threeML.utils.bayesian_blocks module

threeML.utils.bayesian_blocks.bayesian_blocks(tt, ttstart, ttstop, p0, bkg_integral_distribution=None)[source]

Divide a series of events characterized by their arrival time in blocks of perceptibly constant count rate. If the background integral distribution is given, divide the series in blocks where the difference with respect to the background is perceptibly constant.

Parameters:

  • tt – arrival times of the events

  • ttstart – the start of the interval

  • ttstop – the stop of the interval

  • p0 – the false positive probability. This is used to decide the penalization on the likelihood, so this parameter affects the number of blocks

  • bkg_integral_distribution – (default: None) If given, the algorithm account for the presence of the background and finds changes in rate with respect to the background

Returns:

the np.array containing the edges of the blocks

threeML.utils.bayesian_blocks.bayesian_blocks_not_unique(tt, ttstart, ttstop, p0)[source]