distributions.Poisson

Poisson distribution implementation.

Usage

Source

distributions.Poisson()

Used to simulate number of events that occur in an interval of time. E.g. number of items in a batch.

This class conforms to the Distribution protocol.

Sources:

Law (2007 pg. 308) Simulation modelling and analysis.

Methods

Name	Description
__init__()	Initialize a Poisson distribution.
sample()	Generate random samples from the Poisson distribution.

---

__init__()

Initialize a Poisson distribution.

Usage

Source

__init__(rate, random_seed=None)

Parameters

rate: float

Mean number of events in time period.

random_seed: Optional[Union[int, SeedSequence]] = None

A random seed or SeedSequence to reproduce samples. If None, a unique sample sequence is generated.

---

sample()

Generate random samples from the Poisson distribution.

Usage

Source

sample(size=None)

Parameters

size: Optional[Union[int, Tuple[int, …]]] = None

The number/shape of samples to generate:

• If None: returns a single sample as an integer
• If int: returns a 1-D array with that many samples
• If tuple of ints: returns an array with that shape

Returns

Union[int, NDArray[np.int_]]

Random samples from the Poisson distribution:

• A single integer when size is None
• A numpy array of integers with shape determined by size parameter