diffusion.py 文件源码

def process(self, **kwargs):
        """Process module."""
        Transform.process(self, **kwargs)
        self._kappa = kwargs[self.key('kappa')]
        self._kappa_gamma = kwargs[self.key('kappagamma')]
        self._m_ejecta = kwargs[self.key('mejecta')]
        self._v_ejecta = kwargs[self.key('vejecta')]

        self._tau_diff = np.sqrt(self.DIFF_CONST * self._kappa *
                                 self._m_ejecta / self._v_ejecta) / DAY_CGS
        self._trap_coeff = (
            self.TRAP_CONST * self._kappa_gamma * self._m_ejecta /
            (self._v_ejecta ** 2)) / DAY_CGS ** 2
        td2, A = self._tau_diff ** 2, self._trap_coeff  # noqa: F841

        new_lums = np.zeros_like(self._times_to_process)
        if len(self._dense_times_since_exp) < 2:
            return {self.dense_key('luminosities'): new_lums}
        min_te = min(self._dense_times_since_exp)
        tb = max(0.0, min_te)
        linterp = interp1d(
            self._dense_times_since_exp, self._dense_luminosities, copy=False,
            assume_sorted=True)

        uniq_times = np.unique(self._times_to_process[
            (self._times_to_process >= tb) & (
                self._times_to_process <= self._dense_times_since_exp[-1])])
        lu = len(uniq_times)

        num = int(round(self.N_INT_TIMES / 2.0))
        lsp = np.logspace(
            np.log10(self._tau_diff /
                     self._dense_times_since_exp[-1]) +
            self.MIN_LOG_SPACING, 0, num)
        xm = np.unique(np.concatenate((lsp, 1 - lsp)))

        int_times = np.clip(
            tb + (uniq_times.reshape(lu, 1) - tb) * xm, tb,
            self._dense_times_since_exp[-1])

        int_te2s = int_times[:, -1] ** 2
        int_lums = linterp(int_times)  # noqa: F841
        int_args = int_lums * int_times * np.exp(
            (int_times ** 2 - int_te2s.reshape(lu, 1)) / td2)
        int_args[np.isnan(int_args)] = 0.0

        uniq_lums = np.trapz(int_args, int_times)
        uniq_lums *= -2.0 * np.expm1(-A / int_te2s) / td2

        new_lums = uniq_lums[np.searchsorted(uniq_times,
                                             self._times_to_process)]

        return {self.key('tau_diffusion'): self._tau_diff,
                self.dense_key('luminosities'): new_lums}