detectda.hypo

Classes

VacuumSeries

Functionality to generate vacuum region videos for multiple hypothesis testing.

Module Contents

class detectda.hypo.VacuumSeries(vacuum_video, observed_ImageSeries, parametric=True, div=1, n_jobs=None)[source]

Bases: detectda.imgs.ImageSeries

Functionality to generate vacuum region videos for multiple hypothesis testing.

adjust_alpha(alpha, conservative=False)[source]

Adjust p-values based on a different alpha value.

Parameters:

  • alpha (float) – Statistical significance level.

  • conservative (bool, optional) – Whether to use Benjamini-Yekutieli. The default is False.

Return type:

None.

fit(convert_to_int=False)[source]

Fits the Poisson mle for the vacuum region if parametric==True

Else, it fits the empirical probability mass function.

gen_images(n)[source]

Generate and return a random image according to estimated null distribution

kolm_dist()[source]

Check how far the empirical distribution of vacuum values is from Poisson with parameter equal to mle, in terms of the Kolmogorov distance

Uses the DKW inequality with the tight constant = 2 for Poisson testing.

plot_hypo()[source]

Plots hypothesis testing sequence.

transform(n, func='pers_entr', seed=0, alpha=0.05, conservative=False)[source]

Collects p-values and rejections for based off n Monte Carlo simulations…