Loon's displays that are based on Cartesian coordinates (i.e. scatterplot, histogram and graph display) allow for layering visual information including polygons, text and rectangles.
Usage
l_layer_polygon(
widget,
x,
y,
color = "gray80",
linecolor = "black",
linewidth = 1,
label = "polygon",
parent = "root",
index = 0,
...
)Arguments
- widget
widget path name as a string
- x
x coordinates
- y
y coordinates
- color
fill color, if empty string
"", then the fill is transparant- linecolor
outline color
- linewidth
linewidth of outline
- label
label used in the layers inspector
- parent
group layer
- index
of the newly added layer in its parent group
- ...
additional state initialization arguments, see
l_info_states
Examples
if (interactive()){
set.seed(500)
x <- rnorm(30)
y <- 4 + 3*x + rnorm(30)
fit <- lm(y~x)
xseq <- seq(min(x)-1, max(x)+1, length.out = 50)
fit_line <- predict(fit, data.frame(x=range(xseq)))
ci <- predict(fit, data.frame(x=xseq),
interval="confidence", level=0.95)
pi <- predict(fit, data.frame(x=xseq),
interval="prediction", level=0.95)
p <- l_plot(y~x, color='black', showScales=TRUE, showGuides=TRUE)
gLayer <- l_layer_group(
p, label="simple linear regression",
parent="root", index="end"
)
fitLayer <- l_layer_line(
p, x=range(xseq), y=fit_line, color="#04327F",
linewidth=4, label="fit", parent=gLayer
)
ciLayer <- l_layer_polygon(
p,
x = c(xseq, rev(xseq)),
y = c(ci[,'lwr'], rev(ci[,'upr'])),
color = "#96BDFF", linecolor="",
label = "95 % confidence interval",
parent = gLayer, index='end'
)
piLayer <- l_layer_polygon(
p,
x = c(xseq, rev(xseq)),
y = c(pi[,'lwr'], rev(pi[,'upr'])),
color = "#E2EDFF", linecolor="",
label = "95 % prediction interval",
parent = gLayer, index='end'
)
l_info_states(piLayer)
}