View source: R/hypervolume_thin.R

hypervolume_thin | R Documentation |

Many hypervolume algorithms have computational complexities that scale with the number of random points used to characterize a hypervolume (`@RandomPoints`

). This value can be reduced to improve runtimes at the cost of lower resolution.

hypervolume_thin(hv, factor = NULL, num.points = NULL)

`hv` |
An object of class |

`factor` |
A number in (0,1) describing the fraction of random points to keep. |

`num.points` |
A number describing the number random points to keep. |

Either `factor`

or `npoints`

(but not both) must be specified.

A `Hypervolume`

object

data(penguins,package='palmerpenguins') penguins_no_na = as.data.frame(na.omit(penguins)) penguins_adelie = penguins_no_na[penguins_no_na$species=="Adelie", c("bill_length_mm","bill_depth_mm","flipper_length_mm")] hv = hypervolume_box(penguins_adelie,name='Adelie') # downsample to 1000 random points hv_thinned = hypervolume_thin(hv, num.points=1000) hv_thinned

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.