Changelog

All notable changes to this project will be documented in this file.

The format is based on Keep a Changelog.

1.1.0

• No longer calling transform() on parameters for single condition fits. See #160.

• Added init_beta_variance parameter to the Model instantiation to allow the user to initialize beta parameters by sampling a normal distribution. See #161.

1.0.0

• This release re-implements the joint model as a using a generalized lasso, and bit-flipping, as described in #156. Please see the issue for more detailed description about how, and why these changes were made. Note that this changes the parameters that one may get from the model including a set of beta’s for each experimental condition.

• It also cleans up various TODO’s in the code as checked-off in #153 <https://github.com/matsengrp/multidms/issues/153>.

• Fixes a bug, where the phenotype predictions for single mutants did not correctly include the bundle effects.

• Fixes and cleans various plotting bugs.

0.4.0

• new simulation validation analysis and plotting functions (at the time of re-submission)

• fixes bug described in `#130 https://github.com/matsengrp/multidms/issues/130`_, having to do with pandas groupby.apply 2.2.0 behavior change.

• updates python version requirements to 3.9 or newer, as 3.8 did not work with the new pandas version, 2.2.0 bug patch described above.

• supresses the cpu warning from jax.

• adds ModelCollection.add_validation_loss, ModelCollection.get_conditional_loss_df, Model.conditional_loss, and Model.get_df_loss methods, which can all be used quite easily to perform cross validation analysis.

0.3.3

• simply updates the ruff linting to version 0.0.289

0.3.2

• fixes bug #128

0.3.1

• fixes bug #126.

• Adds the initial working simulation notebook.

0.3.0

• Adds initial multidms.model_collection module with multidms.fit_models for the ability to fit multiple models across a range of parameter spaces in parallel using multiprocessing. This is inspired by the polyclonal.fit_models function.

• Adds the ModelCollection class for split-apply-combine interface to the mutational dataframes for a collection of models

• Adds four altair plotting methods to ModelCollection: mut_param_heatmap, shift_sparsity, mut_param_dataset_correlation, and mut_param_traceplot.

• removes utils module.

• Cleans up #114

• optionally removes “wts”, “sites”, “muts” from the mutations dataframe returned by Model.get_mutations_df.

• Changes the naming of columns produced by Model.get_mutations_df(), in particular, it moves the condition name for predicted func score to be a suffix (as with shift, and time_seen) rather than a prefix. e.g. “delta_predicted_func_score” -> “predicted_func_score_delta”.

0.2.2

• Fixed a bug

  caused by non-unique indices in input variant functional score dataframes.

0.2.1

• Made lineplot_and_heatmap() more private to remove from docs.

• Fixed bug pointed out by @jbloom #110

• Model.get_mutations_df() now sets the mutation as the index

• added some testing utils

0.2.0

• Closed a docs testing issue, thanks, @WSDeWitt !

• Cleaned Actions, again thanks to @WSDeWitt

• Fixed a bug in wildtype predictions

• Implemented QC on invalid bundle muts as pointed out by @Haddox.

• a few other minor cleanup tasks.

0.1.9

• First Release on PYPI