NCL Website header
NCL Home > Documentation > Functions > Random number generators

random_uniform

Generates random numbers using a uniform range distribution.

Prototype

	function random_uniform (
		low  [1] : numeric,                       
		high [1] : numeric,                       
		N    [*] : byte, short, integer or long   
	)

	return_val [dimsizes(N)] :  float or double

Arguments

low

Scalar representing low bound (exclusive) on real values to be generated.

high

Scalar representing high bound (exclusive) on real values to be generated.

N

Dimensions of the multi-dimensional array to be generated.

As of version 6.0.0, N can be of type long, allowing dimension sizes greater than or equal to 2 gigabytes (GB) on 64-bit systems.

Return value

Returns an array of random numbers dimensioned the same as N.

The return type is floating point if the input is floating point, and double if the input is of type double.

Description

This function generates an array of random numbers from the range (0, 1) using a uniform distribution. If the user does not explicitly set initial values for seeds via random_setallseed, those initial seeds will be set to default values. It is recommended that the user specify these seeds. The source of this random number generator is from the random section at Netlib. The authors were Brian Brown and James Lovato. The official reference is:

Authors: P. L'Ecuyer and S. Cote
Title: Implementing a Random Number Package with Splitting Facilities
Journal: ACM Transactions on Mathematical Software 17:1, pp 98-111.

See Also

random_chi, random_gamma, random_normal, random_setallseed

Examples

Example 1

Generate random deviates:

begin
  random_setallseed(36484749, 9494848)               ; Set seeds (suggested, NOT required)
  low   = -1.0
  high  =  1.0
  unf   = random_uniform(low, high, (/10, 64, 128/)) ; uniform(10, 64, 128)

end
Example 2

Let U(18, 64, 128), and assume the user wishes to perturb these values by a max of 1%:

  random_setallseed(363738674, 918273645)   ; Set seeds (suggested, NOT required)

  low   = 0.99
  high  = 1.01
  dimU  = dimsizes(U)
  unf   = random_uniform(low, high, dimU)   ; uniform(18, 64, 128)
  U     = U * unf                           ; element by element multiply
Example 3

Generate 1000 series of length 30 with unique ordering.

  random_setallseed(363738674, 918273645)   ; Set seeds (NOT required)

  nvals = 30
  narr  = 1000

;---Generate 1000 x 30 random numbers
  r = random_uniform(0,1,(/narr,nvals/))  ; random numbers

;---Sorting the values and keeping the indexes gives us random indexes.
  indexes = dim_pqsort(r, 1)              ; use in 30 element segments

;--- concise print for illustration
  do i=0,narr-1
    str = ""
    do j=0,nvals-1
      str = str + " " + indexes(i,j)
    end do
    print("" + str)
  end do
Sample 'indexes'
(0)      15 16 22 18 23 5 21 12 3 17 0 1 8 11 9 4 20 25 28 2 13 6 27 24 19 26 14 7 29 10
(0)      1 7 25 9 21 29 8 14 20 11 16 4 5 22 19 23 12 0 27 18 28 24 15 13 26 3 6 17 2 10
(0)      14 29 4 20 18 22 27 3 24 25 0 9 28 12 6 7 1 15 26 10 23 5 21 19 13 11 17 8 2 16
(0)      28 27 1 10 2 0 5 23 4 21 18 17 22 29 13 16 11 26 6 24 15 9 19 14 25 20 3 7 12 8
(0)      20 2 12 11 22 17 25 19 15 4 16 6 18 23 9 13 8 1 27 29 5 28 3 0 14 21 7 24 26 10
(0)      4 15 25 8 10 28 16 21 26 0 14 6 27 24 18 22 7 2 13 17 11 23 9 5 19 20 29 3 12 1
(0)      2 7 0 28 10 26 24 19 13 20 29 25 17 14 23 18 27 6 3 5 1 21 16 4 15 9 22 11 12 8
(0)      17 15 11 24 27 12 14 1 22 6 9 21 5 0 29 28 23 13 3 16 25 8 26 2 20 4 19 10 18 7
(0)      3 15 27 2 6 21 17 28 16 11 18 26 13 9 24 19 5 8 12 14 7 1 20 25 23 22 0 29 10 4
[SNIP]