batchPlot.list: Plot a Set of Curves from a List of Data
In thomasWeise/plotteR: An R Package with Utilities for Graphics and Plots

A simple utility method for visualizing a list of data.

batchPlot.list(data, xfun = function(x) x$x, yfun = function(x) x$y,
  ffun = function(x) x$f, plotXY = TRUE, widthXY = 0.5,
  plotXF = TRUE, widthXF = 1.5, names = NULL,
  colors = colors.distinct(length(data)), xlab = "", ylab = "",
  legend = NULL, x.min.lower = NA, x.min.upper = NA,
  x.max.lower = NA, x.max.upper = NA, y.min.lower = NA,
  y.min.upper = NA, y.max.lower = NA, y.max.upper = NA,
  x.add = NULL, XYType = "p", XFType = "l", ...)

`data`	the data object, could be a list of lists or anything
`xfun`	a function which receives an element from the `data` list and extracts a vector of `x`-coordinates from it
`yfun`	a function which receives an element from the `data` list and extracts a vector of `y`-coordinates from it to be plotted as points, or `NULL` if no points should be plotted (see `plotXY`)
`ffun`	a function which receives an element from the `data` list and extracts a unary function from it to be plotted over the extracted `x` coordinates, or `NULL` if no points should be plotted (see `plotXF`)
`plotXY`	should the `x-y` points be plotted (if `yfun` is not `NULL`)
`widthXY`	the line width for points to be plotted (only considered if `plotXY` is `TRUE` and `yfun` is not `NULL`)
`plotXF`	should the `x-y` lines be plotted (if `ffun` is not `NULL`)
`widthXF`	the line width for lines to be plotted (only considered if `plotXF` is `TRUE` and `ffun` is not `NULL`)
`names`	the names of the lines to be printed in the legend, or `NULL` if no legend should be plotted
`colors`	the colors to be used for the plot
`xlab`	the label for the x-axis
`ylab`	the label for the y-axis
`legend`	a list of additional parameters to be passed to `legend`, or `NULL` to use the default parameters
`x.min.lower`	a lower bound for the automatically computed `x` coordinate minimum
`x.min.upper`	an upper bound for the automatically computed `x` coordinate minimum
`x.max.lower`	a lower bound for the automatically computed `x` coordinate maximum
`x.max.upper`	an upper bound for the automatically computed `x` coordinate maximum
`y.min.lower`	a lower bound for the automatically computed `y` coordinate minimum
`y.min.upper`	an upper bound for the automatically computed `y` coordinate minimum
`y.max.lower`	a lower bound for the automatically computed `y` coordinate maximum
`y.max.upper`	an upper bound for the automatically computed `y` coordinate maximum
`x.add`	some additional `x` coordinates at which the function should be evaluated, or `TRUE` if the `x` coordinate minimum and maximum over all data sets should be added as evaluation points
`XYType`	the type in which the XY data should be plotted, by default `"p"`, i.e., as points
`XFType`	the type in which the XF data should be plotted, by default `"l"`, i.e., as lines
`...`	Arguments passed on to `graphics::plot`

library(plotteR)

# set a random seed for replicability
set.seed(1367);

# make an example
make.example <- function(f) {
  n <- as.integer(round(runif(n=1, min=10, max=200)));
  x <- sort(runif(n=n, min=0, max=3)); # generate x data
  y <- rnorm(n=n, mean=f(x), s=0.1);  # noisy y
  x <- rnorm(n=n, mean=x, s=0.1); # noisy x
  return(list(x=x, y=y, f=f));
}

# the three base functions
f <- c(function(x) 1 - 0.2*x + 0.75*x*x - 0.3*x*x*x,
       function(x) 0.1 * exp(3 - x),
       function(x) 1.2 + 0.7*sin(2*x));

# create the three example data sets
examples <- lapply(X=f, FUN=make.example);

# plot the original data
batchPlot.list(examples,
               names=c("f1", "f2", "f3"),
               main="Original Data and Function Values for x",
               legend=list(x="bottom", horiz=TRUE));
library(plotteR)

# set a random seed for replicability
set.seed(1367);

# make an example
make.example <- function(f) {
  suppressWarnings({
    repeat {
      n <- as.integer(round(runif(n=1, min=10, max=20)));
      x <- sort(runif(n=n, min=-5, max=5)); # generate x data
      y <- rnorm(n=n, mean=f(x), s=0.1);  # noisy y
      x <- rnorm(n=n, mean=x, s=0.1); # noisy x
      fi <- is.finite(x) & is.finite(y);
      x <- x[fi];
      if(length(x) > 4L) {
        y <- y[fi];
        return(list(x=x, y=y, f=f));
      }
    }
  });
}

# the three base functions
f <- c(function(x) 1 - 0.2*x + 0.75*x*x - 0.3*x*x*x,
       log,   # this function becomes non-finite for x <= 0
       asin); # non-finite for any x outside of [-1, 1]

# create the three example data sets
examples <- lapply(X=f, FUN=make.example);

old <- par(mfcol=c(2, 1));

# plot the original data, which only covers part of the x.axis
batchPlot.list(examples,
               names=c("f1", "f2", "f3"),
               main="Original Data and Function Values for x",
               legend=list(x="left"),
               y.min.lower = -3,
               y.max.upper= 3);
abline(v=-1, col="gray");abline(v=0, col="gray");abline(v=1, col="gray");


# extending the function lines towards their smallest and largest finite
# points
batchPlot.list(examples,
               names=c("f1", "f2", "f3"),
               main="Functions Extented by Finite Point Search",
               legend=list(x="left"),
               y.min.lower = -3,
               y.max.upper= 3,
               x.add = TRUE);
abline(v=-1, col="gray");abline(v=0, col="gray");abline(v=1, col="gray");

par(old);