## distributions.Bernoulli


Bernoulli distribution implementation.


Usage

``` python
distributions.Bernoulli(
    p,
    random_seed=None,
)
```


A discrete probability distribution that takes value 1 with probability p and value 0 with probability 1-p.

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


## Methods

| Name | Description |
|----|----|
| [__init__()](#__init__) | Initialize a Bernoulli distribution. |
| [sample()](#sample) | Generate random samples from the Bernoulli distribution. |

------------------------------------------------------------------------


#### \_\_init\_\_()


Initialize a Bernoulli distribution.


Usage

``` python
__init__(p, random_seed=None)
```


##### Parameters


`p: float`  
Probability of drawing a 1. Must be between 0 and 1.

`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 Bernoulli distribution.


Usage

``` python
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 Bernoulli distribution:

- A single float (0 or 1) when size is None
- A numpy array of floats (0s and 1s) with shape determined by size parameter