Rescale vector to have specified minimum, midpoint, and maximum
Usage
rescale_mid(x, to, from, mid, ...)
# S3 method for numeric
rescale_mid(x, to = c(0, 1), from = range(x, na.rm = TRUE), mid = 0, ...)
# S3 method for logical
rescale_mid(x, to = c(0, 1), from = range(x, na.rm = TRUE), mid = 0, ...)
# S3 method for dist
rescale_mid(x, to = c(0, 1), from = range(x, na.rm = TRUE), mid = 0, ...)
# S3 method for POSIXt
rescale_mid(x, to = c(0, 1), from = range(x, na.rm = TRUE), mid, ...)
# S3 method for Date
rescale_mid(x, to = c(0, 1), from = range(x, na.rm = TRUE), mid, ...)
# S3 method for integer64
rescale_mid(x, to = c(0, 1), from = range(x, na.rm = TRUE), mid = 0, ...)
# S3 method for AsIs
rescale_mid(x, to, from, ...)Arguments
- x
vector of values to manipulate.
- to
output range (numeric vector of length two)
- from
input range (vector of length two). If not given, is calculated from the range of
x- mid
mid-point of input range
- ...
other arguments passed on to methods
Examples
rescale_mid(1:100, mid = 50.5)
#> [1] 0.00000000 0.01010101 0.02020202 0.03030303 0.04040404 0.05050505
#> [7] 0.06060606 0.07070707 0.08080808 0.09090909 0.10101010 0.11111111
#> [13] 0.12121212 0.13131313 0.14141414 0.15151515 0.16161616 0.17171717
#> [19] 0.18181818 0.19191919 0.20202020 0.21212121 0.22222222 0.23232323
#> [25] 0.24242424 0.25252525 0.26262626 0.27272727 0.28282828 0.29292929
#> [31] 0.30303030 0.31313131 0.32323232 0.33333333 0.34343434 0.35353535
#> [37] 0.36363636 0.37373737 0.38383838 0.39393939 0.40404040 0.41414141
#> [43] 0.42424242 0.43434343 0.44444444 0.45454545 0.46464646 0.47474747
#> [49] 0.48484848 0.49494949 0.50505051 0.51515152 0.52525253 0.53535354
#> [55] 0.54545455 0.55555556 0.56565657 0.57575758 0.58585859 0.59595960
#> [61] 0.60606061 0.61616162 0.62626263 0.63636364 0.64646465 0.65656566
#> [67] 0.66666667 0.67676768 0.68686869 0.69696970 0.70707071 0.71717172
#> [73] 0.72727273 0.73737374 0.74747475 0.75757576 0.76767677 0.77777778
#> [79] 0.78787879 0.79797980 0.80808081 0.81818182 0.82828283 0.83838384
#> [85] 0.84848485 0.85858586 0.86868687 0.87878788 0.88888889 0.89898990
#> [91] 0.90909091 0.91919192 0.92929293 0.93939394 0.94949495 0.95959596
#> [97] 0.96969697 0.97979798 0.98989899 1.00000000
rescale_mid(runif(50), mid = 0.5)
#> [1] 0.23858803 0.65327368 0.71839967 0.69802609 0.36260269 0.27979377
#> [7] 1.00000000 0.68695708 0.37350071 0.72178669 0.96219285 0.05953806
#> [13] 0.36927159 0.26884698 0.88423812 0.48033161 0.76443852 0.08247150
#> [19] 0.05465952 0.18195180 0.83732268 0.86786401 0.84075822 0.16917701
#> [25] 0.61216506 0.33785983 0.93354873 0.80687585 0.55009626 0.36207289
#> [31] 0.55739005 0.34216089 0.25654976 0.84739860 0.64232989 0.49987847
#> [37] 0.38892807 0.12059159 0.90258888 0.99403280 0.15757793 0.03754062
#> [43] 0.51129380 0.75840477 0.95977154 0.33097547 0.75909044 0.60844550
#> [49] 0.59325436 0.32575767
rescale_mid(1)
#> [1] 0.5