Description Usage Arguments Details Value Note Author(s) References See Also Examples
View source: R/BioGeoBEARS_basics_v1.R
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.
1 2 | symbolic_to_Q_matrix(dedf, cellsplit = "\\+",
mergesym = "*", d = 0.1, e = 0.01, ...)
|
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
|
e |
The extinction/range contraction rate. Default
|
... |
Additional arguments to pass to
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This is not particularly fast, but good for illustrative purposes.
dedf_vals
The output
data.frame
, contains the Q matrix
Go BEARS!
Nicholas J. Matzke matzke@berkeley.edu
http://phylo.wikidot.com/matzke-2013-international-biogeography-society-poster
Matzke_2012_IBS
FosterIdiots
areas_list_to_states_list_new
,
areas_list_to_states_list_old
,
make_relprob_matrix_de
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | 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
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