v0.3.0

New release with some significant documentation improvements and bug fixes. Changes in this release:

• New documentation with more specific installation instructions
• New documentation page with talk from Firedrake '21 conference
• Bug fixes to assemble.py and license information in setup.py

v0.2.0

Second release of the stat-fem code base. The release implements a number of improvements and fixes from the first release, including the following:

• LinearSolver and other routines involving a solver can now accept keyword arguments to control the PETSc solver method and options. These are the same as the Firedrake options, so should enable straightforward integration between the two code bases.
• A bug fix in the LinearSolver class has been implemented to ensure that the gradient of the log-posterior is correctly computed.
• More transparency has been provided on how the mean of the solver output is scaled by providing a boolean scale_mean keyword argument that determines if the mean should be scaled by the model discrepancy scaling factor. By default, posterior solves do not scale the mean, while predictions do scale the mean, to maintain consistency with the previous behavior.
• Improved documentation, including full docstrings for all functions and arguments, as well as a page on ensemble parallelism in the docs.

v0.1.0

First release of the stat-fem library. Implements the method and provides documentation and an example.

New Features in this Release:

• Implements the base classes for the ForcingCovariance, InterpolationMatrix, ObsData, and LinearSolver to implement the method
• Utility functions to do the heavy lifting in the solves and compute covariance functions
• Standalone functions for all solves
• A MAP estimation routine
• Full unit tests
• A working example based on Poisson's equation
• Documentation
• A docker image based on the Firedrake image to make installation easier