Generate random numbers from various distributions.

If you use NPM, npm install d3-random. Otherwise, download the latest release.

# uniform([min, ][max])

Returns a function for generating random numbers with a uniform distribution. The minimum allowed value of a returned number is min, and the maximum is max. If min is not specified, it defaults to 0; if max is not specified, it defaults to 1. For example:

uniform(6)(); // Returns a number greater than or equal to 0 and less than 6.
uniform(1, 5)(); // Returns a number greater than or equal to 1 and less than 5.

Note that you can also use the built-in Math.random to generate uniform distributions directly. For example, to generate a random integer between 0 and 99 (inclusive), you can say Math.random() * 100 | 0.

# normal([mu][, sigma])

Returns a function for generating random numbers with a normal (Gaussian) distribution. The expected value of the generated numbers is mu, with the given standard deviation sigma. If mu is not specified, it defaults to 0; if sigma is not specified, it defaults to 1.

# logNormal([mu][, sigma])

Returns a function for generating random numbers with a log-normal distribution. The expected value of the random variable’s natural logrithm is mu, with the given standard deviation sigma. If mu is not specified, it defaults to 0; if sigma is not specified, it defaults to 1.

# bates(n)

Returns a function for generating random numbers with a Bates distribution with n independent variables.

# irwinHall(n)

Returns a function for generating random numbers with an Irwin–Hall distribution with n independent variables.

# exponential(lambda)

Returns a function for generating random numbers with an exponential distribution with a mean of 1/lambda. Equivalent of intervals in a Poisson process.

Example: exponential(1/40) will generate random times for a Poisson random event that occurs an average of once every 40 units of time.

• Added a uniform random number generator.