Releases: ilabcode/pyhgf
Releases · ilabcode/pyhgf
v0.0.7
What's Changed
- internal refactoring and variables naming convention by @LegrandNico in #82
- add support for categorical state nodes by @LegrandNico in #83
- add binary softmax response function by @LegrandNico in #88
- CPC tutorial and documentation by @LegrandNico in #89
Full Changelog: v0.0.6...v0.0.7
v0.0.6
What's Changed
- nodes can store additional parameters by @LegrandNico in #73
- children/parents coupling strength stored in nodes' parameter by @LegrandNico in #74
- explicit variable names in the update functions and avoid duplicating parameters by @LegrandNico in #75
- update function for multivariate descendency by @LegrandNico in #76
- plot_nodes method by @LegrandNico in #70
- support for multiple binary children by @LegrandNico in #79
- improve code coverage by @LegrandNico in #80
- v0.0.6 by @LegrandNico in #81
Full Changelog: v0.0.5...v0.0.6
v0.0.5
What's Changed
- typo by @LegrandNico in #59
- documentation on networks by @LegrandNico in #60
- restore the theory tutorial by @LegrandNico in #61
- multivariate input values for probabilistic networks by @LegrandNico in #62
- test the exact values of all parameters after node updates by @LegrandNico in #64
- value coupling to continuous parent with multiple children by @LegrandNico in #63
- remove numba from dependencies by @LegrandNico in #66
- add a second input_data method for models with time varying update sequences by @LegrandNico in #67
- add environment.yml by @LegrandNico in #68
- change numpy versions in requirements by @LegrandNico in #69
- document the use of custom response functions by @LegrandNico in #71
- v0.0.5 by @LegrandNico in #72
Full Changelog: v0.0.4...v0.0.5
v0.0.4
What's Changed
- data sience exercises by @LegrandNico in #48
- fix typo in math equation by @LegrandNico in #49
- typo by @LegrandNico in #50
- remove volatility update for continuous inputs by @LegrandNico in #53
- improve plot trajectories design by @LegrandNico in #54
- refine target for code coverage by @LegrandNico in #55
- use pre-commit for CI by @LegrandNico in #57
- add the total_gaussian_surprise response function by @LegrandNico in #56
Full Changelog: v0.0.3...v0.0.4
v0.0.3
What's Changed
- Add network plotting functionalities by @LegrandNico in #44
- use the first level surprise as the default response function by @LegrandNico in #46
- add tutorials and documentation by @LegrandNico in #45
- new version by @LegrandNico in #47
Full Changelog: v0.0.2...v0.0.3
v0.0.2
What's Changed
- v0.0.1 by @LegrandNico in #32
- packaging by @LegrandNico in #33
- cleaning and updating documentation by @LegrandNico in #34
- PIP badge in README by @LegrandNico in #35
- remove the pure Python implementation by @LegrandNico in #36
- Update docs: Replace theory part with references by @lilianAweber in #37
- Refactor package internals to handle multi parents/children situations by @LegrandNico in #39
- Use mypy's type checking in git action and pre-commit by @LegrandNico in #40
- Github action to publish on PIP automatically by @LegrandNico in #41
- TestPYPI only when tagged by @LegrandNico in #42
- v0.0.2 by @LegrandNico in #43
New Contributors
- @lilianAweber made their first contribution in #37
Full Changelog: v0.0.1...v0.0.2
v0.0.1
This is the first release of pyhgf, a Python package for nodalized, generalized and multilevel Hierarchical Gaussian Filters.
The package contains pure Python and JAX code to fit binary and continuous HGF (two-level and three-level) and tools for visualization.
The model is fully compatible with PyMC(>=5.0.0). The JAX implementation can update any node structure.
The pure Python implementation was used for development and testing and will be removed in 0.02.
The documentation can be found at: https://ilabcode.github.io/pyhgf/index.html#