BAT.jl
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A Bayesian Analysis Toolkit in Julia
Adds support for doing marg_s = BAT.bat_marginalize(some_shaped_samples, i) where `i` is an Integer, Vector or Tuple of Integers or Unit Range. The new marginalized samples will have `N` ScalarShaped parameters...
Hello! I am a new user of BAT, and currently use bat_report(samples) for the credible intervals to be printed on screen. However, that only prints out the 68% CI, not...
This pull request changes the compat entry for the `Distributions` package from `0.24.0 - 0.25.64` to `0.24.0 - 0.25.64, 0.25`. This keeps the compat entries for earlier versions. Note: I...
WIP * need to add a bit more support for `NamedTuples` * need to do some minor adaptions & clean-up * @oschulz: I did not (yet) add a `FixedBinning` type...
This issue is intended to keep track of modularizing (splitting up) BAT to reduce package load time(s) and increase flexibility. The current high load time of BAT is mainly due...
Hi! Found this on Github and I'd like to say, BAT.jl looks really interesting, and I'm always happy to see new tools for Bayesian analysis in Julia! I have a...
Support pyhf
Hello, I believe the previous version of BAT had an interface for working with RooFit likelihoods (that can be stored in a RooFit workspace in a ROOT file). I am...
as of: - #70 we can use histogram as prior, in HEP (as @oschulz knows), the input data is also histogram (with same binning of course), and each uncertainty variation...
When using the bridge sampler on samples generated with non-integer weights, it crashes (stack trace below). It is in particular the `nsamples=Int(sum(second_batch.weight))` here: https://github.com/bat/BAT.jl/blob/e4fcc532e5eb1ad192374d062ae50328d4ddfa21/src/integration/bridge_sampling_integration.jl#L134 I suggest for instance to use...
Sampling with `nchains=1` results in an AssertionError: ``` JULIA: AssertionError: length(chains) == nchains Stacktrace: [1] mcmc_init!(rng::Random123.Philox4x{UInt64, 10}, algorithm::BAT.MetropolisHastings{BAT.MvTDistProposal, BAT.RepetitionWeighting{Int64}, BAT.AdaptiveMHTuning}, density::BAT.PosteriorDensity{Float64, Float64, BAT.ReshapedDensity{BAT.TransformedDensity{BAT.DensityWithShape{BAT.LFDensity{PyObject}, ScalarShape{Real}}, BAT.DistributionTransform{BAT.StandardUvNormal{Float64}, Distributions.Uniform{Float64}, ScalarShape{Real}, ScalarShape{Real}}, BAT.TDNoCorr, ScalarShape{Real}},...