Add Baker-Cousins style log likelihood #2
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ashleyrback
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Jan 20, 2015
This is the class described in snoplusuk#4, and provides the functionality required by snoplusuk#2, snoplusuk#5 and snoplusuk#6, although the structure is modified. As such this pull request fixes snoplusuk#2, closes snoplusuk#4, resolves snoplusuk#5 and fixes snoplusuk#6. The module contains three functions to calculate chi squared for a number given number of observed events and number of expected events. The forms of chi squared calculation included are Pearson's, Neyman's and the Poisson Likelihood chi squared. The module also adds the `ChiSquared` class that acts as a calculator for a given `form` of chi squared calculation. It can also be initialised with penalty term information via the keyword argument `penalty_term`. Or this can be specified when calling the `get_chi_squared` method. The method takes two 1D numpy arrays, representing the observed (or "data") spectrum and the expected (or "MC") spectrum, as arguments and iterates over the array, calculating the chi squared for each bin using the appropriate function, and adding a penalty term if required. The method returns the total chi squared comparing the two spectra.
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Write a method to perform calculation of log likelihood, based on Baker-Cousins method of setting limits
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get_log_likelihoodmethod in #4The text was updated successfully, but these errors were encountered: