A friend of mine runs a pharmacy.   He has a specialized function in his Dispensary application which receives a decimal value of currency and replaces it to a standard value.   This value is regulated by a government department.



Task

Given a floating point value between   0.00   and   1.00,   rescale according to the following table:

>=  0.00  <  0.06  :=  0.10
>=  0.06  <  0.11  :=  0.18
>=  0.11  <  0.16  :=  0.26
>=  0.16  <  0.21  :=  0.32
>=  0.21  <  0.26  :=  0.38
>=  0.26  <  0.31  :=  0.44
>=  0.31  <  0.36  :=  0.50
>=  0.36  <  0.41  :=  0.54
>=  0.41  <  0.46  :=  0.58
>=  0.46  <  0.51  :=  0.62
>=  0.51  <  0.56  :=  0.66
>=  0.56  <  0.61  :=  0.70
>=  0.61  <  0.66  :=  0.74
>=  0.66  <  0.71  :=  0.78
>=  0.71  <  0.76  :=  0.82
>=  0.76  <  0.81  :=  0.86
>=  0.81  <  0.86  :=  0.90
>=  0.86  <  0.91  :=  0.94
>=  0.91  <  0.96  :=  0.98
>=  0.96  <  1.01  :=  1.00



 
price_fraction <- function(x)
{
  stopifnot(all(x >= 0 & x <= 1))
  breaks <- seq(0.06, 1.01, 0.05)
  values <- c(.1, .18, .26, .32, .38, .44, .5, .54, .58, .62, .66, .7, .74, .78, .82, .86, .9, .94, .98, 1)
  indices <- sapply(x, function(x) which(x < breaks)[1])
  values[indices]
}
 
#Example usage:
price_fraction(c(0, .01, 0.06, 0.25, 1))                # 0.10 0.10 0.18 0.38 1.00
 