1.2.0 Release

Description

Added

• BestCandidateSampler: A new option in trata.adaptive_sampler that chooses new samples that add most to diversity of existing samples.
• All adaptive samples can be passed a random seed for reproducability.
• The sampling documentation notebook has been updated to include adaptive_sampler examples.
• The ProbabilityDensityFunctionSampler will automatically scale values based on ranges passed with the "box" parameter.

Changed

• Adaptive samplers use the same variable names as the rest of the modules. Only "values" for the inputs/X, and "output" for response/Y.

Bug fixes

• Updated some indexing and variable assignment methods to be compatible with numpy > 2.0
• One-at-a-time sampler has input validation and avoids duplicating default values.
• Other fixes and updates to the testing suite