def solve_T(self, P, V, quick=True):
<EOL><INDENT>return super(PR, self).solve_T(P, V, quick=quick) <EOL><DEDENT>Tc, a, b, kappa0, kappa1, kappa2, kappa3 = self.Tc, self.a, self.b, self.kappa0, self.kappa1, self.kappa2, self.kappa3<EOL>if quick:<EOL><INDENT>x0 = V - b<EOL>R_x0 = R/x0<EOL>x5 = (<NUM_LIT>*(V*(V + b) + b*x0))<EOL>x4 = <NUM_LIT>*kappa0<EOL>def to_solve(T):<EOL><INDENT>x1 = T/Tc<EOL>x2 = x1**<NUM_LIT:0.5><EOL>x3 = x2 - <NUM_LIT:1.><EOL>return (R_x0*T - a*(x3*(x4 - (kappa1 + kappa2*x3*(-kappa3 + x1))*(<NUM_LIT>*x1 - <NUM_LIT>)*(x2 + <NUM_LIT:1.>)) - <NUM_LIT>)**<NUM_LIT:2>/x5) - P<EOL><DEDENT><DEDENT>else:<EOL><INDENT>def to_solve(T):<EOL><INDENT>P_calc = R*T/(V - b) - a*((kappa0 + (kappa1 + kappa2*(-sqrt(T/Tc) + <NUM_LIT:1>)*(-T/Tc + kappa3))*(sqrt(T/Tc) + <NUM_LIT:1>)*(-T/Tc + <NUM_LIT:7>/<NUM_LIT:10>))*(-sqrt(T/Tc) + <NUM_LIT:1>) + <NUM_LIT:1>)**<NUM_LIT:2>/(V*(V + b) + b*(V - b))<EOL>return P_calc - P<EOL><DEDENT><DEDENT>return newton(to_solve, Tc*<NUM_LIT:0.5>)<EOL>
r'''Method to calculate `T` from a specified `P` and `V` for the PRSV2
        EOS. Uses `Tc`, `a`, `b`, `kappa0`, `kappa1`, `kappa2`, and `kappa3`
        as well, obtained from the class's namespace.

        Parameters
        ----------
        P : float
            Pressure, [Pa]
        V : float
            Molar volume, [m^3/mol]
        quick : bool, optional
            Whether to use a SymPy cse-derived expression (somewhat faster) or 
            individual formulas.

        Returns
        -------
        T : float
            Temperature, [K]

        Notes
        -----
        Not guaranteed to produce a solution. There are actually 8 solutions,
        six with an imaginary component at a tested point. The two temperature
        solutions are quite far apart, with one much higher than the other;
        it is possible the solver could converge on the higher solution, so use
        `T` inputs with care. This extra solution is a perfectly valid one
        however.