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#' Transformed Cartesian coordinate system
#'
#' `coord_trans()` is different to scale transformations in that it occurs after
#' statistical transformation and will affect the visual appearance of geoms - there is
#' no guarantee that straight lines will continue to be straight.
#'
#' Transformations only work with continuous values: see
#' [scales::trans_new()] for list of transformations, and instructions
#' on how to create your own.
#'
#' @inheritParams coord_cartesian
#' @param x,y Transformers for x and y axes or their names.
#' @param limx,limy `r lifecycle::badge("deprecated")` use `xlim` and `ylim` instead.
#' @export
#' @examples
#' \donttest{
#' # See ?geom_boxplot for other examples
#'
#' # Three ways of doing transformation in ggplot:
#' # * by transforming the data
#' ggplot(diamonds, aes(log10(carat), log10(price))) +
#' geom_point()
#' # * by transforming the scales
#' ggplot(diamonds, aes(carat, price)) +
#' geom_point() +
#' scale_x_log10() +
#' scale_y_log10()
#' # * by transforming the coordinate system:
#' ggplot(diamonds, aes(carat, price)) +
#' geom_point() +
#' coord_trans(x = "log10", y = "log10")
#'
#' # The difference between transforming the scales and
#' # transforming the coordinate system is that scale
#' # transformation occurs BEFORE statistics, and coordinate
#' # transformation afterwards. Coordinate transformation also
#' # changes the shape of geoms:
#'
#' d <- subset(diamonds, carat > 0.5)
#'
#' ggplot(d, aes(carat, price)) +
#' geom_point() +
#' geom_smooth(method = "lm") +
#' scale_x_log10() +
#' scale_y_log10()
#'
#' ggplot(d, aes(carat, price)) +
#' geom_point() +
#' geom_smooth(method = "lm") +
#' coord_trans(x = "log10", y = "log10")
#'
#' # Here I used a subset of diamonds so that the smoothed line didn't
#' # drop below zero, which obviously causes problems on the log-transformed
#' # scale
#'
#' # With a combination of scale and coordinate transformation, it's
#' # possible to do back-transformations:
#' ggplot(diamonds, aes(carat, price)) +
#' geom_point() +
#' geom_smooth(method = "lm") +
#' scale_x_log10() +
#' scale_y_log10() +
#' coord_trans(x = scales::exp_trans(10), y = scales::exp_trans(10))
#'
#' # cf.
#' ggplot(diamonds, aes(carat, price)) +
#' geom_point() +
#' geom_smooth(method = "lm")
#'
#' # Also works with discrete scales
#' set.seed(1)
#' df <- data.frame(a = abs(rnorm(26)),letters)
#' plot <- ggplot(df,aes(a,letters)) + geom_point()
#'
#' plot + coord_trans(x = "log10")
#' plot + coord_trans(x = "sqrt")
#' }
coord_trans <- function(x = "identity", y = "identity", xlim = NULL, ylim = NULL,
limx = deprecated(), limy = deprecated(), clip = "on", expand = TRUE) {
if (lifecycle::is_present(limx)) {
deprecate_warn0("3.3.0", "coord_trans(limx)", "coord_trans(xlim)")
xlim <- limx
}
if (lifecycle::is_present(limy)) {
deprecate_warn0("3.3.0", "coord_trans(limy)", "coord_trans(ylim)")
ylim <- limy
}
# resolve transformers
if (is.character(x)) x <- as.trans(x)
if (is.character(y)) y <- as.trans(y)
ggproto(NULL, CoordTrans,
trans = list(x = x, y = y),
limits = list(x = xlim, y = ylim),
expand = expand,
clip = clip
)
}
#' @rdname ggplot2-ggproto
#' @format NULL
#' @usage NULL
#' @export
CoordTrans <- ggproto("CoordTrans", Coord,
is_free = function() TRUE,
distance = function(self, x, y, panel_params) {
max_dist <- dist_euclidean(panel_params$x.range, panel_params$y.range)
dist_euclidean(self$trans$x$transform(x), self$trans$y$transform(y)) / max_dist
},
backtransform_range = function(self, panel_params) {
list(
x = self$trans$x$inverse(panel_params$x.range),
y = self$trans$y$inverse(panel_params$y.range)
)
},
range = function(self, panel_params) {
list(
x = panel_params$x.range,
y = panel_params$y.range
)
},
transform = function(self, data, panel_params) {
# trans_x() and trans_y() needs to keep Inf values because this can be called
# in guide_transform.axis()
trans_x <- function(data) {
idx <- !is.infinite(data)
data[idx] <- transform_value(self$trans$x, data[idx], panel_params$x.range)
data
}
trans_y <- function(data) {
idx <- !is.infinite(data)
data[idx] <- transform_value(self$trans$y, data[idx], panel_params$y.range)
data
}
new_data <- transform_position(data, trans_x, trans_y)
warn_new_infinites(data$x, new_data$x, "x")
warn_new_infinites(data$y, new_data$y, "y")
transform_position(new_data, squish_infinite, squish_infinite)
},
setup_panel_params = function(self, scale_x, scale_y, params = list()) {
c(
view_scales_from_scale_with_coord_trans(scale_x, self$limits$x, self$trans$x, self$expand),
view_scales_from_scale_with_coord_trans(scale_y, self$limits$y, self$trans$y, self$expand)
)
},
render_bg = function(panel_params, theme) {
guide_grid(
theme,
panel_params$x.minor,
panel_params$x.major,
panel_params$y.minor,
panel_params$y.major
)
},
render_axis_h = function(panel_params, theme) {
list(
top = panel_guides_grob(panel_params$guides, position = "top", theme = theme),
bottom = panel_guides_grob(panel_params$guides, position = "bottom", theme = theme)
)
},
render_axis_v = function(panel_params, theme) {
list(
left = panel_guides_grob(panel_params$guides, position = "left", theme = theme),
right = panel_guides_grob(panel_params$guides, position = "right", theme = theme)
)
}
)
transform_value <- function(trans, value, range) {
if (is.null(value))
return(value)
rescale(trans$transform(value), 0:1, range)
}
# TODO: can we merge this with view_scales_from_scale()?
view_scales_from_scale_with_coord_trans <- function(scale, coord_limits, trans, expand = TRUE) {
expansion <- default_expansion(scale, expand = expand)
scale_trans <- scale$trans %||% identity_trans()
coord_limits <- coord_limits %||% scale_trans$inverse(c(NA, NA))
scale_limits <- scale$get_limits()
if (scale$is_discrete()) {
continuous_ranges <- expand_limits_discrete_trans(
scale_limits,
expansion,
coord_limits,
trans,
range_continuous = scale$range_c$range
)
} else {
# transform user-specified limits to scale transformed space
coord_limits <- scale$trans$transform(coord_limits)
continuous_ranges <- expand_limits_continuous_trans(
scale_limits,
expansion,
coord_limits,
trans
)
}
# calculate break information
out <- scale$break_info(continuous_ranges$continuous_range)
# range in coord space has already been calculated
# needs to be in increasing order for transform_value() to work
out$range <- range(continuous_ranges$continuous_range_coord)
# major and minor values in coordinate data
out$major_source <- transform_value(trans, out$major_source, out$range)
out$minor_source <- transform_value(trans, out$minor_source, out$range)
out$sec.major_source <- transform_value(trans, out$sec.major_source, out$range)
out$sec.minor_source <- transform_value(trans, out$sec.minor_source, out$range)
out <- list(
# Note that a ViewScale requires a limit and a range that are before the
# Coord's transformation, so we pass `continuous_range`, not `continuous_range_coord`.
view_scale_primary(scale, scale_limits, continuous_ranges$continuous_range),
sec = view_scale_secondary(scale, scale_limits, continuous_ranges$continuous_range),
range = out$range,
labels = out$labels,
major = out$major_source,
minor = out$minor_source,
sec.labels = out$sec.labels,
sec.major = out$sec.major_source,
sec.minor = out$sec.minor_source
)
aesthetic <- scale$aesthetics[1]
names(out) <- c(aesthetic, paste(aesthetic, names(out)[-1], sep = "."))
out
}
#' Generate warning when finite values are transformed into infinite values
#'
#' @param old_values A vector of pre-transformation values.
#' @param new_values A vector of post-transformation values.
#' @param axis Which axis the values originate from (e.g. x, y).
#' @noRd
warn_new_infinites <- function(old_values, new_values, axis, call = caller_env()) {
if (any(is.finite(old_values) & !is.finite(new_values))) {
cli::cli_warn("Transformation introduced infinite values in {axis}-axis", call = call)
}
}
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