Coyote Graphics Routines

Date: Fri Mar 27 12:14:20 2015

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top cgRandomWald


result = cgRandomWald( [seed] [, dims] [, MU=double] [, LAMBDA=double])

This function creates a vector of N random numbers using an Inverse Gaussian Distribution, which is also known as the Wald Distribution. The reference for the code can be found at


seed in optional

The seed for the random number generator. If undefined, on output will have the seed used by the IDL RandomU function. See the documentation for RandomU for additional information.

dims in optional type=integer

A scalar or integer array defining the dimensions of the result. If no dimensions are specified, a single random number is returned. If Dims is a scalar, a 1D vector of that number of values will be returned.


MU in optional type=double default=1.0

The mean of the distribution.

LAMBDA in optional type=double default=1.0

The shape parameter of the distribution. As lambda tends to infinity, the inverse distribution becomes more like a normal distribution.


For example, to create 100 random numbers, using the Wald distribution:

wald = cgRandomWald(seed, 100)
To create a 20-column by 10-row array of random numbers:
wald = cgRandoWald(seed, [20,10])

Author information



David W. Fanning 1645 Sheely Drive Fort Collins, CO 80526 USA Phone: 970-221-0438 E-mail: Coyote's Guide to IDL Programming:


Copyright (c) 2012, Fanning Software Consulting, Inc.


Written, 25 Oct 2012, by David W. Fanning.

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