Documentation ¶
Overview ¶
Package like implements a command to perform a biogeographic reconstruction using likelihood.
Index ¶
Constants ¶
This section is empty.
Variables ¶
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var Command = &command.Command{
Usage: `like [--ranges] [--stem <age>] [--lambda <value>]
[-o|--output <file>]
[--cpu <number>] [--nomat] <project-file>`,
Short: "perform a likelihood reconstruction",
Long: `
Command like reads a PhyGeo project and performs a likelihood reconstruction
for the trees in the project.
The argument of the command is the name of the project file.
By default, it will use geographic distributions stored as points
(presence-absence maps). If there are no point distributions or the flag
--ranges is defined, the continuous range maps will be used.
By default, a stem branch will be added to each tree using 10% of the root
age. To set a different stem age, use the flag --stem; the value should be in
million years.
The flag --lambda defines the concentration parameter of the spherical normal
(equivalent to the kappa parameter of the von Mises-Fisher distribution) for a
diffusion process over a million years using 1/radias^2 units. If no value is
defined, it will use 100. As the kappa parameter, larger values indicate low
diffusivity, while smaller values indicate high diffusivity.
The output file is a pixel probability file with the conditional likelihoods
(i.e., down-pass results) for each pixel at each node. The prefix of the
output file name is the name of the project file. To set a different prefix,
use the flag --output, or -o. The output file name will be named by the tree
name, the lambda value, and the suffix 'down'.
By default, all available CPUs will be used in the calculations. Set the flag
--cpu to use a different number of CPUs.
By default, if the base pixelation is smaller than 500 pixels at the equator,
it will build a distance matrix to speed up the search. As this matrix
consumes a lot of memory, this procedure can be disabled using the flag
--nomat.
`,
SetFlags: setFlags,
Run: run,
}
Functions ¶
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Types ¶
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