# PointMeasures¶

class astropy.stats.PointMeasures(p0=0.05, gamma=None, ncp_prior=None)[source] [edit on github]

Bayesian blocks fitness for point measures

Parameters: p0 : float (optional) False alarm probability, used to compute the prior on $$N_{\rm blocks}$$ (see eq. 21 of Scargle 2012). If gamma is specified, p0 is ignored. ncp_prior : float (optional) If specified, use the value of ncp_prior to compute the prior as above, using the definition $${\tt ncp\_prior} = -\ln({\tt gamma})$$. If ncp_prior is specified, gamma and p0 are ignored.

Methods Summary

 fitness(a_k, b_k) validate_input(t, x, sigma)

Methods Documentation

fitness(a_k, b_k)[source] [edit on github]
validate_input(t, x, sigma)[source] [edit on github]