eos.py 文件源码

def fit(self):
        # Quadratic fit to get an initial guess for the parameters. 
        # Thanks: https://github.com/materialsproject/pymatgen
        # -> pymatgen/io/abinitio/eos.py 
        a, b, c = np.polyfit(self.volume, self.energy, 2)
        v0 = -b/(2*a)
        e0 = a*v0**2 + b*v0 + c
        b0 = 2*a*v0
        b1 = 4  # b1 is usually a small number like 4
        if not self.volume.min() < v0 and v0 < self.volume.max():
            raise StandardError('The minimum volume of a fitted parabola is not in the input volumes')

        # need to use lst2dct and dct2lst here to keep the order of parameters 
        pp0_dct = dict(e0=e0, b0=b0, b1=b1, v0=v0)
        target = lambda pp, v: self.energy - self.func(v, self.func.lst2dct(pp))
        pp_opt, ierr = leastsq(target, 
                               self.func.dct2lst(pp0_dct), 
                               args=(self.volume,))
        self.params = self.func.lst2dct(pp_opt)