ppsds 0.0.1 (private beta)

A private beta, not on PyPI. Everything below is the first release; 0.0.1 is handed to
collaborators through a GitHub Release so that problems are found before the version number that
matters is spent. The first public version will be 0.1.0, and it will contain this.

Added

• ppsds.ambiguity — conic-moment ambiguity sets over an additive-drift assumption
  (LinearAmbiguitySet, NonlinearAmbiguitySet), covering drift, noise-mean and covariance
  uncertainty through a small set of radii.
• ppsds.probabilistic_predictor — NominalPredictor, NoiseDrpp and EigDrpp, where
  EigDrpp solves the paper's cone program (eigvec_fixed_minmax, equation 19) with CVXPY/SCS.
• ppsds.scoring_rule — the logarithmic scoring rule.
• ppsds.environment — a gymnasium Env assembled from an ambiguity set plus a dynamics mode
  (FixedDynamics, RandomDynamics, PreSampledDynamics,
  EigvecFixedAdversarialDynamics), for simulating ambiguity rather than consuming it.
• ppsds.dynamics — robotic-arm models and system identification.
• ppsds.experiment and ppsds.visualization — a multiprocess experiment driver with a
  validating cache, and the paper's figures. These need the optional experiments extra.
• Examples for applying a predictor to an environment you already have
  (examples/scene1_own_environment/) and for building a simulated one
  (examples/scene2_simulated_ambiguity/).

Known limitations

Recorded here rather than only in the issue tracker, because they affect whether the package
fits a given problem:

• alphas['A'] and alphas['B'] perturb only the superdiagonal of A and only B[0, -1],
  which is the structure of the paper's own example. Uncertainty in arbitrary entries of A and
  B is not expressible through them.
• The batch experiment driver requires the fork start method, because one ambiguity set holds
  lambdas and cannot be pickled. It asserts this at startup and fails loudly.
• The A/B time-varying path of Predictor.trajectory_prediction is deprecated and has no
  equivalent in the environment layer yet.
• Four modules ship with no callers (visualization/box.py, visualization/contour.py,
  scoring_rule/epsilon_logarithm_score.py, numerics/random_variables.multivariate_gmm). They
  are kept deliberately for now.