This is a wrapper for the `RFsimulate`

function in the `RandomFields`

package. The main addition is the `speedup`

argument which allows
for faster map generation. A `speedup`

of 1 is normal and will get
progressively faster as the number increases, at the expense of coarser
pixel resolution of the pattern generated.

gaussMap( x, scale = 10, var = 1, speedup = 1, method = "RMexp", alpha = 1, inMemory = FALSE, ... )

x | A spatial object (e.g., a |
---|---|

scale | The spatial scale in map units of the Gaussian pattern. |

var | Spatial variance. |

speedup | An numeric value indicating how much faster than 'normal' to generate maps. It may be necessary to give a value larger than 1 for large maps. Default is 1. |

method | The type of model used to produce the Gaussian pattern.
Should be one of |

alpha | A required parameter of the 'RMstable' model. Should be in the interval [0,2] to provide a valid covariance function. Default is 1. |

inMemory | Should the RasterLayer be forced to be in memory?
Default |

... | Additional arguments to |

A raster map with same extent as `x`

, with a Gaussian random pattern.

`RFsimulate`

and `extent`

if (FALSE) { if (require(RandomFields)) { library(raster) nx <- ny <- 100L r <- raster(nrows = ny, ncols = nx, xmn = -nx/2, xmx = nx/2, ymn = -ny/2, ymx = ny/2) speedup <- max(1, nx/5e2) map1 <- gaussMap(r, scale = 300, var = 0.03, speedup = speedup, inMemory = TRUE) if (interactive()) Plot(map1) # with non-default method map1 <- gaussMap(r, scale = 300, var = 0.03, method = "RMgauss") } }