Create plotlyreference text Returns a list text you can pass to the annotations argument of plotly::layout()

Create plotlyreference text Returns a list text you can pass to the annotations argument of plotly::layout()

reference_text(
  threshold,
  reference = 0,
  offset,
  text = c("reference", "important decrease", "important increase")
)

Arguments

threshold

A vector of either 1 or 2 thresholds. A single threshold will be transformed into reference + c(-abs(threshold), abs(threshold)).

reference

The null hypothesis. Defaults to 0.

offset

An numeric vector with the offset between text and the lines. In units of the y variable. Defaults to 10% of the difference between reference and threshold.

text

A character vector with three elements with the text to display on the reference line, bottom threshold line and upper threshold line. Defaults to c("reference", "important decrease", "important increase").

See also

Other plotly add-ons: add_classification(), add_fan(), reference_shape()

Examples

# All possible classes
z <- data.frame(
  estimate = c(-0.5, 0, 0.5, 1.5, 1, 0.5, 0, -0.5, -1, -1.5),
  sd = c(rep(0.8, 3), rep(0.3, 7))
)
z$lcl <- qnorm(0.05, z$estimate, z$sd)
z$ucl <- qnorm(0.95, z$estimate, z$sd)
classification(z$lcl, z$ucl, threshold = 1) -> z$effect
c(
  "?" = "unknown\neffect", "?+" = "potential\npositive\neffect",
  "?-" = "potential\nnegative\neffect", "~" = "no effect",
  "+" = "positive\neffect", "-" = "negative\neffect",
  "+~" = "moderate\npositive\neffect", "-~" = "moderate\nnegative\neffect",
  "++" = "strong\npositive\neffect", "--" = "strong\nnegative\neffect"
)[as.character(z$effect)] -> z$x
z$x <- factor(z$x, z$x)
z$display <- paste(
  "estimate:", format_ci(z$estimate, lcl = z$lcl, ucl = z$ucl)
)

# Simulated trend
set.seed(20190521)
base_year <- 2000
n_year <- 20
trend <- data.frame(
  dt = seq_len(n_year),
  change = rnorm(n_year, sd = 0.2),
  sd = rnorm(n_year, mean = 0.1, sd = 0.01)
)
trend$index <- cumsum(trend$change)
trend$lcl <- qnorm(0.025, trend$index, trend$sd)
trend$ucl <- qnorm(0.975, trend$index, trend$sd)
trend$year <- base_year + trend$dt
trend$display <- paste(
  "index:", format_ci(trend$index, lcl = trend$lcl, ucl = trend$ucl)
)
th <- 0.25
ref <- 0
library(plotly)
plot_ly(z, x = ~x, y = ~estimate) |>
  add_fan(sd = ~sd, text = ~display) |>
  add_classification(lcl = ~lcl, ucl = ~ucl, threshold = 1) |>
  layout(
    hovermode = "x unified",
    shapes = reference_shape(threshold = 1),
    annotations = reference_text(threshold = 1)
  )

plot_ly(z, x = ~x, y = ~estimate) |>
  add_fan(sd = ~sd, step = 0.1, text = ~display) |>
  add_classification(
    lcl = ~lcl, ucl = ~ucl, threshold = 1, detailed = FALSE
   ) |>
  layout(
    shapes = reference_shape(threshold = 1, line = TRUE),
    annotations = reference_text(threshold = 1)
   )

plot_ly(z, x = ~x, y = ~estimate) |>
  add_fan(sd = ~sd, step = 0.2, hoverinfo = "none") |>
  add_classification(
    lcl = ~lcl, ucl = ~ucl, threshold = 1, signed = FALSE
  ) |>
  layout(shapes = reference_shape(threshold = 1))

plot_ly(z, x = ~x, y = ~estimate) |>
  add_fan(sd = ~sd, step = 0.3) |>
  add_classification(
    lcl = ~lcl, ucl = ~ucl, threshold = 1, detailed = FALSE, signed = FALSE,
    text = ~display
  ) |>
  layout(
    shapes = reference_shape(threshold = 1, line = TRUE)
  )


# trend
plot_ly(data = trend, x = ~year, y = ~index) |>
  add_fan(sd = ~sd, text = ~display, hoverinfo = "text") |>
  add_classification(sd = ~sd, threshold = th) |>
  layout(
    hovermode = "x unified", hoverdistance = 1,
    shapes = reference_shape(threshold = th, reference = ref),
    annotations = reference_text(threshold = th, reference = ref)
  )