chains argument in
redist_flip().redist_shortburst() along with the new features. The
following issues are fixed:
redist_plans object would store the wrong
score for the ‘stop_at was
specified and minimize = FALSE. (#181)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.redistmetrics package.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").redist.mcmc(), which was replaced by
redist.flip() a few years ago, and finally
redist_flip().redist_ci interface for confidence interval
calculationredist.plot.distr_qtys()
for custom geometry types.redist_constr() and
?constraints). For the first time, user-defined custom
constraints are supported and integrated within all three
algorithms.summary.redist_plans()redistmetrics package This will speed up compilation time
and also provides a cleaner, more extensible interface for the
implementation of additional metrics.doRNGmatch_numbers() using the Hungarian
methodmin_move_parity() calculates how much population needs
to be moved between districts in order to completely balance a
redistricting plan.cli errors and warnings throughout the packageredist.splits()color_graph()redist_mergesplit_parallel()rbind() generic for redist_plans
objectsredist.smc() in favor of
redist_smc() and redist.mergesplit() in favor
of redist_mergesplit(). # redist 3.0.2redist_map and
redist_plans objectsredist_mergesplit()redist_shortburst() along with scoring functions
(?scorers)compare_plans()
and classify_plans()iowa dataset and cleaned-up package dataredist.subset allows for easy subsetting of an
adjacency graphNEWS.md file to track changes to the
package
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