filterCoefData filters contributions of species
to function by sign.
filterCoefData(coefData, type = "positive")Matrix of functions and coefficients for which species affect them from getRedundancy.
Are the kinds of effects we're looking at "positive", "negative" or "all".
Returns a filtered matrix.
Takes a matrix of functions and coefficients for species and filters out only the sign of contributions desired. Typically used by other functions in the package.
data(all_biodepth)
allVars <- qw(biomassY3, root3, N.g.m2, light3, N.Soil, wood3, cotton3)
germany <- subset(all_biodepth, all_biodepth$location == "Germany")
vars <- whichVars(germany, allVars)
species <- relevantSp(germany, 26:ncol(germany))
# re-normalize N.Soil so that everything is on the same
# sign-scale (e.g. the maximum level of a function is
# the "best" function)
germany$N.Soil <- -1 * germany$N.Soil + max(germany$N.Soil, na.rm = TRUE)
res.list <- lapply(vars, function(x) sAICfun(x, species, germany))
names(res.list) <- vars
coefs <- getRedundancy(vars, species, germany, output = "coef")
stdCoefs <- stdEffects(coefs, germany, vars, species)
filterCoefData(stdCoefs)
#> ACHMIL1 ALOPRA1 ANTODO1 ARRELA1 BROHOR1 CAMPAT1 CENJAC1
#> biomassY3 0.0000000 0.0000000 0.000000 0 0.0000000 0.0000000 0
#> root3 0.2545806 0.0000000 0.000000 0 0.5482183 0.0000000 0
#> N.g.m2 0.2083257 0.0000000 0.000000 0 0.0000000 0.0000000 0
#> N.Soil 0.0000000 0.0000000 0.000000 0 1.1112317 0.0000000 0
#> cotton3 0.0000000 0.2954783 1.061634 0 0.0000000 0.8870159 0
#> CHRLEU1 CREBIE1 CYNCRI1 DACGLO1 FESPRA1 FESRUB1 GERPRA1 HOLLAN1
#> biomassY3 0 0.00000 0 0.1506547 0.1588554 0.0000000 0 0
#> root3 0 0.00000 0 0.0000000 0.0000000 0.3223808 0 0
#> N.g.m2 0 0.00000 0 0.0000000 0.2845360 0.0000000 0 0
#> N.Soil 0 1.71227 0 0.2846729 0.0000000 0.0000000 0 0
#> cotton3 0 0.00000 0 0.0000000 0.0000000 0.0000000 0 0
#> KNAARV1 LATPRA1 LEOAUT1 LOLPER1 LOTCOR1 LYCFLO1 PHLPRA1
#> biomassY3 0 0.2342718 0 0.0000000 0.4398584 0 0.0000000
#> root3 0 0.3222751 0 0.3413014 0.0000000 0 0.0000000
#> N.g.m2 0 0.0000000 0 0.1201910 0.4888396 0 0.0000000
#> N.Soil 0 1.1149286 0 0.0000000 0.2943426 0 0.9196661
#> cotton3 0 0.0000000 0 0.0000000 0.0000000 0 0.0000000
#> PIMMAJ1 PLALAN1 RANACR1 RUMACE1 TAROFF1 TRIPRA1 TRIREP1 VICCRA1
#> biomassY3 0 0.0000000 0.00000 0 0 0.6546163 0.4084509 0
#> root3 0 0.0000000 0.00000 0 0 0.0000000 0.0000000 0
#> N.g.m2 0 0.0000000 0.00000 0 0 0.8410219 0.4558752 0
#> N.Soil 0 0.0000000 0.59527 0 0 0.0000000 0.0000000 0
#> cotton3 0 0.4548995 0.00000 0 0 0.5531104 0.2790614 0
#> VICSEP1
#> biomassY3 0
#> root3 0
#> N.g.m2 0
#> N.Soil 0
#> cotton3 0
#########
# filterCoefData takes a matrix of coefficients
# and filters it so that only the positive, negative, or both contributions
# are present
#########