viprs 0.1.3 on Python PyPI

Fixed bugs in VIPRSGridSearch and VIPRSBMA models, specifically how they were handling _log_var_tau,
and the hyperparameters objects after selecting best models or performing model averaging.
Fixed bug in how viprs_fit handles validation gdls when the user passes genotype data.
Updated interfaces in HyperparameterSearch script to make it more flexible and efficient. Primarily,
I added shared memory object for the LD matrix to avoid redundant memory usage when fitting multiple
models in parallel. (** WORK IN PROGRESS **).
Updated implementation of pseudo_r2 to use square of pseudo correlation coefficient instead. The previous
implementation can be problematic with highly sparsified LD matrices.
Updated implementation of VIPRSGrid to be better integrated with the VIPRS class. The new implementation
also allows for fitting the grid in a pathwise fashion (now default behavior), where we use
parameter estimates from previous grid points as warm-start initialization for the current grid point.
Removed VIPRSGridSearch and VIPRSBMA classes for now. These functions are implemented in grid_utils.py instead
and they can be applied generically to any VIPRSGrid model.

Added viprs-cli-example.ipynb notebook to demonstrate how to use the viprs commandline interface.
Added documentation page for Downloading LD matrices.
Added new utility function combine_coefficient_tables to combine the output from multiple VIPRS models.
Added more thorough tests for the various models + CLI scripts.
Added PeakMemoryProfiler to viprs_fit to more accurately track peak memory usage. Temporary solution,
this will be moved to magenpy later on.
Added support for splitting GWAS sumstats to training/validation sets and exposed appropriate interfaces
in the base class BayesPRSModel.
Added IterationConditionCounter class to keep track of the number of consecutive iterations
where a certain condition is met. This is used to monitors convergence of the optimization routine.

viprs 0.1.3 v0.1.3 on Python PyPI