Octopodes.jl － Joint exoplanet modelling

Getting started

Basic usage:

using Octopodes, Random

dict = Octopodes.Examples.small_dict()
runs = IndepRuns(dict)
b = Binning(runs, n_log_P_yr_intervals = 20, n_log_q_intervals = 20)
binned = bin(b, runs)
result = run_imh(Xoshiro(1), binned);
typeof(result)

@NamedTuple{psi_trace::Matrix{Float64}, pi_trace::Matrix{Float64}, accept_prs::Vector{Float64}}

Summarize the joint-π posterior (warmup drop, per-bin rate density   ,   and ) and plot the population heatmap. The bin edges are read from b, so they never have to be passed by hand:

fig = population_posterior_plot(result, b; warmup_frac = 0.2)

If you also want the summarized quantities, build the PopulationPosterior explicitly and plot that:

post = population_posterior(result, b; warmup_frac = 0.2)
post.lambda   # n_keep × n_log_P × n_log_q  (E[n]·π per bin)
post.P_geq    # max_n_companions × n_keep   (P(n ≥ c))
fig = population_posterior_plot(post)

Bins whose posterior is driven by the prior rather than the data can be masked out using the per-bin relative prior-sensitivity. Masked bins are blanked on the heatmap and dropped from the marginal sums:

sens = relative_sensitivities(binned, 1e-3)
fig = population_posterior_plot(post; sensitivity = sens, sensitivity_threshold = 2.0)

How to generate/preview doc

Use include("docs/preview.jl") or include("docs/make.jl").

How to develop

JET and Revise need to be in sync, so use the following to start Julia: ./dev.sh This will load the Test environment. Run individual tests with e.g., include("test/test_imh.jl).

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