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Major Changes:
multidms.fit_models
for the ability to fit multiple models across a range of parameter spaces in parallel usingmultiprocessing
. This is inspired by thepolyclonal.fit_models
function.ModelCollection
class for split-apply-combine interface to the mutational dataframes for a collection of modelsModelCollection
. (1)mut_param_heatmap
for visualizing aggregated parameter sets across fits, and (2)mut_param_traceplot
making trace plots across fits with variable lasso coeff strengthsTo do:
multidms.plot.mut_shift_plot
into a method ofModelCollection
for querying and visualizing aggregated groups of the collectionModelCollection
class. this could be both trace "lines" for comparison of continuous hyper-parameters like lasso penalty coeff, as well as boxplots for sets of fits with unordered hyperparameters (different non-linearities, perhaps?)Questions:
Other Minor changes:
utils
module.ipywidgets
#114Model.get_mutations_df
. Those were unnecessary IMOModel.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".