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,] 1.47073203 -1.258018766
#> [2,] 0.33366123 -1.332680870
#> [3,] 1.13611968 -0.832239487
#> [4,] 1.17919925 -1.353292397
#> [5,] 0.63157306 -0.393176375
#> [6,] -1.88270851 1.171874830
#> [7,] 0.18757829 -0.006887564
#> [8,] 1.12796118 1.284925119
#> [9,] 0.53471390 -1.025075340
#> [10,] -0.82085270 0.227347974
#> [11,] 1.17541526 0.495358342
#> [12,] 0.35879898 -1.524380509
#> [13,] -0.13852087 0.217900158
#> [14,] -0.63629149 0.704308207
#> [15,] -0.57720226 -0.751992375
#> [16,] -1.18694775 0.785776414
#> [17,] -1.36514061 -0.055205115
#> [18,] -0.16790986 -0.414880583
#> [19,] 0.57037504 -0.184065453
#> [20,] -0.01518033 -0.810975339
#> [21,] -2.03234214 -1.566672264
#> [22,] 1.87315052 -0.392646716
#> [23,] 0.38788201 0.004858200
#> [24,] 1.10628317 0.965011766
#> [25,] 0.63434750 -1.312012816
#> [26,] 0.51302944 -1.918013703
#> [27,] -0.16015063 0.093832010
#> [28,] 0.56062405 -1.076149483
#> [29,] 0.20452969 2.200127302
#> [30,] -0.17630018 -0.005071820
#> [31,] -1.16687235 -1.602550243
#> [32,] -0.87506108 -0.003713870
#> [33,] 0.40671129 1.940001439
#> [34,] -0.61199550 0.232542318
#> [35,] -0.94199232 -0.653319147
#> [36,] 0.75895377 0.511247243
#> [37,] -1.43957235 1.790971027
#> [38,] -0.46082657 -0.602038436
#> [39,] 1.25034476 -2.060321384
#> [40,] 0.33285069 -1.543311814
#> [41,] -1.58280576 -0.050266381
#> [42,] -0.38496189 0.774456939
#> [43,] -0.66045568 1.378186654
#> [44,] 0.85612181 -2.024294882
#> [45,] 0.03994205 -0.350415784
#> [46,] -2.28752220 -0.521105521
#> [47,] -0.47208936 0.118951478
#> [48,] 1.55625271 -0.036027174
#> [49,] 1.15045509 1.214186053
#> [50,] -0.45332157 -0.380823535
#>
#> Slot "weights":
#> [1] 0.02721305 0.48958724 0.99499331 0.93060837 0.46788487 0.29207875
#> [7] 0.41057292 0.15333049 0.49687816 0.37071024 0.70375219 0.95706132
#> [13] 0.67041750 0.53405550 0.92381556 0.46644003 0.98437345 0.21427925
#> [19] 0.04642168 0.19822015 0.58173241 0.39944537 0.95886370 0.23000955
#> [25] 0.11466910 0.03061763 0.72477981 0.15822648 0.78181034 0.57540717
#> [31] 0.44643628 0.11877352 0.68460706 0.61563837 0.67630997 0.39455456
#> [37] 0.48096725 0.30485306 0.23352605 0.27429248 0.70524684 0.09099607
#> [43] 0.05443510 0.90300795 0.38210081 0.05637002 0.25011004 0.89465186
#> [49] 0.22081772 0.68882898
#>
# }