0.1.6

Installation

conda install -c aportnoy fitgrid

or

pip install -U fitgrid

Features

• new lmer fitting routine that allows for visual model comparison based on AIC
• grids can now be saved to files and loaded from files using grid.save and fitgrid.load_grid
• additional parameters now available in epochs.lmer: REML/ML, confidence interval types, etc.

Bug fixes

• exorbitant memory usage slightly mitigated by removing a number of attributes from lmer fit objects
• missing lmer correctness tests now added

Other

• fitgrid is now available from conda: run conda install -c aportnoy fitgrid
• Travis tests are now run using conda
• slight structure reorganization

0.1.5

Bug fixes

• fix stupid bug where lmer did not use specified channels

0.1.4

Bug fixes

• add option to plot legend separately in plot_betas, otherwise we fail miserably with many betas
• guard against duplicate channels in Epochs and FitGrid's, also when slicing FitGrid's
• fix issue with plot_betas used on a grid with a single channel
• add colorscale to plot_betas

0.1.3

Features

• Add multicore processing, made possible by making NumPy single-threaded
• Add support for full linear mixed models using lme4, replacing statsmodels

Bug fixes

• Use all channels by default in run_model
• Fix formatting of duplicate epoch indices error message

Other

• Model running is now done sample by sample instead of channel by channel
• Correctness tests for lm added

0.1.2

Features

• Add support for mixed models to the extent allowed by statsmodels
• Add Epochs.distances, a function assigning distances from the "mean epoch" to all epochs. This allows for preliminary outlier rejection.

Bug fixes

• Fix bad _snapshots access using get_group (#38)

Other

• Private Epochs attributes are prefixed with _ to get them out of the way of the user.
• Refactor LHS and RHS validation (DRY).

0.1.1

Features

• Helpful message on duplicate indices (suggested by Melissa)
• run_model function in Epochs allowing for running arbitrary models
• One shot R^2 plot with marginal subplots
• Averages plotted negative up by default to respect the convention
• Add correct epoch id resolution for returned dataframes, this matters when we get bare arrays from statsmodels
• Both Epochs and FitGrid are channel aware (have a channels attribute tracking what channels they have)

Bug fixes

• Font sizes for the plots are changed using context managers so the changes are contained
• table inside epochs is now a copy not a reference to the original
• Use Agg matplotlib backend to prevent fatal erros when $DISPLAY is not set
• Copy when creating smaller grids on slicing

Other

• Add API reference to docs
• Trimmed down dependencies
• Better test coverage
• Clearer example in demo notebook