This function creates a new DemandPoints object
DemandPoints(coords, weights)base::matrix() of coordinates for each demand point.
numeric weights for each demand point.
A new DemandPoints object.
# \dontrun{
# make demand points
dps <- DemandPoints(
matrix(rnorm(100), ncol=2),
runif(50)
)
# print object
print(dps)
#> An object of class "DemandPoints"
#> Slot "coords":
#> [,1] [,2]
#> [1,] 0.416942847 -0.10921759
#> [2,] -0.632587542 0.26466174
#> [3,] 1.150146673 0.30384826
#> [4,] -0.235475907 -0.18338848
#> [5,] -1.643107386 0.55964967
#> [6,] -1.503382146 -0.18655384
#> [7,] -2.050584847 -0.81227537
#> [8,] -0.753198229 -1.64058167
#> [9,] -0.134141958 0.50792248
#> [10,] 1.005782847 1.75433696
#> [11,] 2.167186798 0.59240020
#> [12,] 2.322556540 1.01671329
#> [13,] -1.020423391 0.12162059
#> [14,] 0.048814436 -1.07806726
#> [15,] -0.771888628 -1.14356572
#> [16,] -0.785235068 -0.52964368
#> [17,] -0.726603031 -0.68127316
#> [18,] 0.681878032 -0.20244756
#> [19,] -0.229843287 1.68449572
#> [20,] -1.510601724 -1.03377324
#> [21,] -0.583727687 -0.15597667
#> [22,] -2.022918454 -0.04640064
#> [23,] 0.403504676 -0.95362873
#> [24,] 0.550015549 0.41626080
#> [25,] 0.028357122 0.11402961
#> [26,] 0.893165020 0.06391875
#> [27,] -0.376555496 -0.91933224
#> [28,] 0.605884808 0.90133529
#> [29,] -0.004874726 -0.79772830
#> [30,] -0.520796373 0.66822120
#> [31,] -0.639018598 0.15521430
#> [32,] -0.635894137 0.12868809
#> [33,] 0.106586975 -1.53306545
#> [34,] 1.176914248 0.20236067
#> [35,] 0.447391153 -0.71753865
#> [36,] 2.272954766 0.36169476
#> [37,] 0.136058206 1.39900429
#> [38,] -1.999039133 0.37269896
#> [39,] -0.420500870 -1.56564429
#> [40,] -0.378407395 -0.05169454
#> [41,] 1.220774789 0.51408210
#> [42,] -1.541030292 0.54989952
#> [43,] -0.310310122 0.86781691
#> [44,] -0.020108184 0.68436008
#> [45,] -2.390200336 -0.16267998
#> [46,] 0.889865359 -1.78436472
#> [47,] -1.482813325 -1.03714557
#> [48,] 0.445750348 0.83014772
#> [49,] 1.369775856 0.60734694
#> [50,] -0.020110027 -0.12218636
#>
#> Slot "weights":
#> [1] 0.82462233 0.20905156 0.16820653 0.98027422 0.60067001 0.15167630
#> [7] 0.29273868 0.44806062 0.82390783 0.96940433 0.29540916 0.23268974
#> [13] 0.32548104 0.10037212 0.33022536 0.19259870 0.26887364 0.88352934
#> [19] 0.67062316 0.07432107 0.68530920 0.60081559 0.70614048 0.46816601
#> [25] 0.01098793 0.78329569 0.62185330 0.86605874 0.91985234 0.32539892
#> [31] 0.91576207 0.08054491 0.85551768 0.30502898 0.73636304 0.94096257
#> [37] 0.86102324 0.36417012 0.91252348 0.75292220 0.64148241 0.79545033
#> [43] 0.98497173 0.62236924 0.55532649 0.96106650 0.91563972 0.60327560
#> [49] 0.31155411 0.55515212
#>
# }