PRC diagram of treatment and plot lines or points without species loading

Source: R/plot_sample_scores_cdt.R

plot_sample_scores_cdt creates a PRC diagram of the treatments without species loadings.

plot_sample_scores_cdt(
  object,
  treatment = NULL,
  condition = NULL,
  plot = 1,
  xvals = NULL,
  score_name = "PRC1",
  size = c(2, 2),
  symbols_on_curves = FALSE,
  verbose = TRUE
)

Arguments

object

a result of doPRC or PRC_scores or a list with element PRCplus (a data frame with a variables to plot, see details).

treatment

character vector of names of factors in object$PRCplus, the first two of which set the color and linetype of treatments. Default: derived from object$'focal_and_conditioning_factors'.

condition

character vector of names of factors in object$PRCplus, the first one being used as x-axis. Default: derived from object$'focal_and_conditioning_factors'.

plot

0 or 1 (no/yes individual plot points) or character name of a factor in object$PRCplus indicating the plots (microcosms, subjects or objects) in a longitudinal study so as to plot lines. Default: 1 yielding points instead of lines.

xvals

numeric values for the levels of the condition factor, or name of numeric variable in object$PRCplus to be used for the x-axis. Default: NULL for which the values are obtained using the function fvalues4levels applied to object$PRCplus[[condition[1]]]

score_name

name of scores to use as y-axis; default: "PRC1".

size

size of symbols and symbols in the legend. default: c(2, 2). If the length is not 2 than the first entry is replicated.

symbols_on_curves

logical, draw symbols on the PRC curves at the measurement times (default FALSE). If TRUE, symbols are for the treatment, if there is one, and for the second treatment if there are two.

verbose

logical for printing the current model, score_name, condition and treatment (default TRUE).

Value

a ggplot object

Details

plot_sample_scores_cdt can be used to plot any ordination score or variable against the condition with treatments indicated by colors and line type by setting score_name to the name of the variable of interest and argument plot to 0. If object is not a result of doPRC or PRC_scores), set treatment and condition (or object$'focal_and_conditioning_factors') and set object to a list with element PRCplus; object$PRCplus should contain the names indicated by the arguments treatment, condition and, optionally, plot

  • treatment: a factor for the treatments,

  • condition: a factor or variable condition

If plot!=0, the scores (values) for individual sample points or lines must be in the variable "PRC1_E" or, in general, paste(score_name,"_E", sep = "").

Examples

data(pyrifos, package = "vegan") #transformed species data from package vegan
#the chlorpyrifos experiment from van den Brink & ter Braak 1999
Design <- data.frame(week=gl(11, 12, labels=c(-4, -1, 0.1, 1, 2, 4, 8, 12, 15, 19, 24)),
                     dose=factor(rep(c(0.1, 0, 0, 0.9, 0, 44, 6, 0.1, 44, 0.9, 0, 6), 11)),
                     ditch = gl(12, 1, length=132))

mod_rda <- vegan::rda( pyrifos ~ dose:week + Condition(week),  data = Design)
#> 
#> Some constraints or conditions were aliased because they were redundant. This
#> can happen if terms are constant or linearly dependent (collinear):
#> 'dose44:week-4', 'dose44:week-1', 'dose44:week0.1', 'dose44:week1',
#> 'dose44:week2', 'dose44:week4', 'dose44:week8', 'dose44:week12',
#> 'dose44:week15', 'dose44:week19', 'dose44:week24'
Design_w_PRCs <- PRC_scores(mod_rda, focal_factor_name= "dose", referencelevel = "0",
                            rank = 2, data= Design, scaling ="ms", flip = FALSE)

plot_sample_scores_cdt(Design_w_PRCs, plot = "ditch")
#> The analysis is based on model
#>  pyrifos~dose:week + Condition(week) 
#> The current score, condition and treatment(s) are:
#>  score    (y-axis): PRC1 
#> condition (x-axis): week 
#> treatments (color ): dose 
#> Set these arguments yourself if you wish otherwise.

plot_sample_scores_cdt(Design_w_PRCs)
#> The analysis is based on model
#>  pyrifos~dose:week + Condition(week) 
#> The current score, condition and treatment(s) are:
#>  score    (y-axis): PRC1 
#> condition (x-axis): week 
#> treatments (color ): dose 
#> Set these arguments yourself if you wish otherwise.

plot_sample_scores_cdt(Design_w_PRCs, plot = "Ditch")
#> The analysis is based on model
#>  pyrifos~dose:week + Condition(week) 
#> The current score, condition and treatment(s) are:
#>  score    (y-axis): PRC1 
#> condition (x-axis): week 
#> treatments (color ): dose 
#> Set these arguments yourself if you wish otherwise.
#> Warning: Ditch is not a variable in object$PRCplus