# monte_carlo()

Realizations of the long-term capacity under the five uncertainty sources.

Usage

[Source](https://github.com/lornearnold/driven-pile/blob/main/src/driven_pile/montecarlo.py#L16-L108)

``` python
monte_carlo(
    log,
    soil,
    options=None,
    mc_options=None,
    *,
    target=None,
    top_band=None,
)
```

## Parameters

`log: DriveLog`  

`soil: SoilProfile`  

`options: ModelOptions = None`  

`mc_options: MonteCarloOptions = None`  

`target: Target = None`  
Precomputed capacity target; built from the log when omitted.

`top_band: TopPhiBand = None`  
Precomputed admissible top-segment band; swept when omitted.

## Returns

`MonteCarloResult`  

## Notes

Each realization draws a capacity-formula bias (lognormal), a multiplier on the cyclic resistance ratio (lognormal), a shift of the friction angle correlation line (uniform), independent normal noise on each foot's capacity target, and a top-segment friction angle uniform over the admissible band. Realizations are added in chunks until the 95 percent confidence half-width of the mean long-term capacity is below `mc_options.ci_target` of the mean or `mc_options.max_realizations` is reached.