Generate random numbers from various distributions.
If you use NPM, npm install d3-random. Otherwise, download the latest release. You can also load directly from d3js.org, either as a standalone library or as part of D3 4.0. AMD, CommonJS, and vanilla environments are supported. In vanilla, a d3 global is exported:
<script src="https://d3js.org/d3-random.v1.min.js"></script>
<script>
var random = d3.randomUniform(1, 10);
</script>Try d3-random in your browser.
# d3.randomUniform([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:
d3.randomUniform(6)(); // Returns a number greater than or equal to 0 and less than 6.
d3.randomUniform(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.
# d3.randomNormal([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.
# d3.randomLogNormal([mu][, sigma]) <>
Returns a function for generating random numbers with a log-normal distribution. The expected value of the random variable’s natural logarithm 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.
Returns a function for generating random numbers with a Bates distribution with n independent variables.
Returns a function for generating random numbers with an Irwin–Hall distribution with n independent variables.
# d3.randomExponential(lambda) <>
Returns a function for generating random numbers with an exponential distribution with the rate lambda; equivalent to time between events in a Poisson process with a mean of 1 / lambda. For example, exponential(1/40) generates random times between events where, on average, one event occurs every 40 units of time.
# random.source(source)
Returns the same type of function for generating random numbers but where the given random number generator source is used as the source of randomness instead of Math.random. The given random number generator must implement the same interface as Math.random and only return values in the range [0, 1). This is useful when a seeded random number generator is preferable to Math.random. For example:
var d3 = require("d3-random"),
seedrandom = require("seedrandom"),
random = d3.randomNormal.source(seedrandom("a22ebc7c488a3a47"))(0, 1);
random(); // 0.9744193494813501