comp_schwartz

Calculate Schwartzberg Compactness

Reliable and flexible tools for scoring redistricting plans using
common measures and metrics. These functions provide key direct access to
tools useful for non-simulation analyses of redistricting plans, such as for
measuring compactness or partisan fairness. Tools are designed to work with
the 'redist' package seamlessly.

Christopher T. Kenny

redistmetrics

Redistricting Metrics

Cory McCartan

Ben Fifield

Kosuke Imai

comp_schwartz function

<dl><dt>plans</dt>
<dd>A <code>redist_plans</code> object or plans_matrix where each row indicates a district assignment and each column is a plan.</dd>
<dt>shp</dt>
<dd>A <code>redist_map</code> object, tibble, or data frame with an <code>sf</code> geometry column.</dd>
<dt>use_Rcpp</dt>
<dd>Logical. Use Rcpp?</dd>
<dt>perim_path</dt>
<dd>path to perimeter tibble saved by <code>prep_perims()</code></dd>
<dt>perim_df</dt>
<dd>tibble of perimeters from <code>prep_perims()</code></dd>
<dt>epsg</dt>
<dd>Numeric EPSG code to use to project the shapefile, if needed. Default is 3857.</dd>
<dt>ncores</dt>
<dd>Integer number of cores to use. Default is 1.</dd></dl>

Arguments

Calculate Schwartzberg Compactness — comp_schwartz

<dl>

<dt>plans</dt>
<dd>A <code>redist_plans</code> object or plans_matrix where each row indicates a district assignment and each column is a plan.</dd>


<dt>shp</dt>
<dd>A <code>redist_map</code> object, tibble, or data frame with an <code>sf</code> geometry column.</dd>


<dt>use_Rcpp</dt>
<dd>Logical. Use Rcpp?</dd>


<dt>perim_path</dt>
<dd>path to perimeter tibble saved by <code>prep_perims()</code></dd>


<dt>perim_df</dt>
<dd>tibble of perimeters from <code>prep_perims()</code></dd>


<dt>epsg</dt>
<dd>Numeric EPSG code to use to project the shapefile, if needed. Default is 3857.</dd>


<dt>ncores</dt>
<dd>Integer number of cores to use. Default is 1.</dd>

</dl>

comp_schwartz: Calculate Schwartzberg Compactness

Description

Usage

Value

Arguments

References

Examples