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library(ggvis)
# Slider input in transform_smooth
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_smooths(
span = input_slider(0.2, 1, value = 0.5, step = 0.05, label = "span")
)
# Slider and select input in transform_density
mtcars %>% ggvis(x = ~wt) %>%
layer_densities(
adjust = input_slider(.1, 2, value = 1, step = .1, label = "Bandwidth adjustment"),
kernel = input_select(
c("Gaussian" = "gaussian", "Epanechnikov" = "epanechnikov",
"Rectangular" = "rectangular", "Triangular" = "triangular",
"Biweight" = "biweight", "Cosine" = "cosine", "Optcosine" = "optcosine"),
label = "Kernel")
)
# Example with value map function
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_model_predictions(model = "loess",
model_args = list(n = input_select(
choices = c("Two", "Six", "Eighty"),
map = function(value) switch(value, Two = 2, Six = 6, Eighty = 80),
label = "Number of points"
))
)
# Checkbox input
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points(
opacity := input_checkbox(label = "Semi-transparent",
map = function(val) ifelse(val, .3, 1))) %>%
layer_model_predictions(
model = input_checkbox(label = "LOESS (curve) model fit",
map = function(val) ifelse(val, "loess", "lm")))
# Text input
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points(fill := input_text(label = "Point color", value = "red")) %>%
layer_model_predictions(model = input_text(label = "Model type", value = "loess"))
# Numeric input
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points(size := input_numeric(value = 25, label = "Point size")) %>%
layer_smooths(span = input_numeric(value = 0.5, label = "Interpolation points"))
# Radio buttons
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points() %>%
layer_model_predictions(
model = input_radiobuttons(c("LOESS" = "loess", "Linear" = "lm"),
label = "Model type"),
stroke := input_radiobuttons(c("Red" = "red", "Black" = "black"),
label = "Line color")
)
# Checkbox group
mtcars %>% ggvis(x = ~wt, y = ~mpg) %>%
layer_points(
fill := input_checkboxgroup(
choices = c("Red" = "r", "Green" = "g", "Blue" = "b"),
label = "Point color components",
map = function(val) {
rgb(0.8 * "r" %in% val, 0.8 * "g" %in% val, 0.8 * "b" %in% val)
}
)
)
# Reactive properties -------------------------------------------------------
# Constant values, raw (not on a scale)
mtcars %>% ggvis(
x = ~wt,
y = ~mpg,
fill := input_select(c("red", "blue"), label = "Color"),
size := input_slider(10, 1000, 100, label = "Size"),
opacity := input_slider(0, 1, 1, label = "Opacity")
) %>%
layer_points()
# Constant values, on a scale
new_vals <- input_select(c("Set A" = "A", "Set B" = "B"),
label = "Dynamically-generated column",
map = function(value) {
vals <- switch(value,
"A" = rep(c("One", "Two")),
"B" = c("First", "Second", "Third", "Fourth"))
rep(vals, length = nrow(mtcars))
})
mtcars %>% ggvis(x = ~wt, y = ~mpg, fill = new_vals) %>%
layer_points()
# Variable values, raw (not on a scale)
mtc <- mtcars
mtc$colour1 <- c("red", "black")
mtc$colour2 <- c("blue", "gray")
mtc %>% ggvis(
x = ~wt,
y = ~mpg,
fill := input_select(c("colour1", "colour2"), map = as.name)
) %>%
layer_points()
# Variable values
mtcars %>% ggvis(
x = ~wt,
y = ~mpg,
fill = input_select(c("mpg", "wt"), map = as.name)
) %>%
layer_points()
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