Rescale vector to have specified minimum, midpoint, and maximum.

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, ...)

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] 0.566923663 0.898159943 0.594491877 0.831758720 0.593427740 0.779028499 #> [7] 0.397750442 0.849955349 0.741895746 0.317752424 0.111599676 0.101012622 #> [13] 0.800159996 0.379921840 0.052608190 0.986609612 0.604195575 0.148709871 #> [19] 0.538768212 0.125711606 0.963277829 0.046841037 0.161338950 0.936577965 #> [25] 0.970778994 0.710317669 0.885170808 0.976974233 0.034803170 0.438744566 #> [31] 0.644499727 0.994935046 0.314624177 0.855955785 0.540346049 0.873494809 #> [37] 0.515588852 0.869535933 0.856596547 0.345651175 0.000000000 0.205118592 #> [43] 0.945312841 0.281288156 0.881013233 0.961211924 0.003915575 0.552911178 #> [49] 0.219177735 0.646757578
rescale_mid(1)
#> [1] 0.5