plot_fuzz: Plot fuzzy metrics

In USEPA/CoralBCG: Quantitative Rules for the Coral Biological Condition Gradient

Description

Plot fuzzy metrics given based on expert BCG levels

Usage

plot_fuzz(met_in, scr_in, met, cols = "Paired", met_val = NULL,
  sdchg = NULL, widths = c(0.6, 1, 0.6, 0.6))

Arguments

met_in	input data.frame of coral metrics
scr_in	input data.frame of site BCG scores, see details
met	chr string of metric to plot
cols	chr string of palette for plot colors, from brewer.pal
met_val	numeric value of metric to show on plot
sdchg	optional list passed to met_crvs for manually changing standard deviation estimates
widths	numeric vector indicating widths of each of four plots, passed to grid.arrange

Details

The input scr_in data has two columns labelled station_code and scr. The station codes should match those in met_in. The scr values for each station can be numeric or character string BCG levels that represent qualitative rankings.

Value

A ggplot object

See Also

met_crvs, met_dist

Examples

## Not run: 
# coral metrics
met_in <- get_stony_mets(crl_dem)

# bcg scores for each station
station_code <- c(1:5)
scr <- c(2, 5, 3, 2, 4)
scr_in <- data.frame(station_code, scr) 

# plot
plot_fuzz(met_in, scr_in, met = 'tot_rich')

# plot, manual change of standard deviation
sdchg <- list(tot_rich = c(2, 2, 2, 2))
plot_fuzz(met_in, scr_in, met = 'tot_rich', sdchg = sdchg)

## End(Not run)

USEPA/CoralBCG documentation built on May 20, 2019, 3:28 p.m.