## distributions.FixedDistribution


Fixed distribution implementation.


Usage

``` python
distributions.FixedDistribution(value)
```


A degenerate distribution that always returns the same fixed value. Useful for constants or deterministic parameters in models.

This class conforms to the Distribution protocol and provides methods to sample a constant value regardless of the number of samples requested.


## Methods

| Name | Description |
|----|----|
| [__init__()](#__init__) | Initialize a fixed distribution. |
| [sample()](#sample) | Generate "samples" from the fixed distribution (always the same value). |

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


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


Initialize a fixed distribution.


Usage

``` python
__init__(value)
```


##### Parameters


`value: float`  
The constant value that will be returned by sampling.


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


#### sample()


Generate "samples" from the fixed distribution (always the same value).


Usage

``` python
sample(size=None)
```


##### Parameters


`size: Optional[Union[int, Tuple[int, …]]] = None`  
The number/shape of samples to generate:

- If None: returns the fixed value as a float
- If int: returns a 1-D array filled with the fixed value
- If tuple of ints: returns an array with that shape filled with the fixed value


##### Returns


`Union[float, NDArray[np.float64]]`  
The fixed value:

- A single float when size is None
- A numpy array filled with the fixed value with shape determined by size parameter