One of the use cases for fractal noise is to simulate natural phenomena.
perlin/simplex noise are e.g. often used to create flow fields, but this can
be problematic as they are not divergence-free (particles will concentrate at
sinks/gutters in the field). An approach to avoid this is to take the curl of
a field instead. The curl operator is ensured to produce divergence-free
output, when supplied with continuous fields such as those generated by
simplex and perlin noise. The end result is a field that is incompressible,
thus modelling fluid dynamics quite well.

curl_noise(
generator,
x,
y,
z = NULL,
...,
seed = NULL,
delta = NULL,
mod = NULL
)

## Arguments

generator |
The noise generating function, such as gen_simplex, or
`fracture()` |

x, y, z |
The coordinates to generate the curl for as unquoted expressions |

... |
Further arguments to `generator` |

seed |
A seed for the generator. For 2D curl the seed is a single
integer and for 3D curl it must be a vector of 3 integers. If `NULL` the
seeds will be random. |

delta |
The offset to use for the partial derivative of the `generator` .
If `NULL` , it will be set as 1e-4 of the largest range of the dimensions. |

mod |
A modification function taking the coordinates along with the
output of the `generator` call and allow modifications of it prior to
calculating the curl. The function will get the coordinates as well as a
`value` holding the generator output for each coordinate. If the curl is
requested in 2D the value will be a numeric vector and `mod()` should return
a numeric vector of the same length. IF the curl is requested in 3D the value
is a list of three numeric vectors (x, y, and z) and `mod()` should return a
list of three vectors of the same length. Passing NULL will use the generator
values unmodified. |

## References

Bridson, Robert. Hourihan, Jim. Nordenstam, Marcus (2007). *Curl-noise for procedural fluid flow*.
ACM Transactions on Graphics 26(3): 46. doi:10.1145/1275808.1276435.

## See also

## Examples