex 'Na')
    * Atomic number (as a string)

    Parameters
    ----------
    ID : str
        One of the name formats described above

    Returns
    -------
    CASRN : string
        A three-piece, dash-separated set of numbers

    Notes
    -----
    An exception is raised if the name cannot be identified. The PubChem
    database includes a wide variety of other synonyms, but these may not be
    present for all chemcials.

    Examples
    --------
    >>> CAS_from_any('water')
    '7732-18-5'
    >>> CAS_from_any('InChI=1S/C2H6O/c1-2-3/h3H,2H2,1H3')
    '64-17-5'
    >>> CAS_from_any('CCCCCCCCCC')
    '124-18-5'
    >>> CAS_from_any('InChIKey=LFQSCWFLJHTTHZ-UHFFFAOYSA-N')
    '64-17-5'
    >>> CAS_from_any('pubchem=702')
    '64-17-5'
    >>> CAS_from_any('O') # only elements can be specified by symbol
    '17778-80-2'
    '''
    ID = ID.strip()
    ID_lower = ID.lower()
    if ID in periodic_table:
        if periodic_table[ID].number not in homonuclear_elemental_gases:
            return periodic_table[ID].CAS
        else:
            for i in [periodic_table.symbol_to_elements,
                      periodic_table.number_to_elements,
                      periodic_table.CAS_to_elements]:
                if i == periodic_table.number_to_elements:
                    if int(ID in i):
                        return periodic_table[int(ID)].CAS

                else:
                    if ID in i:
                        return periodic_table[ID].CAS

    if checkCAS(ID):
        CAS_lookup = pubchem_db.search_CAS(ID, autoload)
        if CAS_lookup:
            return CAS_lookup.CASs

        # handle the case of synonyms
        CAS_alternate_loopup = pubchem_db.search_name(ID, autoload)
        if CAS_alternate_loopup:
            return CAS_alternate_loopup.CASs
        if not autoload:
            return CAS_from_any(ID, autoload=True)
        raise Exception('A valid CAS number was recognized, but is not in the database')

    ID_len = len(ID)
    if ID_len > 9:
        inchi_search = False
        # normal upper case is 'InChI=1S/'
        if ID_lower[0:9] == 'inchi=1s/':
            inchi_search = ID[9:]
        elif ID_lower[0:8] == 'inchi=1/':
            inchi_search = ID[8:]
        if inchi_search:
            inchi_lookup = pubchem_db.search_InChI(inchi_search, autoload)
            if inchi_lookup:
                return inchi_lookup.CASs
            else:
                if not autoload:
                    return CAS_from_any(ID, autoload=True)
                raise Exception('A valid InChI name was recognized, but it is not in the database')
        if ID_lower[0:9] == 'inchikey=':
            inchi_key_lookup = pubchem_db.search_InChI_key(ID[9:], autoload)
            if inchi_key_lookup:
                return inchi_key_lookup.CASs
            else:
                if not autoload:
                    return CAS_from_any(ID, autoload=True)
                raise Exception('A valid InChI Key was recognized, but it is not in the database')
    if ID_len > 8:
        if ID_lower[0:8] == 'pubchem=':
            pubchem_lookup = pubchem_db.search_pubchem(ID[8:], autoload)
            if pubchem_lookup:
                return pubchem_lookup.CASs
            else:
                if not autoload:
                    return CAS_from_any(ID, autoload=True)
                raise Exception('A PubChem integer identifier was recognized, but it is not in the database.')
    if ID_len > 7:
        if ID_lower[0:7] == 'smiles=':
            smiles_lookup = pubchem_db.search_smiles(ID[7:], autoload)
            if smiles_lookup:
                return smiles_lookup.CASs
            else:
                if not autoload:
                    return CAS_from_any(ID, autoload=True)
                raise Exception('A SMILES identifier was recognized, but it is not in the database.')

    # Try the smiles lookup anyway
    # Parsing SMILES is an option, but this is faster
    # Pybel API also prints messages to console on failure
    smiles_lookup = pubchem_db.search_smiles(ID, autoload)
    if smiles_lookup:
        return smiles_lookup.CASs

    try:
        formula_query = pubchem_db.search_formula(serialize_formula(ID), autoload)
        if formula_query and type(formula_query) == ChemicalMetadata:
            return formula_query.CASs
    except:
        pass

    # Try a direct lookup with the name - the fastest
    name_lookup = pubchem_db.search_name(ID, autoload)
    if name_lookup:
        return name_lookup.CASs

#     Permutate through various name options
    ID_no_space = ID.replace(' ', '')
    ID_no_space_dash = ID_no_space.replace('-', '')

    for name in [ID, ID_no_space, ID_no_space_dash]:
        for name2 in [name, name.lower()]:
            name_lookup = pubchem_db.search_name(name2, autoload)
            if name_lookup:
                return name_lookup.CASs

    if ID[-1] == ')' and '(' in ID:#
        # Try to matck in the form 'water (H2O)'
        first_identifier, second_identifier = ID[0:-1].split('(', 1)
        try:
            CAS1 = CAS_from_any(first_identifier)
            CAS2 = CAS_from_any(second_identifier)
            assert CAS1 == CAS2
            return CAS1
        except:
            pass

    if not autoload:
        return CAS_from_any(ID, autoload=True)

    raise Exception('Chemical name not recognized')


Instruction:
Can you generate the documentation for the following Python 3 function
def mixture_from_any(ID):
    '''Looks up a string which may represent a mixture in the database of
    thermo to determine the key by which the composition of that mixture can
    be obtained in the dictionary `_MixtureDict`.

    Parameters
    ----------
    ID : str
        A string or 1-element list containing the name which may represent a
        mixture.

    Returns
    -------
    key : str
        Key for access to the data on the mixture in `_MixtureDict`.

    Notes
    -----
    White space, '-', and upper case letters are removed in the search.

    Examples
    --------
    >>> mixture_from_any('R512A')
    'R512A'
    >>> mixture_from_any([u'air'])
    'Air'
    '''
    if type(ID) == list:
        if len(ID) == 1:
            ID = ID[0]
        else:
            raise Exception('If the input is a list, the list must contain only one item.')
    ID = ID.lower().strip()
    ID2 = ID.replace(' ', '')
    ID3 = ID.replace('-', '')
    for i in [ID, ID2, ID3]:
        if i in _MixtureDictLookup:
            return _MixtureDictLookup[i]
    raise Exception('Mixture name not recognized')

Response:
Returns the key for which the composition of that mixture can be obtained in the dictionary of
   .


Instruction:
Create a Python 3 function to
return the charge of the species as an integer.

Response:
def charge(self):
        '''Charge of the species as an integer. Computed as a property as most
        species do not have a charge and so storing it would be a waste of
        memory.
        '''
        try:
            return self._charge
        except AttributeError:
            self._charge = charge_from_formula(self.formula)
            return self._charge


Instruction:
Given the following Python 3 function, write the documentation
def load_included_indentifiers(self, file_name):
        '''Loads a file with newline-separated integers representing which
        chemical should be kept in memory; ones not included are ignored.
        '''
        self.restrict_identifiers = True
        included_identifiers = set()
        with open(file_name) as f:
            [included_identifiers.add(int(line)) for line in f]
        self.included_identifiers = included_identifiers

Response:
Loads a file with newline - separated integers representing which
        chemical should be kept in memory ; ones not included are ignored.


Instruction:
Here you have a function in Python 3, explain what it does
def EQ100(T, A=0, B=0, C=0, D=0, E=0, F=0, G=0, order=0):
    r'''DIPPR Equation # 100. Used in calculating the molar heat capacities
    of liquids and solids, liquid thermal conductivity, and solid density.
    All parameters default to zero. As this is a straightforward polynomial,
    no restrictions on parameters apply. Note that high-order polynomials like
    this may need large numbers of decimal places to avoid unnecessary error.

    .. math::
        Y = A + BT + CT^2 + DT^3 + ET^4 + FT^5 + GT^6

    Parameters
    ----------
    T : float
        Temperature, [K]
    A-G : float
        Parameter for the equation; chemical and property specific [-]
    order : int, optional
        Order of the calculation. 0 for the calculation of the result itself;
        for 1, the first derivative of the property is returned, for
        -1, the indefinite integral of the property with respect to temperature
        is returned; and for -1j, the indefinite integral of the property
        divided by temperature with respect to temperature is returned. No
        other integrals or derivatives are implemented, and an exception will
        be raised if any other order is given.

    Returns
    -------
    Y : float
        Property [constant-specific; if order == 1, property/K; if order == -1,
                  property*K; if order == -1j, unchanged from default]

    Notes
    -----
    The derivative with respect to T, integral with respect to T, and integral
    over T with respect to T are computed as follows. All derivatives and
    integrals are easily computed with SymPy.

    .. math::
        \frac{d Y}{dT} = B + 2 C T + 3 D T^{2} + 4 E T^{3} + 5 F T^{4}
        + 6 G T^{5}

    .. math::
        \int Y dT = A T + \frac{B T^{2}}{2} + \frac{C T^{3}}{3} + \frac{D
        T^{4}}{4} + \frac{E T^{5}}{5} + \frac{F T^{6}}{6} + \frac{G T^{7}}{7}

    .. math::
        \int \frac{Y}{T} dT = A \log{\left (T \right )} + B T + \frac{C T^{2}}
        {2} + \frac{D T^{3}}{3} + \frac{E T^{4}}{4} + \frac{F T^{5}}{5}
        + \frac{G T^{6}}{6}

    Examples
    --------
    Water liquid heat capacity; DIPPR coefficients normally listed in J/kmol/K.

    >>> EQ100(300, 276370., -2090.1, 8.125, -0.014116, 0.0000093701)
    75355.81000000003

    References
    ----------
    .. [1] Design Institute for Physical Properties, 1996. DIPPR Project 801
       DIPPR/AIChE
    '''
    if order == 0:
        return A + T*(B + T*(C + T*(D + T*(E + T*(F + G*T)))))
    elif order == 1:
        return B + T*(2*C + T*(3*D + T*(4*E + T*(5*F + 6*G*T))))
    elif order == -1:
        return T*(A + T*(B/2 + T*(C/3 + T*(D/4 + T*(E/5 + T*(F/6 + G*T/7))))))
    elif order == -1j:
        return A*log(T) + T*(B + T*(C/2 + T*(D/3 + T*(E/4 + T*(F/5 + G*T/6)))))
    else:
        raise Exception(order_not_found_msg)

Response: r'''DIPPR Equation # 100. Used in calculating the molar heat capacities of liquids and solids and liquid thermal conductivity.


Instruction:
Given the following Python 3 function, write the documentation
def EQ104(T, A, B, C, D, E, order=0):
    r'''DIPPR Equation #104. Often used in calculating second virial
    coefficients of gases. All 5 parameters are required.
    C, D, and E are normally large values.

    .. math::
        Y = A + \frac{B}{T} + \frac{C}{T^3} + \frac{D}{T^8} + \frac{E}{T^9}

    Parameters
    ----------
    T : float
        Temperature, [K]
    A-E : float
        Parameter for the equation; chemical and property specific [-]
    order : int, optional
        Order of the calculation. 0 for the calculation of the result itself;
        for 1, the first derivative of the property is returned, for
        -1, the indefinite integral of the property with respect to temperature
        is returned; and for -1j, the indefinite integral of the property
        divided by temperature with respect to temperature is returned. No
        other integrals or derivatives are implemented, and an exception will
        be raised if any other order is given.

    Returns
    -------
    Y : float
        Property [constant-specific; if order == 1, property/K; if order == -1,
                  property*K; if order == -1j, unchanged from default]

    Notes
    -----
    The derivative with respect to T, integral with respect to T, and integral
    over T with respect to T are computed as follows. All expressions can be
    obtained with SymPy readily.

    .. math::
        \frac{d Y}{dT} = - \frac{B}{T^{2}} - \frac{3 C}{T^{4}}
        - \frac{8 D}{T^{9}} - \frac{9 E}{T^{10}}

    .. math::
        \int Y dT = A T + B \log{\left (T \right )} - \frac{1}{56 T^{8}}
        \left(28 C T^{6} + 8 D T + 7 E\right)

    .. math::
        \int \frac{Y}{T} dT = A \log{\left (T \right )} - \frac{1}{72 T^{9}}
        \left(72 B T^{8} + 24 C T^{6} + 9 D T + 8 E\right)

    Examples
    --------
    Water second virial coefficient; DIPPR coefficients normally dimensionless.

    >>> EQ104(300, 0.02222, -26.38, -16750000, -3.894E19, 3.133E21)
    -1.1204179007265156

    References
    ----------
    .. [1] Design Institute for Physical Properties, 1996. DIPPR Project 801
       DIPPR/AIChE
    '''
    if order == 0:
        T2 = T*T
        return A + (B + (C + (D + E/T)/(T2*T2*T))/T2)/T
    elif order == 1:
        T2 = T*T
        T4 = T2*T2
        return (-B + (-3*C + (-8*D - 9*E/T)/(T4*T))/T2)/T2
    elif order == -1:
        return A*T + B*log(T) - (28*C*T**6 + 8*D*T + 7*E)/(56*T**8)
    elif order == -1j:
        return A*log(T) - (72*B*T**8 + 24*C*T**6 + 9*D*T + 8*E)/(72*T**9)
    else:
        raise Exception(order_not_found_msg)

Response: r Returns the second virial base class for the given temperature and property.


Instruction:
Make a summary of the following Python 3 code
def EQ106(T, Tc, A, B, C=0, D=0, E=0):
    r'''DIPPR Equation #106. Often used in calculating liquid surface tension,
    and heat of vaporization.
    Only parameters A and B parameters are required; many fits include no
    further parameters. Critical temperature is also required.

    .. math::
        Y = A(1-T_r)^{B + C T_r + D T_r^2 + E T_r^3}

        Tr = \frac{T}{Tc}

    Parameters
    ----------
    T : float
        Temperature, [K]
    Tc : float
        Critical temperature, [K]
    A-D : float
        Parameter for the equation; chemical and property specific [-]

    Returns
    -------
    Y : float
        Property [constant-specific]

    Notes
    -----
    The integral could not be found, but the integral over T actually could,
    again in terms of hypergeometric functions.

    Examples
    --------
    Water surface tension; DIPPR coefficients normally in Pa*s.

    >>> EQ106(300, 647.096, 0.17766, 2.567, -3.3377, 1.9699)
    0.07231499373541

    References
    ----------
    .. [1] Design Institute for Physical Properties, 1996. DIPPR Project 801
       DIPPR/AIChE
    '''
    Tr = T/Tc
    return A*(1. - Tr)**(B + Tr*(C + Tr*(D + E*Tr)))

Response: r Equation #106. Often used in calculating liquid surface tension and heat of vaporization.


Instruction:
Given the following Python 3 function, write the documentation
def EQ107(T, A=0, B=0, C=0, D=0, E=0, order=0):
    r'''DIPPR Equation #107. Often used in calculating ideal-gas heat capacity.
    All 5 parameters are required.
    Also called the Aly-Lee equation.

    .. math::
        Y = A + B\left[\frac{C/T}{\sinh(C/T)}\right]^2 + D\left[\frac{E/T}{
        \cosh(E/T)}\right]^2

    Parameters
    ----------
    T : float
        Temperature, [K]
    A-E : float
        Parameter for the equation; chemical and property specific [-]
    order : int, optional
        Order of the calculation. 0 for the calculation of the result itself;
        for 1, the first derivative of the property is returned, for
        -1, the indefinite integral of the property with respect to temperature
        is returned; and for -1j, the indefinite integral of the property
        divided by temperature with respect to temperature is returned. No
        other integrals or derivatives are implemented, and an exception will
        be raised if any other order is given.

    Returns
    -------
    Y : float
        Property [constant-specific; if order == 1, property/K; if order == -1,
                  property*K; if order == -1j, unchanged from default]

    Notes
    -----
    The derivative with respect to T, integral with respect to T, and integral
    over T with respect to T are computed as follows. The derivative is
    obtained via SymPy; the integrals from Wolfram Alpha.

    .. math::
        \frac{d Y}{dT} = \frac{2 B C^{3} \cosh{\left (\frac{C}{T} \right )}}
        {T^{4} \sinh^{3}{\left (\frac{C}{T} \right )}} - \frac{2 B C^{2}}{T^{3}
        \sinh^{2}{\left (\frac{C}{T} \right )}} + \frac{2 D E^{3} \sinh{\left
        (\frac{E}{T} \right )}}{T^{4} \cosh^{3}{\left (\frac{E}{T} \right )}}
        - \frac{2 D E^{2}}{T^{3} \cosh^{2}{\left (\frac{E}{T} \right )}}

    .. math::
        \int Y dT = A T + \frac{B C}{\tanh{\left (\frac{C}{T} \right )}}
        - D E \tanh{\left (\frac{E}{T} \right )}

    .. math::
        \int \frac{Y}{T} dT = A \log{\left (T \right )} + \frac{B C}{T \tanh{
        \left (\frac{C}{T} \right )}} - B \log{\left (\sinh{\left (\frac{C}{T}
        \right )} \right )} - \frac{D E}{T} \tanh{\left (\frac{E}{T} \right )}
        + D \log{\left (\cosh{\left (\frac{E}{T} \right )} \right )}

    Examples
    --------
    Water ideal gas molar heat capacity; DIPPR coefficients normally in
    J/kmol/K

    >>> EQ107(300., 33363., 26790., 2610.5, 8896., 1169.)
    33585.90452768923

    References
    ----------
    .. [1] Design Institute for Physical Properties, 1996. DIPPR Project 801
       DIPPR/AIChE
    .. [2] Aly, Fouad A., and Lloyd L. Lee. "Self-Consistent Equations for
       Calculating the Ideal Gas Heat Capacity, Enthalpy, and Entropy." Fluid
       Phase Equilibria 6, no. 3 (January 1, 1981): 169-79.
       doi:10.1016/0378-3812(81)85002-9.
    '''
    if order == 0:
        return A + B*((C/T)/sinh(C/T))**2 + D*((E/T)/cosh(E/T))**2
    elif order == 1:
        return (2*B*C**3*cosh(C/T)/(T**4*sinh(C/T)**3)
                - 2*B*C**2/(T**3*sinh(C/T)**2)
                + 2*D*E**3*sinh(E/T)/(T**4*cosh(E/T)**3)
                - 2*D*E**2/(T**3*cosh(E/T)**2))
    elif order == -1:
        return A*T + B*C/tanh(C/T) - D*E*tanh(E/T)
    elif order == -1j:
        return (A*log(T) + B*C/tanh(C/T)/T - B*log(sinh(C/T))
                - D*E*tanh(E/T)/T + D*log(cosh(E/T)))
    else:
        raise Exception(order_not_found_msg)

Response: r''' DIPPR Equation #107. Often used in calculating ideal - gas heat capacity.


Instruction:
Explain what the following Python 3 code does
def EQ115(T, A, B, C=0, D=0, E=0):
    r'''DIPPR Equation #115. No major uses; has been used as an alternate
    liquid viscosity expression, and as a model for vapor pressure.
    Only parameters A and B are required.

    .. math::
        Y = \exp\left(A + \frac{B}{T} + C\log T + D T^2 + \frac{E}{T^2}\right)

    Parameters
    ----------
    T : float
        Temperature, [K]
    A-E : float
        Parameter for the equation; chemical and property specific [-]

    Returns
    -------
    Y : float
        Property [constant-specific]

    Notes
    -----
    No coefficients found for this expression.
    This function is not integrable for either dT or Y/T dT.

    References
    ----------
    .. [1] Design Institute for Physical Properties, 1996. DIPPR Project 801
       DIPPR/AIChE
    '''
    return exp(A+B/T+C*log(T)+D*T**2 + E/T**2)

Response: r A basic equation for the current language of the language of the liquid viscosity expression.


Instruction:
How would you explain what the following Python 3 function does
def CoolProp_T_dependent_property(T, CASRN, prop, phase):
    r'''Calculates a property of a chemical in either the liquid or gas phase
    as a function of temperature only. This means that the property is
    either at 1 atm or along the saturation curve.

    Parameters
    ----------
    T : float
        Temperature of the fluid [K]
    CASRN : str
        CAS number of the fluid
    prop : str
        CoolProp string shortcut for desired property
    phase : str
        Either 'l' or 'g' for liquid or gas properties respectively

    Returns
    -------
    prop : float
        Desired chemical property, [units]

    Notes
    -----
    For liquids above their boiling point, the liquid property is found on the
    saturation line (at higher pressures). Under their boiling point, the
    property is calculated at 1 atm.

    No liquid calculations are permitted above the critical temperature.

    For gases under the chemical's boiling point, the gas property is found
    on the saturation line (at sub-atmospheric pressures). Above the boiling
    point, the property is calculated at 1 atm.

    An exception is raised if the desired CAS is not supported, or if CoolProp
    is not available.

    The list of strings acceptable as an input for property types is:
    http://www.coolprop.org/coolprop/HighLevelAPI.html#table-of-string-inputs-to-propssi-function

    Examples
    --------
    Water at STP according to IAPWS-95

    >>> CoolProp_T_dependent_property(298.15, '7732-18-5', 'D', 'l')
    997.047636760347

    References
    ----------
    .. [1] Bell, Ian H., Jorrit Wronski, Sylvain Quoilin, and Vincent Lemort.
       "Pure and Pseudo-Pure Fluid Thermophysical Property Evaluation and the
       Open-Source Thermophysical Property Library CoolProp." Industrial &
       Engineering Chemistry Research 53, no. 6 (February 12, 2014):
       2498-2508. doi:10.1021/ie4033999. http://www.coolprop.org/
    '''
    if not has_CoolProp:  # pragma: no cover
        raise Exception('CoolProp library is not installed')
    if CASRN not in coolprop_dict:
        raise Exception('CASRN not in list of supported fluids')
    Tc = coolprop_fluids[CASRN].Tc
    T = float(T) # Do not allow custom objects here
    if phase == 'l':
        if T > Tc:
            raise Exception('For liquid properties, must be under the critical temperature.')
        if PhaseSI('T', T, 'P', 101325, CASRN) in [u'liquid', u'supercritical_liquid']:
            return PropsSI(prop, 'T', T, 'P', 101325, CASRN)
        else:
            return PropsSI(prop, 'T', T, 'Q', 0, CASRN)
    elif phase == 'g':
        if PhaseSI('T', T, 'P', 101325, CASRN) == 'gas':
            return PropsSI(prop, 'T', T, 'P', 101325, CASRN)
        else:
            if T < Tc:
                return PropsSI(prop, 'T', T, 'Q', 1, CASRN)
            else:
                # catch supercritical_gas and friends
                return PropsSI(prop, 'T', T, 'P', 101325, CASRN)
    else:
        raise Exception('Error in CoolProp property function')

Response: r Calculates a property of a fluid in either the liquid or gas phase of a fluid in the system or the system s system s system.


Instruction:
How would you explain what the following Python 3 function does
def Stockmayer(Tm=None, Tb=None, Tc=None, Zc=None, omega=None,
               CASRN='', AvailableMethods=False, Method=None):
    r'''This function handles the retrieval or calculation a chemical's
    Stockmayer parameter. Values are available from one source with lookup
    based on CASRNs, or can be estimated from 7 CSP methods.
    Will automatically select a data source to use if no Method is provided;
    returns None if the data is not available.

    Prefered sources are 'Magalhães, Lito, Da Silva, and Silva (2013)' for
    common chemicals which had valies listed in that source, and the CSP method
    `Tee, Gotoh, and Stewart CSP with Tc, omega (1966)` for chemicals which
    don't.

    Examples
    --------
    >>> Stockmayer(CASRN='64-17-5')
    1291.41

    Parameters
    ----------
    Tm : float, optional
        Melting temperature of fluid [K]
    Tb : float, optional
        Boiling temperature of fluid [K]
    Tc : float, optional
        Critical temperature, [K]
    Zc : float, optional
        Critical compressibility, [-]
    omega : float, optional
        Acentric factor of compound, [-]
    CASRN : string, optional
        CASRN [-]

    Returns
    -------
    epsilon_k : float
        Lennard-Jones depth of potential-energy minimum over k, [K]
    methods : list, only returned if AvailableMethods == True
        List of methods which can be used to obtain epsilon with the given
        inputs

    Other Parameters
    ----------------
    Method : string, optional
        A string for the method name to use, as defined by constants in
        Stockmayer_methods
    AvailableMethods : bool, optional
        If True, function will determine which methods can be used to obtain
        epsilon for the desired chemical, and will return methods instead of
        epsilon

    Notes
    -----
    These values are somewhat rough, as they attempt to pigeonhole a chemical
    into L-J behavior.

    The tabulated data is from [2]_, for 322 chemicals.

    References
    ----------
    .. [1] Bird, R. Byron, Warren E. Stewart, and Edwin N. Lightfoot.
       Transport Phenomena, Revised 2nd Edition. New York:
       John Wiley & Sons, Inc., 2006
    .. [2] Magalhães, Ana L., Patrícia F. Lito, Francisco A. Da Silva, and
       Carlos M. Silva. "Simple and Accurate Correlations for Diffusion
       Coefficients of Solutes in Liquids and Supercritical Fluids over Wide
       Ranges of Temperature and Density." The Journal of Supercritical Fluids
       76 (April 2013): 94-114. doi:10.1016/j.supflu.2013.02.002.
    '''
    def list_methods():
        methods = []
        if CASRN in MagalhaesLJ_data.index:
            methods.append(MAGALHAES)
        if Tc and omega:
            methods.append(TEEGOTOSTEWARD2)
        if Tc:
            methods.append(FLYNN)
            methods.append(BSLC)
            methods.append(TEEGOTOSTEWARD1)
        if Tb:
            methods.append(BSLB)
        if Tm:
            methods.append(BSLM)
        if Tc and Zc:
            methods.append(STIELTHODOS)
        methods.append(NONE)
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]

    if Method == FLYNN:
        epsilon = epsilon_Flynn(Tc)
    elif Method == BSLC:
        epsilon = epsilon_Bird_Stewart_Lightfoot_critical(Tc)
    elif Method == BSLB:
        epsilon = epsilon_Bird_Stewart_Lightfoot_boiling(Tb)
    elif Method == BSLM:
        epsilon = epsilon_Bird_Stewart_Lightfoot_melting(Tm)
    elif Method == STIELTHODOS:
        epsilon = epsilon_Stiel_Thodos(Tc, Zc)
    elif Method == TEEGOTOSTEWARD1:
        epsilon = epsilon_Tee_Gotoh_Steward_1(Tc)
    elif Method == TEEGOTOSTEWARD2:
        epsilon = epsilon_Tee_Gotoh_Steward_2(Tc, omega)

    elif Method == MAGALHAES:
        epsilon = float(MagalhaesLJ_data.at[CASRN, "epsilon"])
    elif Method == NONE:
        epsilon = None
    else:
        raise Exception('Failure in in function')
    return epsilon

Response: r Returns Stockmayer object for the given parameters.


Instruction:
How would you explain what the following Python 3 function does
def molecular_diameter(Tc=None, Pc=None, Vc=None, Zc=None, omega=None,
          Vm=None, Vb=None, CASRN='', AvailableMethods=False, Method=None):
    r'''This function handles the retrieval or calculation a chemical's
    L-J molecular diameter. Values are available from one source with lookup
    based on CASRNs, or can be estimated from 9 CSP methods.
    Will automatically select a data source to use if no Method is provided;
    returns None if the data is not available.

    Prefered sources are 'Magalhães, Lito, Da Silva, and Silva (2013)' for
    common chemicals which had valies listed in that source, and the CSP method
    `Tee, Gotoh, and Stewart CSP with Tc, Pc, omega (1966)` for chemicals which
    don't.

    Examples
    --------
    >>> molecular_diameter(CASRN='64-17-5')
    4.23738

    Parameters
    ----------
    Tc : float, optional
        Critical temperature, [K]
    Pc : float, optional
        Critical pressure, [Pa]
    Vc : float, optional
        Critical volume, [m^3/mol]
    Zc : float, optional
        Critical compressibility, [-]
    omega : float, optional
        Acentric factor of compound, [-]
    Vm : float, optional
        Molar volume of liquid at the melting point of the fluid [K]
    Vb : float, optional
        Molar volume of liquid at the boiling point of the fluid [K]
    CASRN : string, optional
        CASRN [-]

    Returns
    -------
    sigma : float
        Lennard-Jones molecular diameter, [Angstrom]
    methods : list, only returned if AvailableMethods == True
        List of methods which can be used to obtain epsilon with the given
        inputs

    Other Parameters
    ----------------
    Method : string, optional
        A string for the method name to use, as defined by constants in
        molecular_diameter_methods
    AvailableMethods : bool, optional
        If True, function will determine which methods can be used to obtain
        sigma for the desired chemical, and will return methods instead of
        sigma

    Notes
    -----
    These values are somewhat rough, as they attempt to pigeonhole a chemical
    into L-J behavior.

    The tabulated data is from [2]_, for 322 chemicals.

    References
    ----------
    .. [1] Bird, R. Byron, Warren E. Stewart, and Edwin N. Lightfoot.
       Transport Phenomena, Revised 2nd Edition. New York:
       John Wiley & Sons, Inc., 2006
    .. [2] Magalhães, Ana L., Patrícia F. Lito, Francisco A. Da Silva, and
       Carlos M. Silva. "Simple and Accurate Correlations for Diffusion
       Coefficients of Solutes in Liquids and Supercritical Fluids over Wide
       Ranges of Temperature and Density." The Journal of Supercritical Fluids
       76 (April 2013): 94-114. doi:10.1016/j.supflu.2013.02.002.
    '''
    def list_methods():
        methods = []
        if CASRN in MagalhaesLJ_data.index:
            methods.append(MAGALHAES)
        if Tc and Pc and omega:
            methods.append(TEEGOTOSTEWARD4)
        if Tc and Pc:
            methods.append(SILVALIUMACEDO)
            methods.append(BSLC2)
            methods.append(TEEGOTOSTEWARD3)
        if Vc and Zc:
            methods.append(STIELTHODOSMD)
        if Vc:
            methods.append(FLYNN)
            methods.append(BSLC1)
        if Vb:
            methods.append(BSLB)
        if Vm:
            methods.append(BSLM)
        methods.append(NONE)
        return methods

    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    if Method == FLYNN:
        sigma = sigma_Flynn(Vc)
    elif Method == BSLC1:
        sigma = sigma_Bird_Stewart_Lightfoot_critical_1(Vc)
    elif Method == BSLC2:
        sigma = sigma_Bird_Stewart_Lightfoot_critical_2(Tc, Pc)
    elif Method == TEEGOTOSTEWARD3:
        sigma = sigma_Tee_Gotoh_Steward_1(Tc, Pc)
    elif Method == SILVALIUMACEDO:
        sigma = sigma_Silva_Liu_Macedo(Tc, Pc)
    elif Method == BSLB:
        sigma = sigma_Bird_Stewart_Lightfoot_boiling(Vb)
    elif Method == BSLM:
        sigma = sigma_Bird_Stewart_Lightfoot_melting(Vm)
    elif Method == STIELTHODOSMD:
        sigma = sigma_Stiel_Thodos(Vc, Zc)
    elif Method == TEEGOTOSTEWARD4:
        sigma = sigma_Tee_Gotoh_Steward_2(Tc, Pc, omega)
    elif Method == MAGALHAES:
        sigma = float(MagalhaesLJ_data.at[CASRN, "sigma"])
    elif Method == NONE:
        sigma = None
    else:
        raise Exception('Failure in in function')
    return sigma

Response: r Returns the molecular diameter of a given chemical s base class.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def sigma_Silva_Liu_Macedo(Tc, Pc):
    r'''Calculates Lennard-Jones molecular diameter.
    Uses critical temperature and pressure. CSP method by [1]_.

    .. math::
        \sigma_{LJ}^3 = 0.17791 + 11.779 \left( \frac{T_c}{P_c}\right)
        - 0.049029\left( \frac{T_c}{P_c}\right)^2

    Parameters
    ----------
    Tc : float
        Critical temperature of fluid [K]
    Pc : float
        Critical pressure of fluid [Pa]

    Returns
    -------
    sigma : float
        Lennard-Jones molecular diameter, [Angstrom]

    Notes
    -----
    Pc is originally in bar. An excellent paper. None is
    returned if the polynomial returns a negative number, as in the case of
    1029.13 K and 3.83 bar.

    Examples
    --------
    >>> sigma_Silva_Liu_Macedo(560.1, 4550000)
    5.164483998730177

    References
    ----------
    .. [1] Silva, Carlos M., Hongqin Liu, and Eugenia A. Macedo. "Models for
       Self-Diffusion Coefficients of Dense Fluids, Including Hydrogen-Bonding
       Substances." Chemical Engineering Science 53, no. 13 (July 1, 1998):
       2423-29. doi:10.1016/S0009-2509(98)00037-2
    '''
    Pc = Pc/1E5  # Pa to bar
    term = 0.17791 + 11.779*(Tc/Pc) - 0.049029 * (Tc/Pc)**2
    if term < 0:
        sigma = None
    else:
        sigma = (term)**(1/3.)
    return sigma

Response: r Returns the sigma of the base class of the base class of the base class.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def collision_integral_Kim_Monroe(Tstar, l=1, s=1):
    r'''Calculates Lennard-Jones collision integral for any of 16 values of
    (l,j) for the wide range of 0.3 < Tstar < 400. Values are accurate to
    0.007 % of actual values, but the calculation of actual values is
    computationally intensive and so these simplifications are used, developed
    in [1]_.

    .. math::
        \Omega^{(l,s)*} = A^{(l,s)} + \sum_{k=1}^6 \left[ \frac{B_k^{(l,s)}}
        {(T^*)^k} + C_k^{(l,s)} (\ln T^*)^k \right]

    Parameters
    ----------
    Tstar : float
        Reduced temperature of the fluid [-]
    l : int
        term
    s : int
        term

    Returns
    -------
    Omega : float
        Collision integral of A and B

    Notes
    -----
    Acceptable pairs of (l,s) are (1, 1), (1, 2), (1, 3), (1, 4), (1, 5),
    (1, 6), (1, 7), (2, 2), (2, 3), (2, 4), (2, 5), (2, 6), (3, 3), (3, 4),
    (3, 5), and (4, 4).

    .. math::
        T^* = \frac{k_b T}{\epsilon}

    Examples
    --------
    >>> collision_integral_Kim_Monroe(400, 1, 1)
    0.4141818082392228

    References
    ----------
    .. [1] Kim, Sun Ung, and Charles W. Monroe. "High-Accuracy Calculations of
       Sixteen Collision Integrals for Lennard-Jones (12-6) Gases and Their
       Interpolation to Parameterize Neon, Argon, and Krypton." Journal of
       Computational Physics 273 (September 15, 2014): 358-73.
       doi:10.1016/j.jcp.2014.05.018.
    '''
    if (l, s) not in As_collision:
        raise Exception('Input values of l and s are not supported')
    omega = As_collision[(l, s)]
    for ki in range(6):
        Bs = Bs_collision[(l, s)]
        Cs = Cs_collision[(l, s)]
        omega += Bs[ki]/Tstar**(ki+1) + Cs[ki]*log(Tstar)**(ki+1)
    return omega

Response: r Returns a new base class that calculates the collision integral for any of the given values of l and s.


Instruction:
Given the following Python 3 function, write the documentation
def omega(CASRN, AvailableMethods=False, Method=None, IgnoreMethods=['LK', 'DEFINITION']):
    r'''This function handles the retrieval of a chemical's acentric factor,
    `omega`, or its calculation from correlations or directly through the
    definition of acentric factor if possible. Requires a known boiling point,
    critical temperature and pressure for use of the correlations. Requires
    accurate vapor pressure data for direct calculation.

    Will automatically select a method to use if no Method is provided;
    returns None if the data is not available and cannot be calculated.

    .. math::
        \omega \equiv -\log_{10}\left[\lim_{T/T_c=0.7}(P^{sat}/P_c)\right]-1.0

    Examples
    --------
    >>> omega(CASRN='64-17-5')
    0.635

    Parameters
    ----------
    CASRN : string
        CASRN [-]

    Returns
    -------
    omega : float
        Acentric factor of compound
    methods : list, only returned if AvailableMethods == True
        List of methods which can be used to obtain omega with the given inputs

    Other Parameters
    ----------------
    Method : string, optional
        The method name to use. Accepted methods are 'PSRK', 'PD', 'YAWS',
        'LK', and 'DEFINITION'. All valid values are also held in the list
        omega_methods.
    AvailableMethods : bool, optional
        If True, function will determine which methods can be used to obtain
        omega for the desired chemical, and will return methods instead of
        omega
    IgnoreMethods : list, optional
        A list of methods to ignore in obtaining the full list of methods,
        useful for for performance reasons and ignoring inaccurate methods

    Notes
    -----
    A total of five sources are available for this function. They are:

        * 'PSRK', a compillation of experimental and estimated data published
          in the Appendix of [15]_, the fourth revision of the PSRK model.
        * 'PD', an older compillation of
          data published in (Passut & Danner, 1973) [16]_.
        * 'YAWS', a large compillation of data from a
          variety of sources; no data points are sourced in the work of [17]_.
        * 'LK', a estimation method for hydrocarbons.
        * 'DEFINITION', based on the definition of omega as
          presented in [1]_, using vapor pressure data.

    References
    ----------
    .. [1] Pitzer, K. S., D. Z. Lippmann, R. F. Curl, C. M. Huggins, and
       D. E. Petersen: The Volumetric and Thermodynamic Properties of Fluids.
       II. Compressibility Factor, Vapor Pressure and Entropy of Vaporization.
       J. Am. Chem. Soc., 77: 3433 (1955).
    .. [2] Horstmann, Sven, Anna Jabłoniec, Jörg Krafczyk, Kai Fischer, and
       Jürgen Gmehling. "PSRK Group Contribution Equation of State:
       Comprehensive Revision and Extension IV, Including Critical Constants
       and Α-Function Parameters for 1000 Components." Fluid Phase Equilibria
       227, no. 2 (January 25, 2005): 157-64. doi:10.1016/j.fluid.2004.11.002.
    .. [3] Passut, Charles A., and Ronald P. Danner. "Acentric Factor. A
       Valuable Correlating Parameter for the Properties of Hydrocarbons."
       Industrial & Engineering Chemistry Process Design and Development 12,
       no. 3 (July 1, 1973): 365-68. doi:10.1021/i260047a026.
    .. [4] Yaws, Carl L. Thermophysical Properties of Chemicals and
       Hydrocarbons, Second Edition. Amsterdam Boston: Gulf Professional
       Publishing, 2014.
    '''
    def list_methods():
        methods = []
        if CASRN in _crit_PSRKR4.index and not np.isnan(_crit_PSRKR4.at[CASRN, 'omega']):
            methods.append('PSRK')
        if CASRN in _crit_PassutDanner.index and not np.isnan(_crit_PassutDanner.at[CASRN, 'omega']):
            methods.append('PD')
        if CASRN in _crit_Yaws.index and not np.isnan(_crit_Yaws.at[CASRN, 'omega']):
            methods.append('YAWS')
        Tcrit, Pcrit = Tc(CASRN), Pc(CASRN)
        if Tcrit and Pcrit:
            if Tb(CASRN):
                methods.append('LK')
            if VaporPressure(CASRN=CASRN).T_dependent_property(Tcrit*0.7):
                methods.append('DEFINITION')  # TODO: better integration
        if IgnoreMethods:
            for Method in IgnoreMethods:
                if Method in methods:
                    methods.remove(Method)
        methods.append('NONE')
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    # This is the calculate, given the method section
    if Method == 'PSRK':
        _omega = float(_crit_PSRKR4.at[CASRN, 'omega'])
    elif Method == 'PD':
        _omega = float(_crit_PassutDanner.at[CASRN, 'omega'])
    elif Method == 'YAWS':
        _omega = float(_crit_Yaws.at[CASRN, 'omega'])
    elif Method == 'LK':
        _omega = LK_omega(Tb(CASRN), Tc(CASRN), Pc(CASRN))
    elif Method == 'DEFINITION':
        P = VaporPressure(CASRN=CASRN).T_dependent_property(Tc(CASRN)*0.7)
        _omega = -log10(P/Pc(CASRN)) - 1.0
    elif Method == 'NONE':
        _omega = None
    else:
        raise Exception('Failure in in function')
    return _omega

Response: r Returns a new structure of the acentric factor of a given CASRN.


Instruction:
Implement a function in Python 3 to
estimate the acentric factor of a base class based on a correlation based on Three - Parameter Corresponding States.

Response:
def LK_omega(Tb, Tc, Pc):
    r'''Estimates the acentric factor of a fluid using a correlation in [1]_.

    .. math::
        \omega = \frac{\ln P_{br}^{sat} - 5.92714 + 6.09648/T_{br} + 1.28862
        \ln T_{br} -0.169347T_{br}^6}
        {15.2518 - 15.6875/T_{br} - 13.4721 \ln T_{br} + 0.43577 T_{br}^6}

    Parameters
    ----------
    Tb : float
        Boiling temperature of the fluid [K]
    Tc : float
        Critical temperature of the fluid [K]
    Pc : float
        Critical pressure of the fluid [Pa]

    Returns
    -------
    omega : float
        Acentric factor of the fluid [-]

    Notes
    -----
    Internal units are atmosphere and Kelvin.
    Example value from Reid (1987). Using ASPEN V8.4, LK method gives 0.325595.

    Examples
    --------
    Isopropylbenzene

    >>> LK_omega(425.6, 631.1, 32.1E5)
    0.32544249926397856

    References
    ----------
    .. [1] Lee, Byung Ik, and Michael G. Kesler. "A Generalized Thermodynamic
       Correlation Based on Three-Parameter Corresponding States." AIChE Journal
       21, no. 3 (1975): 510-527. doi:10.1002/aic.690210313.
    '''
    T_br = Tb/Tc
    omega = (log(101325.0/Pc) - 5.92714 + 6.09648/T_br + 1.28862*log(T_br) -
             0.169347*T_br**6)/(15.2518 - 15.6875/T_br - 13.4721*log(T_br) +
             0.43577*T_br**6)
    return omega


Instruction:
Can you tell what is the following Python 3 function doing
def omega_mixture(omegas, zs, CASRNs=None, Method=None,
                  AvailableMethods=False):
    r'''This function handles the calculation of a mixture's acentric factor.
    Calculation is based on the omegas provided for each pure component. Will
    automatically select a method to use if no Method is provided;
    returns None if insufficient data is available.

    Examples
    --------
    >>> omega_mixture([0.025, 0.12], [0.3, 0.7])
    0.0915

    Parameters
    ----------
    omegas : array-like
        acentric factors of each component, [-]
    zs : array-like
        mole fractions of each component, [-]
    CASRNs: list of strings
        CASRNs, not currently used [-]

    Returns
    -------
    omega : float
        acentric factor of the mixture, [-]
    methods : list, only returned if AvailableMethods == True
        List of methods which can be used to obtain omega with the given inputs

    Other Parameters
    ----------------
    Method : string, optional
        The method name to use. Only 'SIMPLE' is accepted so far.
        All valid values are also held in the list omega_mixture_methods.
    AvailableMethods : bool, optional
        If True, function will determine which methods can be used to obtain
        omega for the desired chemical, and will return methods instead of
        omega

    Notes
    -----
    The only data used in the methods implemented to date are mole fractions
    and pure-component omegas. An alternate definition could be based on
    the dew point or bubble point of a multicomponent mixture, but this has
    not been done to date.

    References
    ----------
    .. [1] Poling, Bruce E. The Properties of Gases and Liquids. 5th edition.
       New York: McGraw-Hill Professional, 2000.
    '''
    def list_methods():
        methods = []
        if none_and_length_check([zs, omegas]):
            methods.append('SIMPLE')
        methods.append('NONE')
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]

    if Method == 'SIMPLE':
        _omega = mixing_simple(zs, omegas)
    elif Method == 'NONE':
        _omega = None
    else:
        raise Exception('Failure in in function')
    return _omega

Response: r This function calculates the acentric factor of a multicomponent mixture.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def StielPolar(Tc=None, Pc=None, omega=None, CASRN='', Method=None,
               AvailableMethods=False):
    r'''This function handles the calculation of a chemical's Stiel Polar
    factor, directly through the definition of Stiel-polar factor if possible.
    Requires Tc, Pc, acentric factor, and a vapor pressure datum at Tr=0.6.

    Will automatically select a method to use if no Method is provided;
    returns None if the data is not available and cannot be calculated.

    .. math::
        x = \log P_r|_{T_r=0.6} + 1.70 \omega + 1.552

    Parameters
    ----------
    Tc : float
        Critical temperature of fluid [K]
    Pc : float
        Critical pressure of fluid [Pa]
    omega : float
        Acentric factor of the fluid [-]
    CASRN : string
        CASRN [-]

    Returns
    -------
    factor : float
        Stiel polar factor of compound
    methods : list, only returned if AvailableMethods == True
        List of methods which can be used to obtain Stiel polar factor with the
        given inputs

    Other Parameters
    ----------------
    Method : string, optional
        The method name to use. Only 'DEFINITION' is accepted so far.
        All valid values are also held in the list Stiel_polar_methods.
    AvailableMethods : bool, optional
        If True, function will determine which methods can be used to obtain
        Stiel-polar factor for the desired chemical, and will return methods
        instead of stiel-polar factor

    Notes
    -----
    Only one source is available for this function. It is:

        * 'DEFINITION', based on the definition of
          Stiel Polar Factor presented in [1]_, using vapor pressure data.

    A few points have also been published in [2]_, which may be used for
    comparison. Currently this is only used for a surface tension correlation.

    Examples
    --------
    >>> StielPolar(647.3, 22048321.0, 0.344, CASRN='7732-18-5')
    0.024581140348734376

    References
    ----------
    .. [1] Halm, Roland L., and Leonard I. Stiel. "A Fourth Parameter for the
       Vapor Pressure and Entropy of Vaporization of Polar Fluids." AIChE
       Journal 13, no. 2 (1967): 351-355. doi:10.1002/aic.690130228.
    .. [2] D, Kukoljac Miloš, and Grozdanić Dušan K. "New Values of the
       Polarity Factor." Journal of the Serbian Chemical Society 65, no. 12
       (January 1, 2000). http://www.shd.org.rs/JSCS/Vol65/No12-Pdf/JSCS12-07.pdf
    '''
    def list_methods():
        methods = []
        if Tc and Pc and omega:
            methods.append('DEFINITION')
        methods.append('NONE')
        return methods
    if AvailableMethods:
        return list_methods()
    if not Method:
        Method = list_methods()[0]
    if Method == 'DEFINITION':
        P = VaporPressure(CASRN=CASRN).T_dependent_property(Tc*0.6)
        if not P:
            factor = None
        else:
            Pr = P/Pc
            factor = log10(Pr) + 1.70*omega + 1.552
    elif Method == 'NONE':
        factor = None
    else:
        raise Exception('Failure in in function')
    return factor

Response: r Returns a new Stiel - polar factor for the given chemical.


Instruction:
Can you generate a brief explanation for the following Python 3 code
def VDI_tabular_data(CASRN, prop):
    r'''This function retrieves the tabular data available for a given chemical
    and a given property. Lookup is based on CASRNs. Length of data returned
    varies between chemicals. All data is at saturation condition from [1]_.

    Function has data for 58 chemicals.

    Parameters
    ----------
    CASRN : string
        CASRN [-]
    prop : string
        Property [-]

    Returns
    -------
    Ts : list
        Temperatures where property data is available, [K]
    props : list
        Properties at each temperature, [various]

    Notes
    -----
    The available properties are 'P', 'Density (l)', 'Density (g)', 'Hvap',
    'Cp (l)', 'Cp (g)', 'Mu (l)', 'Mu (g)', 'K (l)', 'K (g)', 'Pr (l)',
    'Pr (g)', 'sigma', 'Beta', 'Volume (l)', and 'Volume (g)'.

    Data is available for all properties and all chemicals; surface tension
    data was missing for mercury, but added as estimated from the a/b
    coefficients listed in Jasper (1972) to simplify the function.

    Examples
    --------
    >>> VDI_tabular_data('67-56-1', 'Mu (g)')
    ([337.63, 360.0, 385.0, 410.0, 435.0, 460.0, 500.0], [1.11e-05, 1.18e-05, 1.27e-05, 1.36e-05, 1.46e-05, 1.59e-05, 2.04e-05])

    References
    ----------
    .. [1] Gesellschaft, VDI, ed. VDI Heat Atlas. 2E. Berlin : Springer, 2010.
    '''
    try:
        d = _VDISaturationDict[CASRN]
    except KeyError:
        raise Exception('CASRN not in VDI tabulation')
    try:
        props, Ts = d[prop], d['T']
    except:
        raise Exception('Proprty not specified correctly')
    Ts = [T for p, T in zip(props, Ts) if p]
    props = [p for p in props if p]

    # Not all data series convererge to correct values
    if prop == 'sigma':
        Ts.append(d['Tc'])
        props.append(0)
    return Ts, props

Response: r Returns the tabular data available for a given CASRN and property.


Instruction:
Here you have a function in Python 3, explain what it does
def Yoon_Thodos(T, Tc, Pc, MW):
    r'''Calculates the viscosity of a gas using an emperical formula
    developed in [1]_.

    .. math::
        \eta \xi \times 10^8 = 46.10 T_r^{0.618} - 20.40 \exp(-0.449T_r) + 1
        9.40\exp(-4.058T_r)+1

        \xi = 2173.424 T_c^{1/6} MW^{-1/2} P_c^{-2/3}

    Parameters
    ----------
    T : float
        Temperature of the fluid [K]
    Tc : float
        Critical temperature of the fluid [K]
    Pc : float
        Critical pressure of the fluid [Pa]
    MW : float
        Molwcular weight of fluid [g/mol]

    Returns
    -------
    mu_g : float
        Viscosity of gas, [Pa*S]

    Notes
    -----
    This equation has been tested. The equation uses SI units only internally.
    The constant 2173.424 is an adjustment factor for units.
    Average deviation within 3% for most compounds.
    Greatest accuracy with dipole moments close to 0.
    Hydrogen and helium have different coefficients, not implemented.
    This is DIPPR Procedure 8B: Method for the Viscosity of Pure,
    non hydrocarbon, nonpolar gases at low pressures

    Examples
    --------
    >>> Yoon_Thodos(300., 556.35, 4.5596E6, 153.8)
    1.0194885727776819e-05

    References
    ----------
    .. [1]  Yoon, Poong, and George Thodos. "Viscosity of Nonpolar Gaseous
       Mixtures at Normal Pressures." AIChE Journal 16, no. 2 (1970): 300-304.
       doi:10.1002/aic.690160225.
    '''
    Tr = T/Tc
    xi = 2173.4241*Tc**(1/6.)/(MW**0.5*Pc**(2/3.))
    a = 46.1
    b = 0.618
    c = 20.4
    d = -0.449
    e = 19.4
    f = -4.058
    return (1. + a*Tr**b - c * exp(d*Tr) + e*exp(f*Tr))/(1E8*xi)

Response: r Returns the viscosity of a given set of non - polar gases at normal pressure.


Instruction:
Write a Python 3 script to
calculate the viscosity of a gas mixture according to the given mixing rules.

Response:
def Wilke(ys, mus, MWs):
    r'''Calculates viscosity of a gas mixture according to
    mixing rules in [1]_.

    .. math::
        \eta_{mix} = \sum_{i=1}^n \frac{y_i \eta_i}{\sum_{j=1}^n y_j \phi_{ij}}

        \phi_{ij} = \frac{(1 + \sqrt{\eta_i/\eta_j}(MW_j/MW_i)^{0.25})^2}
        {\sqrt{8(1+MW_i/MW_j)}}

    Parameters
    ----------
    ys : float
        Mole fractions of gas components
    mus : float
        Gas viscosities of all components, [Pa*S]
    MWs : float
        Molecular weights of all components, [g/mol]

    Returns
    -------
    mug : float
        Viscosity of gas mixture, Pa*S]

    Notes
    -----
    This equation is entirely dimensionless; all dimensions cancel.
    The original source has not been reviewed or found.

    Examples
    --------
    >>> Wilke([0.05, 0.95], [1.34E-5, 9.5029E-6], [64.06, 46.07])
    9.701614885866193e-06

    References
    ----------
    .. [1] TODO
    '''
    if not none_and_length_check([ys, mus, MWs]):  # check same-length inputs
        raise Exception('Function inputs are incorrect format')
    cmps = range(len(ys))
    phis = [[(1 + (mus[i]/mus[j])**0.5*(MWs[j]/MWs[i])**0.25)**2/(8*(1 + MWs[i]/MWs[j]))**0.5
                    for j in cmps] for i in cmps]

    return sum([ys[i]*mus[i]/sum([ys[j]*phis[i][j] for j in cmps]) for i in cmps])


Instruction:
Write a Python 3 script for
calculating the Brokaw formula for a single resource in the system.

Response:
def Brokaw(T, ys, mus, MWs, molecular_diameters, Stockmayers):
    r'''Calculates viscosity of a gas mixture according to
    mixing rules in [1]_.

    .. math::
        \eta_{mix} = \sum_{i=1}^n \frac{y_i \eta_i}{\sum_{j=1}^n y_j \phi_{ij}}

        \phi_{ij} = \left( \frac{\eta_i}{\eta_j} \right)^{0.5} S_{ij} A_{ij}

        A_{ij} = m_{ij} M_{ij}^{-0.5} \left[1 +
        \frac{M_{ij} - M_{ij}^{0.45}}
        {2(1+M_{ij}) + \frac{(1 + M_{ij}^{0.45}) m_{ij}^{-0.5}}{1 + m_{ij}}} \right]

        m_{ij} = \left[ \frac{4}{(1+M_{ij}^{-1})(1+M_{ij})}\right]^{0.25}

        M_{ij} = \frac{M_i}{M_j}

        S_{ij} = \frac{1 + (T_i^* T_j^*)^{0.5} + (\delta_i \delta_j/4)}
        {[1+T_i^* + (\delta_i^2/4)]^{0.5}[1+T_j^*+(\delta_j^2/4)]^{0.5}}

        T^* = kT/\epsilon

    Parameters
    ----------
    T : float
        Temperature of fluid, [K]
    ys : float
        Mole fractions of gas components
    mus : float
        Gas viscosities of all components, [Pa*S]
    MWs : float
        Molecular weights of all components, [g/mol]
    molecular_diameters : float
        L-J molecular diameter  of all components, [angstroms]
    Stockmayers : float
        L-J Stockmayer energy parameters of all components, []

    Returns
    -------
    mug : float
        Viscosity of gas mixture, [Pa*S]

    Notes
    -----
    This equation is entirely dimensionless; all dimensions cancel.
    The original source has not been reviewed.

    This is DIPPR Procedure 8D: Method for the Viscosity of Nonhydrocarbon
    Vapor Mixtures at Low Pressure (Polar and Nonpolar)

    Examples
    --------
    >>> Brokaw(308.2, [0.05, 0.95], [1.34E-5, 9.5029E-6], [64.06, 46.07], [0.42, 0.19], [347, 432])
    9.699085099801568e-06

    References
    ----------
    .. [1] Brokaw, R. S. "Predicting Transport Properties of Dilute Gases."
       Industrial & Engineering Chemistry Process Design and Development
       8, no. 2 (April 1, 1969): 240-53. doi:10.1021/i260030a015.
    .. [2] Brokaw, R. S. Viscosity of Gas Mixtures, NASA-TN-D-4496, 1968.
    .. [3] Danner, Ronald P, and Design Institute for Physical Property Data.
       Manual for Predicting Chemical Process Design Data. New York, N.Y, 1982.
    '''
    cmps = range(len(ys))
    MDs = molecular_diameters
    if not none_and_length_check([ys, mus, MWs, molecular_diameters, Stockmayers]): # check same-length inputs
        raise Exception('Function inputs are incorrect format')
    Tsts = [T/Stockmayer_i for Stockmayer_i in Stockmayers]
    Sij = [[0 for i in cmps] for j in cmps]
    Mij = [[0 for i in cmps] for j in cmps]
    mij = [[0 for i in cmps] for j in cmps]
    Aij = [[0 for i in cmps] for j in cmps]
    phiij =[[0 for i in cmps] for j in cmps]

    for i in cmps:
        for j in cmps:
            Sij[i][j] = (1+(Tsts[i]*Tsts[j])**0.5 + (MDs[i]*MDs[j])/4.)/(1 + Tsts[i] + (MDs[i]**2/4.))**0.5/(1 + Tsts[j] + (MDs[j]**2/4.))**0.5
            if MDs[i] <= 0.1 and MDs[j] <= 0.1:
                Sij[i][j] = 1
            Mij[i][j] = MWs[i]/MWs[j]
            mij[i][j] = (4./(1+Mij[i][j]**-1)/(1+Mij[i][j]))**0.25

            Aij[i][j] = mij[i][j]*Mij[i][j]**-0.5*(1 + (Mij[i][j]-Mij[i][j]**0.45)/(2*(1+Mij[i][j]) + (1+Mij[i][j]**0.45)*mij[i][j]**-0.5/(1+mij[i][j])))

            phiij[i][j] = (mus[i]/mus[j])**0.5*Sij[i][j]*Aij[i][j]

    return sum([ys[i]*mus[i]/sum([ys[j]*phiij[i][j] for j in cmps]) for i in cmps])


Instruction:
Make a summary of the following Python 3 code
def load_all_methods(self):
        r'''Method which picks out coefficients for the specified chemical
        from the various dictionaries and DataFrames storing it. All data is
        stored as attributes. This method also sets :obj:`Tmin`, :obj:`Tmax`,
        :obj:`all_methods` and obj:`all_methods_P` as a set of methods for
        which the data exists for.

        Called on initialization only. See the source code for the variables at
        which the coefficients are stored. The coefficients can safely be
        altered once the class is initialized. This method can be called again
        to reset the parameters.
        '''
        methods, methods_P = [], []
        Tmins, Tmaxs = [], []
        if has_CoolProp and self.CASRN in coolprop_dict:
            methods.append(COOLPROP); methods_P.append(COOLPROP)
            self.CP_f = coolprop_fluids[self.CASRN]
            Tmins.append(self.CP_f.Tmin); Tmaxs.append(self.CP_f.Tc)
        if self.CASRN in _VDISaturationDict:
            methods.append(VDI_TABULAR)
            Ts, props = VDI_tabular_data(self.CASRN, 'Mu (l)')
            self.VDI_Tmin = Ts[0]
            self.VDI_Tmax = Ts[-1]
            self.tabular_data[VDI_TABULAR] = (Ts, props)
            Tmins.append(self.VDI_Tmin); Tmaxs.append(self.VDI_Tmax)
        if self.CASRN in Dutt_Prasad.index:
            methods.append(DUTT_PRASAD)
            _, A, B, C, self.DUTT_PRASAD_Tmin, self.DUTT_PRASAD_Tmax = _Dutt_Prasad_values[Dutt_Prasad.index.get_loc(self.CASRN)].tolist()
            self.DUTT_PRASAD_coeffs = [A, B, C]
            Tmins.append(self.DUTT_PRASAD_Tmin); Tmaxs.append(self.DUTT_PRASAD_Tmax)
        if self.CASRN in VN3_data.index:
            methods.append(VISWANATH_NATARAJAN_3)
            _, _, A, B, C, self.VISWANATH_NATARAJAN_3_Tmin, self.VISWANATH_NATARAJAN_3_Tmax = _VN3_data_values[VN3_data.index.get_loc(self.CASRN)].tolist()
            self.VISWANATH_NATARAJAN_3_coeffs = [A, B, C]
            Tmins.append(self.VISWANATH_NATARAJAN_3_Tmin); Tmaxs.append(self.VISWANATH_NATARAJAN_3_Tmax)
        if self.CASRN in VN2_data.index:
            methods.append(VISWANATH_NATARAJAN_2)
            _, _, A, B, self.VISWANATH_NATARAJAN_2_Tmin, self.VISWANATH_NATARAJAN_2_Tmax = _VN2_data_values[VN2_data.index.get_loc(self.CASRN)].tolist()
            self.VISWANATH_NATARAJAN_2_coeffs = [A, B]
            Tmins.append(self.VISWANATH_NATARAJAN_2_Tmin); Tmaxs.append(self.VISWANATH_NATARAJAN_2_Tmax)
        if self.CASRN in VN2E_data.index:
            methods.append(VISWANATH_NATARAJAN_2E)
            _, _, C, D, self.VISWANATH_NATARAJAN_2E_Tmin, self.VISWANATH_NATARAJAN_2E_Tmax = _VN2E_data_values[VN2E_data.index.get_loc(self.CASRN)].tolist()
            self.VISWANATH_NATARAJAN_2E_coeffs = [C, D]
            Tmins.append(self.VISWANATH_NATARAJAN_2E_Tmin); Tmaxs.append(self.VISWANATH_NATARAJAN_2E_Tmax)
        if self.CASRN in Perrys2_313.index:
            methods.append(DIPPR_PERRY_8E)
            _, C1, C2, C3, C4, C5, self.Perrys2_313_Tmin, self.Perrys2_313_Tmax = _Perrys2_313_values[Perrys2_313.index.get_loc(self.CASRN)].tolist()
            self.Perrys2_313_coeffs = [C1, C2, C3, C4, C5]
            Tmins.append(self.Perrys2_313_Tmin); Tmaxs.append(self.Perrys2_313_Tmax)
        if self.CASRN in VDI_PPDS_7.index:
            methods.append(VDI_PPDS)
            self.VDI_PPDS_coeffs = _VDI_PPDS_7_values[VDI_PPDS_7.index.get_loc(self.CASRN)].tolist()[2:]
        if all((self.MW, self.Tc, self.Pc, self.omega)):
            methods.append(LETSOU_STIEL)
            Tmins.append(self.Tc/4); Tmaxs.append(self.Tc) # TODO: test model at low T
        if all((self.MW, self.Tm, self.Tc, self.Pc, self.Vc, self.omega, self.Vml)):
            methods.append(PRZEDZIECKI_SRIDHAR)
            Tmins.append(self.Tm); Tmaxs.append(self.Tc) # TODO: test model at Tm
        if all([self.Tc, self.Pc, self.omega]):
            methods_P.append(LUCAS)
        self.all_methods = set(methods)
        self.all_methods_P = set(methods_P)
        if Tmins and Tmaxs:
            self.Tmin, self.Tmax = min(Tmins), max(Tmaxs)

Response: r This method loads all methods for the specified chemicalicalCOOKIE.


Instruction:
Can you tell what is the following Python 3 function doing
def calculate_P(self, T, P, method):
        r'''Method to calculate pressure-dependent liquid viscosity at
        temperature `T` and pressure `P` with a given method.

        This method has no exception handling; see `TP_dependent_property`
        for that.

        Parameters
        ----------
        T : float
            Temperature at which to calculate viscosity, [K]
        P : float
            Pressure at which to calculate viscosity, [K]
        method : str
            Name of the method to use

        Returns
        -------
        mu : float
            Viscosity of the liquid at T and P, [Pa*S]
        '''
        if method == LUCAS:
            mu = self.T_dependent_property(T)
            Psat = self.Psat(T) if hasattr(self.Psat, '__call__') else self.Psat
            mu = Lucas(T, P, self.Tc, self.Pc, self.omega, Psat, mu)
        elif method == COOLPROP:
            mu = PropsSI('V', 'T', T, 'P', P, self.CASRN)
        elif method in self.tabular_data:
            mu = self.interpolate_P(T, P, method)
        return mu

Response: r Method to calculate pressure - dependent liquid viscosity at a given temperature T and pressure P.


Instruction:
Make a summary of the following Python 3 code
def calculate(self, T, P, zs, ws, method):
        r'''Method to calculate viscosity of a liquid mixture at
        temperature `T`, pressure `P`, mole fractions `zs` and weight fractions
        `ws` with a given method.

        This method has no exception handling; see `mixture_property`
        for that.

        Parameters
        ----------
        T : float
            Temperature at which to calculate the property, [K]
        P : float
            Pressure at which to calculate the property, [Pa]
        zs : list[float]
            Mole fractions of all species in the mixture, [-]
        ws : list[float]
            Weight fractions of all species in the mixture, [-]
        method : str
            Name of the method to use

        Returns
        -------
        mu : float
            Viscosity of the liquid mixture, [Pa*s]
        '''
        if method == MIXING_LOG_MOLAR:
            mus = [i(T, P) for i in self.ViscosityLiquids]
            return mixing_logarithmic(zs, mus)
        elif method == MIXING_LOG_MASS:
            mus = [i(T, P) for i in self.ViscosityLiquids]
            return mixing_logarithmic(ws, mus)
        elif method == LALIBERTE_MU:
            ws = list(ws) ; ws.pop(self.index_w)
            return Laliberte_viscosity(T, ws, self.wCASs)
        else:
            raise Exception('Method not valid')

Response:
r Method to calculate the viscosity of a liquid mixture at
        temperature pressure P mole fractions zs and weight fractions ws.


Instruction:
Here you have a function in Python 3, explain what it does
def calculate(self, T, method):
        r'''Method to calculate low-pressure gas viscosity at
        tempearture `T` with a given method.

        This method has no exception handling; see `T_dependent_property`
        for that.

        Parameters
        ----------
        T : float
            Temperature of the gas, [K]
        method : str
            Name of the method to use

        Returns
        -------
        mu : float
            Viscosity of the gas at T and a low pressure, [Pa*S]
        '''
        if method == GHARAGHEIZI:
            mu = Gharagheizi_gas_viscosity(T, self.Tc, self.Pc, self.MW)
        elif method == COOLPROP:
            mu = CoolProp_T_dependent_property(T, self.CASRN, 'V', 'g')
        elif method == DIPPR_PERRY_8E:
            mu = EQ102(T, *self.Perrys2_312_coeffs)
        elif method == VDI_PPDS:
            mu =  horner(self.VDI_PPDS_coeffs, T)
        elif method == YOON_THODOS:
            mu = Yoon_Thodos(T, self.Tc, self.Pc, self.MW)
        elif method == STIEL_THODOS:
            mu = Stiel_Thodos(T, self.Tc, self.Pc, self.MW)
        elif method == LUCAS_GAS:
            mu = lucas_gas(T, self.Tc, self.Pc, self.Zc, self.MW, self.dipole, CASRN=self.CASRN)
        elif method in self.tabular_data:
            mu = self.interpolate(T, method)
        return mu

Response: r Method to calculate low - pressure gas viscosity at a given temperature.


Instruction:
Can you generate the documentation for the following Python 3 function
def load_all_methods(self):
        r'''Method to initialize the object by precomputing any values which
        may be used repeatedly and by retrieving mixture-specific variables.
        All data are stored as attributes. This method also sets :obj:`Tmin`,
        :obj:`Tmax`, and :obj:`all_methods` as a set of methods which should
        work to calculate the property.

        Called on initialization only. See the source code for the variables at
        which the coefficients are stored. The coefficients can safely be
        altered once the class is initialized. This method can be called again
        to reset the parameters.
        '''
        methods = [SIMPLE]
        if none_and_length_check((self.MWs, self.molecular_diameters, self.Stockmayers)):
            methods.append(BROKAW)
        if none_and_length_check([self.MWs]):
            methods.extend([WILKE, HERNING_ZIPPERER])
        self.all_methods = set(methods)
        Tmins = [i.Tmin for i in self.ViscosityGases if i.Tmin]
        Tmaxs = [i.Tmax for i in self.ViscosityGases if i.Tmax]
        if Tmins:
            self.Tmin = max(Tmins)
        if Tmaxs:
            self.Tmax = max(Tmaxs)

Response: r Method to initialize the object by precomputing any values which should be used repeatedly and by retrieving any values which should be used repeatedly and by retrieving the mixture - specific variables.