Metadata-Version: 2.1
Name: estival
Version: 0.6.0a0
Summary: A set of calibration and probabilistic programming tools for use with summerepi2
Home-page: https://github.com/monash-emu/estival
License: BSD-2-Clause
Keywords: calibration,optimization,bayesian,compartmental modelling,summerepi
Author: David Shipman
Author-email: dshipman@gmail.com
Requires-Python: >=3.8.0,<4.0.0
Classifier: License :: OSI Approved :: BSD License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Provides-Extra: nevergrad
Provides-Extra: pymc
Requires-Dist: arviz (>=0.12.1)
Requires-Dist: cloudpickle (>=2.2.1)
Requires-Dist: nevergrad (>=0.6.0) ; extra == "nevergrad"
Requires-Dist: numpy (>=1.20.3)
Requires-Dist: pymc (>=5.2.0) ; extra == "pymc"
Requires-Dist: scipy (>=1.7.3)
Requires-Dist: summerepi2 (>=1.2.6)
Requires-Dist: tensorflow-probability (>=0.9.0)
Project-URL: Documentation, https://github.com/monash-emu/estival
Project-URL: Repository, https://github.com/monash-emu/estival
Description-Content-Type: text/markdown

# estival
Calibration and optimization tools for summer2
https://github.com/monash-emu/summer2

Estival provides a simple API for using summer2 CompartmentalModels with a variety of optimization frameworks, including
- pymc
- nevergrad

### CHANGELOG

- 0.2.2  
Add logprior/logposterior to BayesianCompartmentalModel
- 0.2.3  
Include tensorflow-probability(jax) for more (and better tested) stats modules
- 0.2.4
Bugfix (vector priors were not exported to pymc correctly)
Add Epoch support to allow DatetimeIndex targets
- 0.2.5
Bugfix for BinomialTarget (wasn't indexing modelled data)
- 0.2.6
Bugfix (reference index for models without date returned incorrect type)
- 0.3.0
Note - breaking changes!
Remove old AuTuMN MCMC implementation
Move nevergrad/pymc -> wrappers
Expand likelihood output tools
Include parallelism framework
- 0.3.1
Bugfix (submodules not properly exported)
- 0.3.2
SampleIterator tools (better support for shaped priors)
Attempted map_parallel bugfix
- 0.3.3
Requirements fix (update summerepi2)
- 0.3.4
Swap modelled/target data in Normal and TruncatedNormal targets (incorrect results previously)
- 0.3.5
Add sampling utils
Add gamma prior
Support multiple targets for each derived output
- 0.3.6
Minor bugfix to 0.3.5
- 0.3.7
Reimplement BetaPrior, and get_series and finite_bounds for priors
- 0.3.8
Fix BetaPrior.to_pymc, add testing
- 0.3.9
Bugfix (BetaPrior .from_ method injected arrays into params)
- 0.4.0
Improved sampling tools
- 0.4.1
Extend sampling tools, more options for map_parallel
- 0.4.2b
Experimental release using expanded transform for uniform priors
- 0.4.3
Better exec_mode defaults for parallel helper functions
- 0.4.4
Fix issues with xarray converting array parameters
- 0.4.5
Fix nevergrad wrapper issue with infinite support priors
- 0.4.8
Improved ergonomics and sample type support
- 0.4.9
Add BetaTarget
- 0.5.0
Correct loc and iloc methods for SampleIterator
- 0.5.1
Make wrapper libraries (pymc/nevergrad) optional extras
- 0.5.2
Add NormalPrior
- 0.6.0
Add hierarchical priors for PyMC
