distributions.Triangular

Triangular distribution implementation.

Usage

Source

distributions.Triangular()

A continuous probability distribution with lower limit, upper limit, and mode, forming a triangular-shaped probability density function.

This class conforms to the Distribution protocol and provides methods to sample from a triangular distribution with specified parameters.

Methods

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

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__init__()

Initialize a triangular distribution.

Usage

Source

__init__(low, mode, high, random_seed=None)

Parameters

low: float

Lower limit of the distribution.

mode: float

Mode (peak) of the distribution. Must be between low and high.

high: float

Upper limit of the distribution.

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

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

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sample()

Generate random samples from the triangular 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 a float
• If int: returns a 1-D array with that many samples
• If tuple of ints: returns an array with that shape

Returns

Union[float, NDArray[np.float64]]

Random samples from the triangular distribution:

• A single float when size is None
• A numpy array of floats with shape determined by size parameter