Python excess_variance Examples

Example #1

    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

Example #2

File: varenergyspectrum.py Project: matteobachetti/stingray

    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

Example #3

File: test_lightcurve.py Project: abigailStev/stingray

def evar_fun(lc):
    from stingray.utils import excess_variance
    return excess_variance(lc, normalization='none')

Example #4

File: test_lightcurve.py Project: guillochon/stingray

def evar_fun(lc):
    from stingray.utils import excess_variance
    return excess_variance(lc, normalization='none')

Example #5

File: exvar.py Project: swapsha96/HENDRICS

def excvar_norm(lc):
    return excess_variance(lc, normalization='norm_xs')

Example #6

File: exvar.py Project: swapsha96/HENDRICS

def fvar(lc):
    return excess_variance(lc, normalization='fvar')

Example #7

File: test_lightcurve.py Project: pabell/stingray

 def excvar(lc):
     from stingray.utils import excess_variance
     return excess_variance(lc, normalization='fvar')

Example #8

File: test_lightcurve.py Project: pabell/stingray

 def excvar(lc):
     from stingray.utils import excess_variance
     return excess_variance(lc, normalization='fvar')