BioGeoBEARS (version 0.2.1)

symbolic_to_Q_matrix: Convert symbolic matrix to an instantaneous rate matrix (Q matrix)

Description

This function takes a transition probability matrix (in text form) and converts it to an instantaneous rate matrix (Q matrix), given values for d, e, or other parameters in the text formulas.

Usage

symbolic_to_Q_matrix(dedf, cellsplit = "\\+", mergesym = "*", d = 0.1, e = 0.01, ...)

Arguments

dedf

The transition matrix or dispersal-extinction data.frame (dedf), contains the actual text of the formulas by which the transition probability matrix would be calculated.

cellsplit

The symbol to split the formulas on. Default "\\+" (plus symbol, with escape code).

mergesym

The symbol to merge the formulas with. Default "+".

d

The dispersal/range expansion rate. Default d=0.1.

e

The extinction/range contraction rate. Default e=0.01.

...

Additional arguments to pass to symbolic_cell_to_relprob_cell via sapply, and thence to cellstrsplit.

Value

dedf_vals The output data.frame, contains the Q matrix

Details

This is not particularly fast, but good for illustrative purposes.

References

http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster

Matzke_2012_IBS

FosterIdiots

See Also

areas_list_to_states_list_new, areas_list_to_states_list_old, make_relprob_matrix_de

Examples

testval=1

states_list = list("_", c("A"), c("B"), c("C"), c("A","B"),
c("B","C"), c("A","C"), c("A","B","C"))

states_list = areas_list_to_states_list_new(areas=c("A","B","C"),
include_null_range=TRUE, split_ABC=TRUE)
states_list

dedf = make_relprob_matrix_de(states_list=states_list, split_ABC=FALSE,
split="", remove_simultaneous_events=TRUE, add_multiple_Ds=TRUE,
dispersal_multiplier_matrix=make_dispersal_multiplier_matrix(states_list=states_list))
dedf

# Right
Qmat = symbolic_to_Q_matrix(dedf, cellsplit="\\\\+", mergesym="+", d=0.1, e=0.01)
Qmat

# Wrong
Qmat = symbolic_to_Q_matrix(dedf, cellsplit="\\\\+", mergesym="*", d=0.1, e=0.01)
Qmat

# You don't have to split, if the formulas are directly parsable
Qmat = symbolic_to_Q_matrix(dedf, cellsplit="yadda", mergesym="", d=0.1, e=0.01)
Qmat