Plot average response curves with error bars

A wrapper for lattice::xyplot that plots average response curves with error bars.

Usage

xyplot_avg_rc(
    Y,
    X,
    point_identifier,
    group_identifier,
    y_error_bars = TRUE,
    x_error_bars = FALSE,
    cols = multi_curve_colors(),
    eb_length = 0.05,
    eb_lwd = 1,
    na.rm = TRUE,
    subset = rep_len(TRUE, length(Y)),
    ...
  )

Arguments

Y

A numeric vector of y-values.

X

A numeric vector of x-values with the same length as Y

point_identifier

A vector with the same length as Y that indicates the location of each (x, y) pair along the response curve; typically this is the seq_num column of an exdf object.

group_identifier

A vector with the same length as Y that indicates the "group" of each response curve.

y_error_bars

A logical value indicating whether to plot y-axis error bars.

x_error_bars

A logical value indicating whether to plot x-axis error bars.

cols

A vector of color specifications.

eb_length

The width of the error bars.

eb_lwd

The line width (thickness) of the error bars.

na.rm

A logical value indicating whether or not to remove NA values before calculating means and standard errors.

subset

A logical vector (of the same length as Y) indicating which points to include in the final plot.

...

Additional arguments to be passed to lattice::xyplot.

Details

This function calculates average values of X and Y at each value of the point_identifier across groups defined by group_identifier, and then uses these values to plot average response curves for each group. Error bars are determined by calculating the standard errors of X and Y at each value of the point_identifier across groups defined by group_identifier.

If points were excluded from the data set using remove_points with method = 'exclude', then the include_when_fitting column should be passed to xyplot_avg_rc as the subset input argument; this will ensure that the excluded points are not used when calculating average response curves.

Value

A trellis object created by lattice::xyplot.

Examples

# Read an example Licor file included in the PhotoGEA package
licor_file <- read_gasex_file(
  PhotoGEA_example_file_path('ball_berry_1.xlsx')
)

# Organize the response curve data
licor_file <- organize_response_curve_data(
  licor_file,
  c('species', 'plot'),
  c(),
  'Qin'
)

# Plot the average light response curve for each species (here there is only one
# curve for tobacco, so there are no tobacco error bars)
xyplot_avg_rc(
  licor_file[, 'A'],
  licor_file[, 'Qin'],
  licor_file[, 'seq_num'],
  licor_file[, 'species'],
  ylim = c(0, 50),
  xlab = paste0('Incident PPFD (', licor_file$units$Qin, ')'),
  ylab = paste0('Average net assimilation (', licor_file$units$A, ')'),
  auto = TRUE,
  grid = TRUE
)


# Exclude a few points from the data set and re-plot the average curves
licor_file <- remove_points(
  licor_file,
  list(obs = c(5, 10, 18)),
  method = 'exclude'
)

xyplot_avg_rc(
  licor_file[, 'A'],
  licor_file[, 'Qin'],
  licor_file[, 'seq_num'],
  licor_file[, 'species'],
  subset = licor_file[, 'include_when_fitting'],
  ylim = c(0, 50),
  xlab = paste0('Incident PPFD (', licor_file$units$Qin, ')'),
  ylab = paste0('Average net assimilation (', licor_file$units$A, ')'),
  auto = TRUE,
  grid = TRUE
)