pint.eventstats

Various routines for calculating pulsation test statistics on event data and helper functions.

author: M. Kerr <matthew.kerr@gmail.com>

Functions

best_m(phases[, weights, m])
cosm(phases[, m])	Return the cosine test for each harmonic up to the specified m.
em_four(phases[, m, weights])	Return the empirical Fourier coefficients up to the mth harmonic.
em_lc(coeffs, dom)	Evaluate the light curve at the provided phases (0 to 1) for the provided coeffs, e.g., as estimated by em_four.
from_array(x)
h2sig(h)	Shortcut function for calculating sigma from the H-test.
hm(phases[, m, c])	Calculate the H statistic (de Jager et al. 1989) for given phases.
hmw(phases, weights[, m, c])	Calculate the H statistic (de Jager et al. 1989) and weight each sine/cosine with the weights in the argument.
sf_h20_dj2010(h)	Use the approximate asymptotic calibration from de Jager et al. 2010.
sf_hm(h[, m, c, logprob])	Return (analytic, asymptotic) survival function (1-F(h)) for the generalized H-test.
sf_stackedh(k, h[, l])	Return the chance probability for a stacked H test assuming the null df for H is exponentially distributed with scale l and that there are k sub-integrations yielding a total TS of h.
sf_z2m(ts[, m])	Return the survival function (chance probability) according to the asymptotic calibration for the Z^2_m test.
sig2h20(sig)	Use approximate (de Jager 2010) relation to invert.
sig2sigma(sig[, two_tailed, logprob])	Convert tail probability to "sigma" units.
sigma2sig(sigma[, two_tailed])	Convert "sigma" units to chance probability, i.e., return the integral of the normal distribution from sigma to infinity, or twice that quantity if two_tailed.
sigma_trials(sigma, trials)
to_array(x[, dtype])
vec(func)
z2m(phases[, m])	Return the Z^2_m test for each harmonic up to the specified m.
z2mw(phases, weights[, m])	Return the Z^2_m test for each harmonic up to the specified m.