PointMeasures¶
-
class
astropy.stats.
PointMeasures
(p0=0.05, gamma=None, ncp_prior=None)[source] [edit on github]¶ Bases:
astropy.stats.FitnessFunc
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 \({\tt ncp\_prior} = -\ln({\tt gamma})\). Ifncp_prior
is specified,gamma
andp0
are ignored.
Methods Summary
fitness
(a_k, b_k)validate_input
(t, x, sigma)Validate inputs to the model. Methods Documentation
-
fitness
(a_k, b_k)[source] [edit on github]¶
-
validate_input
(t, x, sigma)[source] [edit on github]¶ Validate inputs to the model.
Parameters: - t : array_like
times of observations
- x : array_like (optional)
values observed at each time
- sigma : float or array_like (optional)
errors in values x
Returns: - t, x, sigma : array_like, float or None
validated and perhaps modified versions of inputs