A python implementation of the nested sampling algorithm written by Stefano Martiniani and Jacob Stevenson
This implementation uses the language of statistical mechanics (partition function, phase space, configurations, energy, density of states) rather than the language of bayesian sampling (likelihood, prior, evidence). This is simply for convenience, the method is the same.
Tools:
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built-in parallelisation on single computing node (max total number of cpu threads on a single machine)
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built-in parallelisation by distributed computing, ideal to run calculations on a cluster or across a network
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ability to save and restart from checkpoint binary files, ideal for very long calculations
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scripts to compute heat capacities and perform error analysis
See the examples for how to run the method