b_blocks

A simple Bayesian block decomposition utility.
The algorithm is given in Scargle, Jeffrey D.; Norris, Jay P.; Jackson, Brad; Chiang, James Studies in Astronomical Time Series Analysis. VI. Bayesian Block Representations, http://adsabs.harvard.edu/abs/2013ApJ...764..167S and Jackson et al., An algorithm for optimal partitioning of data on an interval, http://adsabs.harvard.edu/abs/2005ISPL...12..105J

The code is partially based on battblocks utility https://heasarc.gsfc.nasa.gov/ftools/caldb/help/battblocks.html

Usage

b_blocks --PriorRatio=9.0 --FileName=input.thc --bbFileName=output.thi --LcType=Poisson

PriorRatio: The higher the PriorRatio the less blocks are produced.

Poisson counts (LcType=Poisson)

input.thc format:
Ti Tf Counts
Ti and Tf - a time bin begin and end
Count - number of counts in the bin

input.thc example: 2.919 5.863 488.010
5.863 8.807 451.890
8.807 11.751 453.890
11.751 14.695 473.960

Gaussian distributed quantity (LcType=Gauss)

input.thi format:
Ti Tf y yErr
Ti and Tf - a time bin begin and end
y - a quantity in the bin
yErr - standard deviation of the quantity

input.thi example:
0.000 0.064 10.000 1.000
0.064 0.128 10.000 1.000
0.128 0.192 10.000 1.000

Output

output.thi (containing Bayesian blocks) format:
Ti Tf CountRate CountRateErr
Ti and Tf - a block begin and end
CountRate - count rate in the block (for Poisson data) or averaged "x" (for Gaussian data) CountRateErr - standard deviation of the count rate in the block, for Poisson data CountRateErr = sqrt(Rate/(Tf-Ti))

output.thi example:
2.416 14919.662 156.425 0.102
14919.662 14931.438 170.200 3.802
14931.438 56659.690 156.925 0.061

Command line arguments

-h, --help print this help and exit
-p, --PriorRatio prior ratio
-f, --FileName input THC (LcType=Poisson) or THI (LcType=Gauss) file name
-o, --bbFileName output THI file name
-t, --LcType Gauss|Poisson

Installation

In the source code folder run
cmake .
make

gsl and gslcblas are required.