plot_fit: Plot metabCombiner Fits

View source: R/plot_fit.R

plot,metabCombiner,ANY-methodR Documentation

Plot metabCombiner Fits

Description

This is a plotting method for metabCombiner objects. It displays ordered pairs and a curve fit computed using fit_gam or fit_loess, using base R graphics.

Usage

## S4 method for signature 'metabCombiner,ANY'
plot(x, y, ...)

plot_fit(
  object,
  fit = c("gam", "loess"),
  pcol = "black",
  lcol = "red",
  lwd = 3,
  pch = 19,
  outlier = "show",
  ocol = "springgreen4",
  legend = c("anchor", "outlier"),
  ...
)

Arguments

x

metabCombiner object

y

...

...

Other variables passed into graphics::plot

object

metabCombiner object

fit

choice of model (either "gam" or "loess").

pcol

color of the normal points (ordered RT pair) in the plot

lcol

color of the fitted line in the plot

lwd

line width of the curve fit between anchor points

pch

plot character type; see ?graphics::par for details

outlier

display option for outliers. If "show" or "s", treats outlier points like normal anchors; if "remove" or "r", removes outlier points from the plot; if "highlight" or "h", displays outliers with a different color and associated legend.

ocol

color of the outlier points; outlier argument must be set to "highlight" or "h"

legend

length-2 character vector indicating point labels in the legend if outlier argument set to "highlight" or "h"

Value

no values returned

Examples

data(plasma30)
data(plasma20)

p30 <- metabData(plasma30, samples = "CHEAR")
p20 <- metabData(plasma20, samples = "Red", rtmax = 17.25)
p.comb = metabCombiner(xdata = p30, ydata = p20, binGap = 0.0075)
p.comb = selectAnchors(p.comb, tolmz = 0.003, tolQ = 0.3, windy = 0.02)
p.comb = fit_gam(p.comb, k = 20, iterFilter = 1, family = "gaussian")

##plot of GAM fit
plot(p.comb, main = "Example GAM Fit Plot", xlab = "X Dataset RTs",
     ylab = "Y Dataset RTs", pcol = "red", lcol = "blue", lwd = 5,
     fit = "gam", outliers = "remove")

grid(lwd =  2, lty = 3 ) #adding gridlines


hhabra/metabCombiner documentation built on June 5, 2024, 5:46 a.m.