Random
Functions and reducers to generate random samples from common probability distributions.
For random generators implemented as reducers (normal, poisson), note that they cannot be called from function context, but only from stream context. Random generators provided as functions can be called in either context.
exponential - function
Generates random numbers following the exponential distribution.
Callable from function or stream context.
Returns x ~ Exp(scale).
... | put value=random.exponential(2) | ...
| Argument | Description | |
|---|---|---|
scale |
1 / lambda, where lambda is the rate parameter |
normal - reducer
Generates random numbers following the normal, or Gaussian, distribution. Uses Marsaglia polar method (improved Box-Muller transform) for the computation.
Callable only from stream context.
Returns x ~ N(loc, scale).
... | put x = random.normal(0,Math.sqrt(0.2)), y = random.normal(0, 1) | ...
| Options | Description | |
|---|---|---|
loc |
mean | |
scale |
standard deviation |
poisson - reducer
Generates random Poisson-distributed numbers that represent the number of event occurrences per interval (therefore, this generator outputs whole nonnegative integers). Uses Knuth's algorithm for the computation.
Callable only from stream context.
Returns x ~ Poisson(lam).
... | put lambda_1=random.poisson(1) | ...
| Options | Description | |
|---|---|---|
lam |
rate parameter, defining the average number of events in an interval, should be >= 0 |
uniform - function
Generates random numbers between the low and high bound
arguments, following uniform distribution.
Callable from function or stream context.
Returns x ~ U(low..high).
... | put value=uniform(0, 24)
| Options | Description | |
|---|---|---|
low |
lower bound | |
high |
upper bound |