kinisi-0.6.2

Changes

• Large improvements to documentation
• Moving to using the pyproject.toml
• Changing 'non-overlapping' to 'multi-origin'

kinisi-0.6.1

Changes

• Remove rogue print statement in Bootstrap method
• Improvements to documentation

kinisi-0.6.0

Changes

• Reverting to using all samples but with the minimum number of non-overlapping samples.

kinisi-0.5.1

Changes

• Fix bug in n_steps keyword argument.
• Set default number of steps to 100, based on the observation that (within reason) there was little dependence of the variance of the diffusion coefficient on the number of steps.
• Enable minimum and maximum dt values in the parser.
• Enable the use of logarithmic steps in dt.
• Some minor refactoring.
• Improvements to estimation of size of disp_3d object.
• Improvements to documentation.

kinisi-0.5.0

Changes

• Resolves the correctness bug introduces in 0.4.0 where the identification of non-overlapping samples was incorrect.
• Using hand rolled log-likelihood calculation, do to problems with the scipy.stats.multivariate_normal.pdf() method arising from changes in scipy/scipy#5288.

kinisi-0.4.0

Changes

• Previously, we had been using overlapping samples of displacements (i.e. the blue and orange observations in the figure below). However, this puts us on thin statistical ice and we were using a “fudge factor” to account for this (which in turn leads to a slightly overestimated variance in diffusion coefficient. We have changed this to only use non-overlapping samples (i.e. the blue and green observations in the figure below). This is more statistically sound and gives a more accurate estimate of the variance in the diffusion coefficient. (03a6edc)
• Removal of the parser keyword arguments min_obs and ndelta_t these were artefacts of the old overlapping sampling approach and therefore have been removed. (03a6edc)
• Now by default, the number of Δt points will reflect that in the simulation (previously there was a reduced sampling approach that has been removed). (03a6edc)
• Thinning and the ability to add a random_state to the Markov chain Monte Carlo process have been introduced (see the keyword arguments for the diffusion params, thin and random_state). (03a6edc)

kinisi-0.3.11

Changes

• Improvements to documentation (233c211)
• Add support for ions from pymatgen files (daa6e94 and 01a079a)
• Raise error if there are no species of the defined type (16ad8a8)
• Covariance matrix now only produced for max_ngp and greater (c17fef5)
• Fix off by one bug (8c5a313)
• Update to use the latest version of uravu (e8ac5e0)

kinisi-0.3.10

Changes

• Addition of save and load functionality for the Analyzer class objects
• Fix to bug that means that the diffusion coefficient would be incorrect for non-xyz systems

kinisi-0.3.9

Changes

• Improvement in stability for covariance matrix estimation
• Addition of memory limit feature to control memory exposure
• Enabling investigation of diffusion in particular dimensions or planes

kinisi-0.3.8

Changes

• Fix small bug in PymatgenParser for sub-sampled trajectories
• Improvements to the documentation