Plot a point based on a summary statistic computed from a given method (typically, mean) for a set of points in a projected ENA space
ena.plot.group(
enaplot,
points = NULL,
method = "mean",
labels = NULL,
colors = default.colors[1],
shape = c("square", "triangle-up", "diamond", "circle"),
confidence.interval = c("none", "crosshairs", "box"),
outlier.interval = c("none", "crosshairs", "box"),
label.offset = "bottom right",
label.font.size = NULL,
label.font.color = NULL,
label.font.family = NULL,
show.legend = T,
legend.name = NULL,
...
)
ENAplot
object to use for plotting
A matrix or data.frame where columns contain coordinates of points in a projected ENA space
A function for computing a summary statistic for each column of points
A character which will be the label for the group's point
A character, determines color of the group's point, default: enaplot$color
A character, determines shape of the group's point, choices: square, triangle, diamond, circle, default: square
A character that determines how the confidence interval is displayed, choices: none, box, crosshair, default: none
A character that determines how outlier interval is displayed, choices: none, box, crosshair, default: none
character: top left (default), top center, top right, middle left, middle center, middle right, bottom left, bottom center, bottom right
An integer which determines the font size for label, default: enaplot\$font.size
A character which determines the color of label, default: enaplot\$font.color
A character which determines font type, choices: Arial, Courier New, Times New Roman, default: enaplot\$font.family
Logical indicating whether to show the point labels in the in legend
Character indicating the name to show above the plot legend
Additional parameters
The ENAplot
provided to the function, with its plot updated to include the new group point.
Plots a point based on a summary statistic for a group (typically, mean)
ena.plot
, ena.plot.points
data(RS.data)
codeNames = c('Data','Technical.Constraints','Performance.Parameters',
'Client.and.Consultant.Requests','Design.Reasoning','Collaboration');
accum = ena.accumulate.data(
units = RS.data[,c("UserName","Condition")],
conversation = RS.data[,c("Condition","GroupName")],
metadata = RS.data[,c("CONFIDENCE.Change","CONFIDENCE.Pre","CONFIDENCE.Post")],
codes = RS.data[,codeNames],
window.size.back = 4
)
set = ena.make.set(
enadata = accum,
rotation.by = ena.rotate.by.mean,
rotation.params = list(
accum$meta.data$Condition=="FirstGame",
accum$meta.data$Condition=="SecondGame"
)
)
plot = ena.plot(set)
unitNames = set$enadata$units
### Plot Condition 1 Group Mean
plot = ena.plot.group(plot, as.matrix(set$points$Condition$FirstGame), labels = "FirstGame",
colors = "red", confidence.interval = "box")
### plot Condition 2 Group Mean
plot = ena.plot.group(plot, as.matrix(set$points$Condition$SecondGame), labels = "SecondGame",
colors = "blue", confidence.interval = "box")
print(plot);