NEWS

redist 4.3.0

Improves SMC performance by pre-allocating some memory while drawing spanning trees.
Replaces SMC label-counting adjustments (exact and importance-sampling-based) with a new backward kernel that eliminates approximation error and requires far less computation
4.2.0 introduced some regressions in redist_shortburst() along with the new features. The following issues are fixed:
- the returned redist_plans object would store the wrong score for the '' input. This issue only impacted the returned object and the correct score was used during the shortburst process. (#180)
- the function would return immediately if stop_at was specified and minimize = FALSE. (#181)
Add summary() support for plans sampled with the flip algorithm. This does not replace the full flip diagnostic suite, but provides an easy way to compute r-hats.

Deprecate functionality that is provided by redistmetrics package.
Improve contiguity checking speed drastically.
Support for multiple independent scoring functions in redist_shortburst(). With multiple scorers, the algorithm will stochastically explore to try to find the largest Pareto frontier for the scores. The frontier can be accessed with attr(<plans obj>, "pareto_score").
Removes the MPI vignette which relied on older implementations of redist.mcmc(), which was replaced by redist.flip() a few years ago, and finally redist_flip().

Improved diagnostic output
New redist_ci interface for confidence interval calculation
Improved plotting options with redist.plot.distr_qtys() for custom geometry types.
Improved resampling efficiency at the final SMC stage
Faster implementation of loop-erased random walk in C++
Faster random number generation in C++
Updated citation information

A new constraint interface that is more flexible, user friendly, and consistent across algorithms (see redist_constr() and ?constraints). For the first time, user-defined custom constraints are supported and integrated within all three algorithms.
New diagnostic-checking function, summary.redist_plans()
Summary statistics have been broken out into a new redistmetrics package This will speed up compilation time and also provides a cleaner, more extensible interface for the implementation of additional metrics.
Parallel computing support for the SMC algorithm, both within and across sampling runs
Reproducible across-run parallelism throughout the package, via doRNG
Much faster match_numbers() using the Hungarian method
min_move_parity() calculates how much population needs to be moved between districts in order to completely balance a redistricting plan.
Support for partial SMC simulations, where fewer districts are drawn than the total number. Allows advanced users to manually combine partial runs to form complete maps.
Improved algorithm reporting, including new progress bars and cli errors and warnings throughout the package
Update the SMC algorithm to include a missing correction factor for the number of ways to sequentially label districts. This factor should not have an effect on substantive conclusions and summary statistics.
Remove deprecated functions
Many bug fixes (see https://github.com/alarm-redist/redist/issues)

Removes prior deprecated functions and arguments
Fix bugs (#78, #81, #86)
Introduces redist_mergesplit_parallel()
Adds rbind() generic for redist_plans objects
Improves sampling speed for SMC and Merge-split with county constraint
Adds county split measures.
Adds population overlap measures for plan comparisons.
Deprecates redist.smc() in favor of redist_smc() and redist.mergesplit() in favor of redist_mergesplit().

Fix bugs (#60, #61, #62, #70, #71, #72), including s2 compatibility, Solaris fixes, and improved dplyr verb robustness.

New tidy interface, including new redist_map and redist_plans objects
Merge-split MCMC now available in redist_mergesplit()
Short burst MCMC optimization now available in redist_shortburst() along with scoring functions (?scorers)
Improved Flip MCMC interface and performance improvements
New support for larger simulation size limits
Functions to freeze parts of a map and extract district cores
New VRA constraint
Many new plotting functions
Consistent function and argument names
New partisanship and compactness metrics
Performance improvements to compactness calculations
Plan comparison and classification in compare_plans() and classify_plans()
New iowa dataset and cleaned-up package data
New vignettes for redistricting analysis and workflows
Various bug fixes