v0.9.16.dev0

latest

Use automated release tag

v0.3.2.dev0

• Fix track labels
• Set likelihood to zero not on track

v0.3.1.dev0

• Add w-track specific 1D random walk state transition
• Add random walk state transition
• Make interface more consistent with scikit-learn

v0.2.1.dev0

• Minor fix to handle the case where the GLM does not converge in the spiking model

v0.2.0.dev0

• Implement smoother, which incorporates both past and future information (feb1db0)
• Allow user to specify lfp_model, which can be any scikit-learn kernel density estimator (5309783)
• Raise NotImplemented Errors for loading and saving models (c8bcc93)
• Convert all data to numpy arrays to handle Pandas DataFrames (a4f58c0)
• Added some model checking plots (ecc8d4c)
• Remove speed from default likelihood (37a6d6a)

v0.1.8.dev0

• Fix handling of NaN
• Don't estimate the movement variance
• Fix the predict function
• Fix the default penalty and knot spacing for spiking model
• Add option to specify bin number

v0.1.7.dev0

• Make speed knot selection for replay state transition based on the data or user specified.

v0.1.6.dev0

• Fix the multiunit likelihood so that the likelihood for the current position is calculated precisely

v0.1.5.dev0

• Minor fix to handle NaN in position for the multiunit likelihood.

v0.1.4.dev0

• Fix the plot_fitted_multiunit function to handle both KernelDensity and GaussianMixture from scikit-learn.
• Make the code more efficient by eliminating some redundant computation and storage of variables.
• Minor code cleanup