Dynesty

Purpose

Dynesty runs dynamic nested sampling for posterior exploration and evidence estimation.

Full Sampling Section Keys

• Sampling.Method (required): must be Dynesty.
• Sampling.Variables (required, array):
• name, description, distribution.type, distribution.parameters
• Runtime-safe parameter sets: Flat(min,max), Log(min,max), Normal(mean,stddev), Log-Normal(mean,stddev), Logit(location,scale)
• Sampling.LogLikelihood (required, array): {name, expression}
• Sampling.selection (optional, string)
• Sampling.Bounds (required for production use):
• nlive (required, integer)
• rseed (required, integer)
• run_nested (required, object): forwarded to DynamicNestedSampler.run_nested(**run_nested)

Full Skeleton

Sampling:
  Method: "Dynesty"
  Variables:
    - name: p1
      description: parameter 1
      distribution:
        type: Flat
        parameters:
          min: 0.0
          max: 1.0
  LogLikelihood:
    - name: L_total
      expression: "-0.5*((obs-100.0)/10.0)^2"
  selection: "p1 > 0"
  Bounds:
    nlive: 800
    rseed: 42
    run_nested:
      dlogz_init: 0.01
      maxiter: 100000
      print_progress: true

Example

Sampling:
  Method: "Dynesty"
  Variables:
    - name: xx
      description: x
      distribution:
        type: Flat
        parameters:
          min: 0.0
          max: 31.4159
    - name: yy
      description: y
      distribution:
        type: Flat
        parameters:
          min: 0.0
          max: 31.4159
  LogLikelihood:
    - name: L_z
      expression: "-0.5*((z-100.0)/10.0)^2"
  Bounds:
    nlive: 800
    rseed: 42
    run_nested:
      dlogz_init: 0.01
      maxiter: 100000
      print_progress: true