Given a random number generator, (rng), generating numbers in the range 0.0 .. 1.0 called rgen, for example; and a function modifier(x)
taking an number in the same range and generating the probability that the input should be generated, in the same range 0..1; then implement the following algorithm for generating random numbers to the probability given by function modifier:

while True:
    random1 = rgen()
    random2 = rgen()
    if random2 < modifier(random1):
        answer = random1
        break
    endif
endwhile
Task

 Create a modifier function that generates a 'V' shaped probability of number generation using something like, for example:
                      modifier(x)  =  2*(0.5 - x)  if x < 0.5  else 2*(x - 0.5) 

 Create a generator of random numbers with probabilities modified by the above function.
 Generate >= 10,000 random numbers subject to the probability modification.
 Output a textual histogram with from 11 to 21 bins showing the distribution of the random numbers generated.


Show your output here, on this page.




library(NostalgiR) #For the textual histogram.
modifier <- function(x) 2*abs(x - 0.5)
gen <- function()
{
  repeat
  {
    random <- runif(2)
    if(random[2] < modifier(random[1])) return(random[1])
  } 
}
data <- replicate(100000, gen())
NostalgiR::nos.hist(data, breaks = 20, pch = "#")