def _spectrum_function(self): spec = np.zeros(len(self.energy_intervals)) spec_err = np.zeros_like(spec) for i, eint in enumerate(self.energy_intervals): lc = self._construct_lightcurves(eint, exclude=False, only_base=True) spec[i], spec_err[i] = excess_variance(lc, self.normalization) return spec, spec_err
def evar_fun(lc): from stingray.utils import excess_variance return excess_variance(lc, normalization='none')
def excvar_norm(lc): return excess_variance(lc, normalization='norm_xs')
def fvar(lc): return excess_variance(lc, normalization='fvar')
def excvar(lc): from stingray.utils import excess_variance return excess_variance(lc, normalization='fvar')