Create Weighted Adjacency Data
redist.wted.adj(map = NULL, plans = NULL)redist_map
redist_plans
tibble
data(iowa)
shp <- redist_map(iowa, existing_plan = cd_2010, pop_tol = 0.01)
plans <- redist_smc(shp, 100)
#> SEQUENTIAL MONTE CARLO
#> Sampling 100 99-unit maps with 4 districts and population between 753973 and 769205.
#> Split [0/3] ■ | ETA?
#> Split [3/3] ■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■■ | ETA 0s
#>
redist.wted.adj(shp, plans = plans)
#> Simple feature collection with 222 features and 3 fields
#> Geometry type: LINESTRING
#> Dimension: XY
#> Bounding box: xmin: 4192376 ymin: 2974708 xmax: 5729102 ymax: 3978011
#> Projected CRS: NAD83(HARN) / Iowa North (ftUS)
#> # A tibble: 222 × 4
#> # Rowwise:
#> i j geometry wt
#> * <int> <int> <LINESTRING [US_survey_foot]> <dbl>
#> 1 1 2 (4654501 3220689, 4590239 3111565) 0.88
#> 2 1 15 (4654501 3220689, 4529015 3222722) 0.84
#> 3 1 39 (4654501 3220689, 4647780 3349436) 0.76
#> 4 1 61 (4654501 3220689, 4779626 3219592) 0.67
#> 5 1 88 (4654501 3220689, 4716357 3109639) 0.66
#> 6 2 15 (4590239 3111565, 4529015 3222722) 0.88
#> 7 2 69 (4590239 3111565, 4464101 3114115) 0.9
#> 8 2 87 (4590239 3111565, 4589159 3005137) 0.79
#> 9 2 88 (4590239 3111565, 4716357 3109639) 0.71
#> 10 3 22 (5486111 3937993, 5500145 3778167) 0.93
#> # ℹ 212 more rows