Package 'gg.layers' reference manual

Title:	ggplot layers
Description:	What the package does (one paragraph).
Authors:	Dongdong Kong [aut, cre] (ORCID: <https://orcid.org/0000-0003-1836-8172>)
Maintainer:	Dongdong Kong <[email protected]>
License:	GPL (>= 3)
Version:	0.1.3
Built:	2026-05-28 06:39:32 UTC
Source:	https://github.com/rpkgs/gg.layers

add_colorbar

Description

add_colorbar

Usage

add_colorbar(
  p,
  g,
  width = NULL,
  height = NULL,
  title = NULL,
  space = "right",
  legend.title = element_text(hjust = 0, vjust = 0, size = 14, family = "Times")
)
add_colorbar(
  p,
  g,
  width = NULL,
  height = NULL,
  title = NULL,
  space = "right",
  legend.title = element_text(hjust = 0, vjust = 0, size = 14, family = "Times")
)

Arguments

p

a ggplot object

g

a grob object, colorbar

width, height

width and height of the colorbar

title

all title elements: plot, axes, legends (element_text(); inherits from text)

space

one of c("left", "bottom")

legend.title

title of legend (element_text(); inherits from title)

add grob to a plot

Description

add grob to a plot

Usage

add_grob(p, ..., ggplot = TRUE)
add_grob(p, ..., ggplot = TRUE)

Arguments

p

ggplot object

...

grob objects

ggplot

logical, if TRUE, return a ggplot object

Examples

library(ggplot2)
library(grid)

p <- ggplot(mtcars, aes(mpg, disp)) +
  geom_point() +
  facet_wrap(~cyl)
g1 <- textGrob("hello",
  x = 0.98, y = 0.1, hjust = 1, vjust = 0,
  gp = gpar(fontfamily = "Times"))
g2 <- element_grob_text(element_text(family = "Times", hjust = 1, vjust = 0, size = 12),
  label = "Hello world", x = 0.98, y = 0.2)

add_grob(p, g1, g2)
add_grob(p, g1) %>% add_grob(g2)
library(ggplot2)
library(grid)

p <- ggplot(mtcars, aes(mpg, disp)) +
  geom_point() +
  facet_wrap(~cyl)
g1 <- textGrob("hello",
  x = 0.98, y = 0.1, hjust = 1, vjust = 0,
  gp = gpar(fontfamily = "Times"))
g2 <- element_grob_text(element_text(family = "Times", hjust = 1, vjust = 0, size = 12),
  label = "Hello world", x = 0.98, y = 0.2)

add_grob(p, g1, g2)
add_grob(p, g1) %>% add_grob(g2)

colourbar_triangle

Description

colourbar_triangle

Usage

colourbar_triangle(...)
colourbar_triangle(...)

Arguments

...

parameters passed to ggplot2::guide_colourbar

References

https://stackoverflow.com/questions/68440366/how-can-i-add-triangles-to-a-ggplot2-colorbar-in-r-to-indicate-out-of-bound-valu

Examples

library(ggplot2)

g <- ggplot(mtcars, aes(mpg, wt)) +
  geom_point(aes(colour = drat))

g + scale_colour_viridis_c(
  limits = c(3, 5), oob = scales::oob_squish,
  guide = colourbar_triangle()
)
library(ggplot2)

g <- ggplot(mtcars, aes(mpg, wt)) +
  geom_point(aes(colour = drat))

g + scale_colour_viridis_c(
  limits = c(3, 5), oob = scales::oob_squish,
  guide = colourbar_triangle()
)

draw horizontal and vertical polygons

Description

draw horizontal and vertical polygons

Usage

draw_polygon(
  vals,
  x = NULL,
  type = "horizontal",
  length.out = 10000,
  col.regions = c("blue", "red"),
  alpha = 0.6,
  zlim = c(-Inf, Inf),
  ...
)
draw_polygon(
  vals,
  x = NULL,
  type = "horizontal",
  length.out = 10000,
  col.regions = c("blue", "red"),
  alpha = 0.6,
  zlim = c(-Inf, Inf),
  ...
)

Arguments

vals

numeric vector

x

The corresponding x position of vals

type

one of "horizontal" or "vertical"

length.out

the length of interpolated vals and x

col.regions

A vector of colors, or a function to produce a vecor of colors, to be used if region=TRUE. Each interval defined by at is assigned a color, so the number of colors actually used is one less than the length of at. See level.colors for details on how the color assignment is done.

alpha

the alpha of polygon's fill color

zlim

limits of vals

...

Extra parameters.

Examples

set.seed(1)
y <- rnorm(10)
x <- seq_along(y)
set.seed(1)
y <- rnorm(10)
x <- seq_along(y)

geom_annotation

Description

geom_annotation

Usage

geom_annotation(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  xmin = 0,
  xmax = 0.5,
  ymin = 0,
  ymax = 0.5,
  just = c(0, 0),
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = FALSE
)
geom_annotation(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  xmin = 0,
  xmax = 0.5,
  ymin = 0,
  ymax = 0.5,
  just = c(0, 0),
  ...,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = FALSE
)

Arguments

mapping

Set of aesthetic mappings created by aes(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

A tibble with the column of grob

stat

The statistical transformation to use on the data for this layer. When using a ⁠geom_*()⁠ function to construct a layer, the stat argument can be used to override the default coupling between geoms and stats. The stat argument accepts the following:

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

xmin, xmax

x location (in data coordinates) giving horizontal location of raster

ymin, ymax

y location (in data coordinates) giving vertical location of raster

just

A string or numeric vector specifying the justification of the viewport relative to its (x, y) location. If there are two values, the first value specifies horizontal justification and the second value specifies vertical justification. Possible string values are: "left", "right", "centre", "center", "bottom", and "top". For numeric values, 0 means left alignment and 1 means right alignment.

...

Other arguments passed on to layer()'s params argument. These arguments broadly fall into one of 4 categories below. Notably, further arguments to the position argument, or aesthetics that are required can not be passed through .... Unknown arguments that are not part of the 4 categories below are ignored.

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes. It can also be a named logical vector to finely select the aesthetics to display. To include legend keys for all levels, even when no data exists, use TRUE. If NA, all levels are shown in legend, but unobserved levels are omitted.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g. annotation_borders().

Examples

## make plot
library(ggplot2)
d <- data.frame(x = 1:3, y = 1:3,
                varname = c("T_min", "T_max", "T_avg"))
p = ggplot(d, aes(x, y)) +
  geom_point() +
  geom_richtext(aes(label = varname), x = 2, y = 2) +
  facet_wrap(~varname, labeller = label_mk) +
  theme(
    strip.text = element_markdown(face = "bold", margin = margin(t = 1, b = 0))
  )

## make legend
brks = 1:5 %>% c(-Inf, ., Inf)
nbrk <- length(brks) - 1
cols <- rcolors::get_color("amwg256", nbrk)
g = make_colorbar(brks, col = cols, space = "right")
d_lgd = tibble(varname = d$varname, grob = rep(list(g), 3))

## add legend to each panel
p2 = p + geom_annotation(data = d_lgd, aes(grob = grob), xmin = 0.8, xmax = 1, ymax = 1)
p2
## make plot
library(ggplot2)
d <- data.frame(x = 1:3, y = 1:3,
                varname = c("T_min", "T_max", "T_avg"))
p = ggplot(d, aes(x, y)) +
  geom_point() +
  geom_richtext(aes(label = varname), x = 2, y = 2) +
  facet_wrap(~varname, labeller = label_mk) +
  theme(
    strip.text = element_markdown(face = "bold", margin = margin(t = 1, b = 0))
  )

## make legend
brks = 1:5 %>% c(-Inf, ., Inf)
nbrk <- length(brks) - 1
cols <- rcolors::get_color("amwg256", nbrk)
g = make_colorbar(brks, col = cols, space = "right")
d_lgd = tibble(varname = d$varname, grob = rep(list(g), 3))

## add legend to each panel
p2 = p + geom_annotation(data = d_lgd, aes(grob = grob), xmin = 0.8, xmax = 1, ymax = 1)
p2

geom_annotation

Description

geom_annotation

Usage

geom_annotation_func(
  mapping = NULL,
  data = NULL,
  plot.fun = NULL,
  ...,
  x = 0,
  y = 0,
  width = unit(0.5, "npc"),
  height = unit(0.5, "npc"),
  just = c(0, 0)
)
geom_annotation_func(
  mapping = NULL,
  data = NULL,
  plot.fun = NULL,
  ...,
  x = 0,
  y = 0,
  width = unit(0.5, "npc"),
  height = unit(0.5, "npc"),
  just = c(0, 0)
)

Arguments

mapping

data

A tibble with the column of grob

plot.fun

function to plot, p <- plot.fun(data, ...)

...

other parameters to plot.fun

x

A numeric vector or unit object specifying x-location.

y

A numeric vector or unit object specifying y-location.

width

A numeric vector or unit object specifying width.

height

A numeric vector or unit object specifying height.

just

Examples

## prepare data
library(gg.layers)
library(ggplot2)
library(rcolors)

data("d_trendPerc")
d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) %>% as_tibble()
n <- nrow(d_mask) * 2
dat <- rbind(cbind(type = "a", d_mask), cbind(type = "b", d_mask)) %>%
  mutate(val = rnorm(n))

brks <- seq(0.9, 1, 0.025)
nbrk <- length(brks) - 1
cols <- get_color(rcolors$amwg256, nbrk)

## option1
# the part of not significant
ggplot(data = dat, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  layer_barchart(aes(z = val),
    width = unit(0.3, "npc"),
    height = unit(0.3, "npc"),
    brks = brks, cols = cols
  ) +
  facet_wrap(~type)

## option2
func <- function(data, ...) {
  add_barchart(data$z, brks, cols, ...)
}

ggplot(data = dat, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_annotation_func(aes(z = val), plot.fun = func) +
  facet_wrap(~type)
## prepare data
library(gg.layers)
library(ggplot2)
library(rcolors)

data("d_trendPerc")
d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) %>% as_tibble()
n <- nrow(d_mask) * 2
dat <- rbind(cbind(type = "a", d_mask), cbind(type = "b", d_mask)) %>%
  mutate(val = rnorm(n))

brks <- seq(0.9, 1, 0.025)
nbrk <- length(brks) - 1
cols <- get_color(rcolors$amwg256, nbrk)

## option1
# the part of not significant
ggplot(data = dat, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  layer_barchart(aes(z = val),
    width = unit(0.3, "npc"),
    height = unit(0.3, "npc"),
    brks = brks, cols = cols
  ) +
  facet_wrap(~type)

## option2
func <- function(data, ...) {
  add_barchart(data$z, brks, cols, ...)
}

ggplot(data = dat, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_annotation_func(aes(z = val), plot.fun = func) +
  facet_wrap(~type)

A box and whiskers plot (in the style of Tukey)

Description

The boxplot compactly displays the distribution of a continuous variable. It visualises five summary statistics (the median, two hinges and two whiskers), and all "outlying" points individually.

Usage

geom_boxplot2(
  mapping = NULL,
  data = NULL,
  stat = "boxplot",
  position = "dodge2",
  ...,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  show.errorbar = TRUE,
  width.errorbar = 0.7,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_boxplot2(
  mapping = NULL,
  data = NULL,
  stat = "boxplot",
  position = "dodge2",
  ...,
  outlier.colour = NULL,
  outlier.color = NULL,
  outlier.fill = NULL,
  outlier.shape = 19,
  outlier.size = 1.5,
  outlier.stroke = 0.5,
  outlier.alpha = NULL,
  show.errorbar = TRUE,
  width.errorbar = 0.7,
  notch = FALSE,
  notchwidth = 0.5,
  varwidth = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

A function will be called with a single argument, the plot data. The return value must be a data.frame, and will be used as the layer data. A function can be created from a formula (e.g. ~ head(.x, 10)).

stat

the statistical transformation to use on the data for this layer

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

outlier.colour, outlier.color, outlier.fill, outlier.shape, outlier.size, outlier.stroke, outlier.alpha

Default aesthetics for outliers. Set to NULL to inherit from the data's aesthetics.

show.errorbar

whether to show errorbar (default TRUE)

width.errorbar

the width of errorbar (default 0.7)

notch

If FALSE (default) make a standard box plot. If TRUE, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this suggests that the medians are significantly different.

notchwidth

For a notched box plot, width of the notch relative to the body (defaults to notchwidth = 0.5).

varwidth

If FALSE (default) make a standard box plot. If TRUE, boxes are drawn with widths proportional to the square-roots of the number of observations in the groups (possibly weighted, using the weight aesthetic).

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Aesthetics

geom_boxplot() understands the following aesthetics. Required aesthetics are displayed in bold and defaults are displayed for optional aesthetics:

•	`x` or `y`
•	`lower` or `xlower`
•	`upper` or `xupper`
•	`middle` or `xmiddle`
•	`ymin` or `xmin`
•	`ymax` or `xmax`
•	`alpha`	→ `NA`
•	`colour`	→ via `theme()`
•	`fill`	→ via `theme()`
•	`group`	→ inferred
•	`linetype`	→ via `theme()`
•	`linewidth`	→ via `theme()`
•	`shape`	→ via `theme()`
•	`size`	→ via `theme()`
•	`weight`	→ `1`
•	`width`	→ `0.9`

Learn more about setting these aesthetics in vignette("ggplot2-specs").

Summary statistics

The lower and upper hinges correspond to the first and third quartiles (the 25th and 75th percentiles). This differs slightly from the method used by the boxplot() function, and may be apparent with small samples. See boxplot.stats() for more information on how hinge positions are calculated for boxplot().

The upper whisker extends from the hinge to the largest value no further than 1.5 * IQR from the hinge (where IQR is the inter-quartile range, or distance between the first and third quartiles). The lower whisker extends from the hinge to the smallest value at most 1.5 * IQR of the hinge. Data beyond the end of the whiskers are called "outlying" points and are plotted individually.

In a notched box plot, the notches extend 1.58 * IQR / sqrt(n). This gives a roughly 95% confidence interval for comparing medians. See McGill et al. (1978) for more details.

References

McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 12-16.

Examples

library(ggplot2)

p <- ggplot(mpg, aes(class, hwy))
p + geom_boxplot2()
p + geom_boxplot2(width.errorbar = 0.5)
p + geom_boxplot2(width = 0.5)
# Orientation follows the discrete axis
# ggplot(mpg, aes(hwy, class)) + geom_boxplot2()

p + geom_boxplot2(notch = TRUE)
p + geom_boxplot2(varwidth = TRUE)
p + geom_boxplot2(fill = "white", colour = "#3366FF")
# By default, outlier points match the colour of the box. Use
# outlier.colour to override
p + geom_boxplot2(outlier.colour = "red", outlier.shape = 1)
# Remove outliers when overlaying boxplot with original data points
p + geom_boxplot2(outlier.shape = NA) + geom_jitter(width = 0.2)

# Boxplots are automatically dodged when any aesthetic is a factor
p + geom_boxplot2(aes(colour = drv))

# You can also use boxplots with continuous x, as long as you supply
# a grouping variable. cut_width is particularly useful
# ggplot(diamonds, aes(carat, price)) +
#   geom_boxplot2()
# ggplot(diamonds, aes(carat, price)) +
#   geom_boxplot2(aes(group = cut_width(carat, 0.25)))
# Adjust the transparency of outliers using outlier.alpha
# ggplot(diamonds, aes(carat, price)) +
#   geom_boxplot2(aes(group = cut_width(carat, 0.25)), outlier.alpha = 0.1)

# It's possible to draw a boxplot with your own computations if you
# use stat = "identity":
y <- rnorm(100)
df <- data.frame(
  x = 1,
  y0 = min(y),
  y25 = quantile(y, 0.25),
  y50 = median(y),
  y75 = quantile(y, 0.75),
  y100 = max(y)
)
ggplot(df, aes(x)) +
  geom_boxplot2(
   aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
   stat = "identity"
 )
library(ggplot2)

p <- ggplot(mpg, aes(class, hwy))
p + geom_boxplot2()
p + geom_boxplot2(width.errorbar = 0.5)
p + geom_boxplot2(width = 0.5)
# Orientation follows the discrete axis
# ggplot(mpg, aes(hwy, class)) + geom_boxplot2()

p + geom_boxplot2(notch = TRUE)
p + geom_boxplot2(varwidth = TRUE)
p + geom_boxplot2(fill = "white", colour = "#3366FF")
# By default, outlier points match the colour of the box. Use
# outlier.colour to override
p + geom_boxplot2(outlier.colour = "red", outlier.shape = 1)
# Remove outliers when overlaying boxplot with original data points
p + geom_boxplot2(outlier.shape = NA) + geom_jitter(width = 0.2)

# Boxplots are automatically dodged when any aesthetic is a factor
p + geom_boxplot2(aes(colour = drv))

# You can also use boxplots with continuous x, as long as you supply
# a grouping variable. cut_width is particularly useful
# ggplot(diamonds, aes(carat, price)) +
#   geom_boxplot2()
# ggplot(diamonds, aes(carat, price)) +
#   geom_boxplot2(aes(group = cut_width(carat, 0.25)))
# Adjust the transparency of outliers using outlier.alpha
# ggplot(diamonds, aes(carat, price)) +
#   geom_boxplot2(aes(group = cut_width(carat, 0.25)), outlier.alpha = 0.1)

# It's possible to draw a boxplot with your own computations if you
# use stat = "identity":
y <- rnorm(100)
df <- data.frame(
  x = 1,
  y0 = min(y),
  y25 = quantile(y, 0.25),
  y50 = median(y),
  y75 = quantile(y, 0.75),
  y100 = max(y)
)
ggplot(df, aes(x)) +
  geom_boxplot2(
   aes(ymin = y0, lower = y25, middle = y50, upper = y75, ymax = y100),
   stat = "identity"
 )

geom_hspan

Description

xmin, xmax
ymin, ymax: optional

Usage

geom_hspan(
  mapping = NULL,
  data = NULL,
  stat = "hspan",
  position = "identity",
  ...,
  ymin = -Inf,
  ymax = Inf,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_hspan(
  mapping = NULL,
  data = NULL,
  stat = "hspan",
  position = "identity",
  ...,
  ymin = -Inf,
  ymax = Inf,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Examples

library(ggplot2)
library(data.table)

d = data.table(x = 1:10, y = 1:10)
d_span = data.table(xmin = c(1, 4), xmax = c(3, 5), group = 1:2)

ggplot(d, aes(x, y)) + 
  geom_point() + 
  geom_hspan(data = d_span, aes(x = NULL, y = NULL, xmin = xmin, xmax = xmax, group = group), 
    alpha = 0.2, fill = "yellow")
library(ggplot2)
library(data.table)

d = data.table(x = 1:10, y = 1:10)
d_span = data.table(xmin = c(1, 4), xmax = c(3, 5), group = 1:2)

ggplot(d, aes(x, y)) + 
  geom_point() + 
  geom_hspan(data = d_span, aes(x = NULL, y = NULL, xmin = xmin, xmax = xmax, group = group), 
    alpha = 0.2, fill = "yellow")

geom_latFreq

Description

geom_latFreq

Usage

geom_latFreq(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  options = list(),
  bbox = c(185, 240, -60, 90),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_latFreq(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  options = list(),
  bbox = c(185, 240, -60, 90),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

options

parameters of make_latFreq()

bbox

bounding box of the plot, in the form of c(xmin, xmax, ymin, ymax).

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Examples

library(ggplot2)
# the lattice version: https://github.com/CUG-hydro/Liu2021-JGRA-ET_trends_attribution

# f <- "data-raw/AridityIndex_MSWEP-prcp_div_GLEAM-Ep_1980-2020.tif"
# r <- terra::rast(f)
# d <- as.data.table(r, xy = TRUE) |> set_names(c("x", "y", "z"))
d = AridityIndex

# make_latFreq(d$y, d$z, debug = TRUE, zlim = c(-2, 2), is_spatial = TRUE)
# brks <- c(-Inf, 0.05, 0.2, 0.5, 0.65, Inf)
brks <- c(-Inf, 0.05, 0.2, 0.5, 0.65, 1:5, 20, Inf)

nbrk <- length(brks) - 1
cols <- rcolors::get_color("amwg256", nbrk) |> rev()

p = ggplot(d, aes(x, y, z = z)) + 
  geom_raster_filled(breaks = brks) + 
  geom_latFreq(options = list(is_spatial = TRUE, zlim = c(-1, 1)*10), 
    bbox = c(190, 240, -60, 90)) + 
  coord_cartesian(xlim = c(-180, 240), ylim = c(-60, 90), expand = FALSE, clip = "on") +
  scale_x_continuous(limits = c(-180, 240), breaks = seq(-180, 180, 60)) + 
  scale_fill_manual(values =cols) + 
  labs(x = NULL, y = NULL)
p
library(ggplot2)
# the lattice version: https://github.com/CUG-hydro/Liu2021-JGRA-ET_trends_attribution

# f <- "data-raw/AridityIndex_MSWEP-prcp_div_GLEAM-Ep_1980-2020.tif"
# r <- terra::rast(f)
# d <- as.data.table(r, xy = TRUE) |> set_names(c("x", "y", "z"))
d = AridityIndex

# make_latFreq(d$y, d$z, debug = TRUE, zlim = c(-2, 2), is_spatial = TRUE)
# brks <- c(-Inf, 0.05, 0.2, 0.5, 0.65, Inf)
brks <- c(-Inf, 0.05, 0.2, 0.5, 0.65, 1:5, 20, Inf)

nbrk <- length(brks) - 1
cols <- rcolors::get_color("amwg256", nbrk) |> rev()

p = ggplot(d, aes(x, y, z = z)) + 
  geom_raster_filled(breaks = brks) + 
  geom_latFreq(options = list(is_spatial = TRUE, zlim = c(-1, 1)*10), 
    bbox = c(190, 240, -60, 90)) + 
  coord_cartesian(xlim = c(-180, 240), ylim = c(-60, 90), expand = FALSE, clip = "on") +
  scale_x_continuous(limits = c(-180, 240), breaks = seq(-180, 180, 60)) + 
  scale_fill_manual(values =cols) + 
  labs(x = NULL, y = NULL)
p

geom_mk

Description

geom_mk

Usage

geom_mk(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  fun_slope = slope_mk,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_mk(
  mapping = NULL,
  data = NULL,
  geom = "abline",
  position = "identity",
  fun_slope = slope_mk,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

stat_spike(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  halfwin = 3,
  sd.times = 3,
  trs = NA,
  verbose = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)
geom_mk(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  fun_slope = slope_mk,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_mk(
  mapping = NULL,
  data = NULL,
  geom = "abline",
  position = "identity",
  fun_slope = slope_mk,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

stat_spike(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  halfwin = 3,
  sd.times = 3,
  trs = NA,
  verbose = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes().

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

fun_slope

function to calculate slope, default rtrend::slope_mk()

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Value

No return. This function is used to calculate data for gglot2 ⁠geom_*⁠, just like ggplot2::stat_smooth().

Examples

library(ggplot2)
library(rtrend)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  stat_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  geom_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)
library(ggplot2)
library(rtrend)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  stat_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  geom_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)
library(ggplot2)
library(rtrend)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  stat_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  geom_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)
library(ggplot2)
library(rtrend)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  stat_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)

ggplot(mpg, aes(displ, hwy, colour = drv)) +
  geom_point() +
  geom_mk(linewidth = 1, fun_slope = slope_mk) +
  geom_smooth(method = "lm", se = FALSE, linetype = 2)

geom_movmean

Description

geom_movmean

Usage

geom_movmean(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  halfwin = 3,
  show.diff = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_movmean(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  halfwin = 3,
  show.diff = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

halfwin

halfwin of movmean, rtrend::movmean()

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Examples

library(data.table)
library(ggplot2)
data("GPP_US_MMS")
dat = melt(GPP_US_MMS[, .(date, SM, GPP)], "date")

ggplot(dat, aes(date, value)) + 
  geom_line() + 
  geom_movmean(halfwin = 5, linewidth = 1, alpha = 0.7, color = "pink") + 
  # geom_movmean(halfwin = 5, show.diff=TRUE, linewidth = 0.2, alpha = 0.7, color = "red") + 
  geom_spike(halfwin = 2, sd.times = 6, color = "red", verbose = TRUE) +
  # geom_spike(halfwin = 5, trs = 3, color = "blue") +
  facet_wrap(~variable, scales = "free_y") 
library(data.table)
library(ggplot2)
data("GPP_US_MMS")
dat = melt(GPP_US_MMS[, .(date, SM, GPP)], "date")

ggplot(dat, aes(date, value)) + 
  geom_line() + 
  geom_movmean(halfwin = 5, linewidth = 1, alpha = 0.7, color = "pink") + 
  # geom_movmean(halfwin = 5, show.diff=TRUE, linewidth = 0.2, alpha = 0.7, color = "red") + 
  geom_spike(halfwin = 2, sd.times = 6, color = "red", verbose = TRUE) +
  # geom_spike(halfwin = 5, trs = 3, color = "blue") +
  facet_wrap(~variable, scales = "free_y")

Draw precipitation bar on the top of the panel

Description

Draw precipitation bar on the top of the panel

Usage

geom_prcpRunoff(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  linejoin = "mitre",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  prcp.ratio = 0.5,
  params_prcp = list(),
  prcp.coef = 1,
  qmax = NULL,
  sec.axis = NULL,
  sec.name = "Precipitation (mm)"
)
geom_prcpRunoff(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  linejoin = "mitre",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  prcp.ratio = 0.5,
  params_prcp = list(),
  prcp.coef = 1,
  qmax = NULL,
  sec.axis = NULL,
  sec.name = "Precipitation (mm)"
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

linejoin

Line join style (round, mitre, bevel).

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

prcp.ratio

the ratio of precipitation to ymax (not used currently)

params_prcp

color: color of precipitation
fill: fill of precipitation

prcp.coef

coefficient of precipitation, y_new = qmax - prcp * prcp.coef prcp.coef = qmax / max(prcp)

qmax

maximum of streamflow, used to calculate prcp.coef

sec.axis

secondary axis for precipitation, returned by ggplot2::sec_axis()

sec.name

name of secondary axis

Aesthetics

x: date or continuous variable
y: runoff
prcp: precipitation

Author(s)

Xie YuXuan and Dongdong Kong

Examples

library(ggplot2)

col_prcp = "blue"  #"#3e89be"
col_runoff = "black"  # "darkorange"

my_theme <-
  theme_dual_axis(col_runoff, col_prcp) +
  theme(
    legend.position.inside = c(0, 1),
    legend.justification = c(0, 1),
    legend.background = element_blank(),
    legend.key = element_blank(),
    # axis.ticks = element_blank(),
    axis.text = element_text(color = "black"),
    axis.text.x = element_text(angle = 60, hjust = 1),
    strip.background = element_blank(),
    strip.text = element_text(face = "bold", hjust = 0)
  )

## Visualization ---------------------------------------------------------------
dat <- runoff_data
qmax <- max(dat$Q) * 1.1
prcp.coef <- guess_prcp_coef(qmax, dat$prcp, ratio = 0.5)
# prcp.coef = qmax / pmax * ratio

ggplot(dat, aes(x = time, Q)) +
  # theme_test() +
  geom_line() +
  geom_prcpRunoff(
    aes(prcp = prcp, color = flood_type),
    params_prcp = list(color = col_prcp, fill = col_prcp),
    prcp.coef = prcp.coef,
    qmax = qmax,
    color = col_runoff, linewidth = 0.5
  ) +
  facet_wrap(~flood_type, scales = "free") +
  # scale_y_precipitation(sec.name = "Precipitation (mm)", coef = set_coef) +
  scale_x_datetime(date_labels = "%m/%d") +
  my_theme +
  labs(x = "Date", y = expression("Streamflow (m"^"3" * "/s)"))
library(ggplot2)

col_prcp = "blue"  #"#3e89be"
col_runoff = "black"  # "darkorange"

my_theme <-
  theme_dual_axis(col_runoff, col_prcp) +
  theme(
    legend.position.inside = c(0, 1),
    legend.justification = c(0, 1),
    legend.background = element_blank(),
    legend.key = element_blank(),
    # axis.ticks = element_blank(),
    axis.text = element_text(color = "black"),
    axis.text.x = element_text(angle = 60, hjust = 1),
    strip.background = element_blank(),
    strip.text = element_text(face = "bold", hjust = 0)
  )

## Visualization ---------------------------------------------------------------
dat <- runoff_data
qmax <- max(dat$Q) * 1.1
prcp.coef <- guess_prcp_coef(qmax, dat$prcp, ratio = 0.5)
# prcp.coef = qmax / pmax * ratio

ggplot(dat, aes(x = time, Q)) +
  # theme_test() +
  geom_line() +
  geom_prcpRunoff(
    aes(prcp = prcp, color = flood_type),
    params_prcp = list(color = col_prcp, fill = col_prcp),
    prcp.coef = prcp.coef,
    qmax = qmax,
    color = col_runoff, linewidth = 0.5
  ) +
  facet_wrap(~flood_type, scales = "free") +
  # scale_y_precipitation(sec.name = "Precipitation (mm)", coef = set_coef) +
  scale_x_datetime(date_labels = "%m/%d") +
  my_theme +
  labs(x = "Date", y = expression("Streamflow (m"^"3" * "/s)"))

geom_raster_filled

Description

geom_raster_filled

Usage

geom_raster_filled(
  mapping = NULL,
  data = NULL,
  stat = "raster_filled",
  position = "identity",
  ...,
  breaks = NULL,
  hjust = 0.5,
  vjust = 0.5,
  interpolate = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_raster_filled(
  mapping = NULL,
  data = NULL,
  geom = "raster",
  position = "identity",
  ...,
  breaks = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_raster_filled(
  mapping = NULL,
  data = NULL,
  stat = "raster_filled",
  position = "identity",
  ...,
  breaks = NULL,
  hjust = 0.5,
  vjust = 0.5,
  interpolate = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_raster_filled(
  mapping = NULL,
  data = NULL,
  geom = "raster",
  position = "identity",
  ...,
  breaks = NULL,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

breaks

One of:

Numeric vector to set the contour breaks
A function that takes the range of the data and binwidth as input and returns breaks as output. A function can be created from a formula (e.g. ~ fullseq(.x, .y)).

Overrides binwidth and bins. By default, this is a vector of length ten with pretty() breaks.

hjust, vjust

horizontal and vertical justification of the grob. Each justification value should be a number between 0 and 1. Defaults to 0.5 for both, centering each pixel over its data location.

interpolate

If TRUE interpolate linearly, if FALSE (the default) don't interpolate.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

geom

The geometric object to use to display the data for this layer. When using a ⁠stat_*()⁠ function to construct a layer, the geom argument can be used to override the default coupling between stats and geoms. The geom argument accepts the following:

A Geom ggproto subclass, for example GeomPoint.
A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".
For more information and other ways to specify the geom, see the layer geom documentation.

Text with Normalised Parent Coordinates

Description

Text with Normalised Parent Coordinates

Usage

geom_richtext_npc(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  nudge_x = 0,
  nudge_y = 0,
  label.padding = unit(c(0.25, 0.25, 0.25, 0.25), "lines"),
  label.margin = unit(c(0, 0, 0, 0), "lines"),
  label.r = unit(0.15, "lines"),
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = FALSE
)

annotate_richtext_npc(x, y, label, size = 5, family = "", ...)

annotate_richlabel_npc(
  x,
  y,
  label,
  size = 5,
  family = "",
  fill = "white",
  label.color = "black",
  ...
)

annotate_label_npc(
  x,
  y,
  label,
  size = 5,
  family = "",
  fill = "white",
  label.color = "black",
  ...
)
geom_richtext_npc(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  nudge_x = 0,
  nudge_y = 0,
  label.padding = unit(c(0.25, 0.25, 0.25, 0.25), "lines"),
  label.margin = unit(c(0, 0, 0, 0), "lines"),
  label.r = unit(0.15, "lines"),
  na.rm = FALSE,
  show.legend = FALSE,
  inherit.aes = FALSE
)

annotate_richtext_npc(x, y, label, size = 5, family = "", ...)

annotate_richlabel_npc(
  x,
  y,
  label,
  size = 5,
  family = "",
  fill = "white",
  label.color = "black",
  ...
)

annotate_label_npc(
  x,
  y,
  label,
  size = 5,
  family = "",
  fill = "white",
  label.color = "black",
  ...
)

Arguments

mapping

Set of aesthetic mappings created by aes() or aes_(). If specified and inherit.aes = TRUE (the default), it is combined with the default mapping at the top level of the plot. You must supply mapping if there is no plot mapping.

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

The statistical transformation to use on the data for this layer, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function. Cannot be jointy specified with nudge_x or nudge_y.

...

Other arguments passed on to layer(). These are often aesthetics, used to set an aesthetic to a fixed value, like colour = "red" or size = 3. They may also be parameters to the paired geom/stat.

nudge_x

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with position.

nudge_y

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with position.

label.padding

Amount of padding around label. Defaults to 0.25 lines.

label.margin

Unit vector of length four specifying the margin outside the text label.

label.r

Radius of rounded corners. Defaults to 0.15 lines.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

x

A numeric vector or unit object specifying x-values.

y

A numeric vector or unit object specifying y-values.

label

A character or expression vector. Other objects are coerced by as.graphicsAnnot.

Aesthetics

geom_richtext() understands the following aesthetics (required aesthetics are in bold; select aesthetics are annotated):

x
y
label
alpha
angle
colour Default color of label text and label outline.
family
fontface
fill Default fill color of label background.
group
hjust
label.colour Color of label outline. Overrides colour.
label.size Width of label outline.
lineheight
size Default font size of label text.
text.colour Color of label text. Overrides colour.
vjust

Examples

library(ggplot2)

## first example
labels <- c(
  "gC m^{-2} d^{-1}",
  "gC m^-2 d^-1",
  "gC m_{-2} d_{-1}",
  "gC m_-2 d_-1"
  # "gC \n mm/d"
)
x = 0.2
y = seq_along(labels)/10

ggplot() + annotate_richtext_npc(x, y, labels, size = 5)
ggplot() + annotate_richlabel_npc(x, y, labels, size = 5, label.color = "red")

# Another option
d = data.frame(x = 0.2, y = seq_along(labels)/10, label = labels)
ggplot(d, aes(npcx = x, npcy = y)) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label))

# remove fill and label.color
ggplot(d, aes(npcx = x, npcy = y)) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label),
                    fill = "white", label.color = "red")

## second example
d$label <- c(
  "Some text **in bold.**",
  "Linebreaks<br>Linebreaks<br>Linebreaks",
  "*x*<sup>2</sup> + 5*x* + *C*<sub>*i*</sub>",
  "Some <span style='color:blue'>blue text **in bold.**</span><br>And 
  *italics text.*<br>
  And some <span style='font-size:18pt; color:black'>large</span> text."
)
ggplot(d, aes(npcx = x, npcy = y)) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label))

## test for `str_mk`
library(magrittr)
indexes_lev = c("DOY_first", "DOY_last", "HWD", "HWI", "HWS_mean", 
  "HWS_sum", "HWA_avg", "HWA_max", "HWA_sum")
labels = indexes_lev %>% str_mk() #%>% label_tag(expression = F)
d = data.frame(x = 0.5, y = 0.5, label = labels)

ggplot(d) +
  facet_wrap(~label) +
  theme(strip.text.x = element_textbox(face = "bold")) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label))
library(ggplot2)

## first example
labels <- c(
  "gC m^{-2} d^{-1}",
  "gC m^-2 d^-1",
  "gC m_{-2} d_{-1}",
  "gC m_-2 d_-1"
  # "gC \n mm/d"
)
x = 0.2
y = seq_along(labels)/10

ggplot() + annotate_richtext_npc(x, y, labels, size = 5)
ggplot() + annotate_richlabel_npc(x, y, labels, size = 5, label.color = "red")

# Another option
d = data.frame(x = 0.2, y = seq_along(labels)/10, label = labels)
ggplot(d, aes(npcx = x, npcy = y)) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label))

# remove fill and label.color
ggplot(d, aes(npcx = x, npcy = y)) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label),
                    fill = "white", label.color = "red")

## second example
d$label <- c(
  "Some text **in bold.**",
  "Linebreaks<br>Linebreaks<br>Linebreaks",
  "*x*<sup>2</sup> + 5*x* + *C*<sub>*i*</sub>",
  "Some <span style='color:blue'>blue text **in bold.**</span><br>And 
  *italics text.*<br>
  And some <span style='font-size:18pt; color:black'>large</span> text."
)
ggplot(d, aes(npcx = x, npcy = y)) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label))

## test for `str_mk`
library(magrittr)
indexes_lev = c("DOY_first", "DOY_last", "HWD", "HWI", "HWS_mean", 
  "HWS_sum", "HWA_avg", "HWA_max", "HWA_sum")
labels = indexes_lev %>% str_mk() #%>% label_tag(expression = F)
d = data.frame(x = 0.5, y = 0.5, label = labels)

ggplot(d) +
  facet_wrap(~label) +
  theme(strip.text.x = element_textbox(face = "bold")) +
  geom_richtext_npc(aes(npcx = x, npcy = y, label = label))

Richtext labels

Description

This geom draws text labels similar to ggplot2::geom_label(), but formatted using basic markdown/html. Parameter and aesthetic names follow the conventions of ggplot2::geom_label(), and therefore the appearance of the frame around the label is controlled with label.colour, label.padding, label.margin, label.size, label.r, even though the same parameters are called box.colour, box.padding, box.margin, box.size, and box.r in ggtext::geom_textbox(). Most styling parameters can be used as aesthetics and can be applied separately to each text label drawn. The exception is styling parameters that are specified as grid units (e.g., label.padding or label.r), which can only be specified for all text labels at once. See examples for details.

Usage

geom_richtext2(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  nudge_x = 0,
  nudge_y = 0,
  label.padding = unit(c(0.25, 0.25, 0.25, 0.25), "lines"),
  label.margin = unit(c(0, 0, 0, 0), "lines"),
  label.r = unit(0.15, "lines"),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_richtext2(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  nudge_x = 0,
  nudge_y = 0,
  label.padding = unit(c(0.25, 0.25, 0.25, 0.25), "lines"),
  label.margin = unit(c(0, 0, 0, 0), "lines"),
  label.r = unit(0.15, "lines"),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

The statistical transformation to use on the data for this layer, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function. Cannot be jointy specified with nudge_x or nudge_y.

...

nudge_x

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with position.

nudge_y

Horizontal and vertical adjustment to nudge labels by. Useful for offsetting text from points, particularly on discrete scales. Cannot be jointly specified with position.

label.padding

Amount of padding around label. Defaults to 0.25 lines.

label.margin

Unit vector of length four specifying the margin outside the text label.

label.r

Radius of rounded corners. Defaults to 0.15 lines.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Value

A ggplot2 layer that can be added to a plot created with ggplot2::ggplot().

Aesthetics

geom_richtext() understands the following aesthetics (required aesthetics are in bold; select aesthetics are annotated):

x
y
label
alpha
angle
colour Default color of label text and label outline.
family
fontface
fill Default fill color of label background.
group
hjust
label.colour Color of label outline. Overrides colour.
label.size Width of label outline.
lineheight
size Default font size of label text.
text.colour Color of label text. Overrides colour.
vjust

Examples

library(ggplot2)

labels1 = c(
  "Some text **in bold.**",
  "Linebreaks<br>Linebreaks<br>Linebreaks",
  "*x*<sup>2</sup> + 5*x* + *C*<sub>*i*</sub>",
  "Some <span style='color:blue'>blue text **in bold.**</span><br>And *italics text.*<br>
    And some <span style='font-size:18pt; color:black'>large</span> text."
)

labels2 <- c(
  "gC m^{-2} d^{-1}",
  "gC m^-2 d^-1",
  "gC m_{-2} d_{-1}",
  "gC m_-2 d_-1"
  # "gC \n mm/d"
)

df <- data.frame(
  x = c(.2, .1, .5, .9),
  y = c(.8, .4, .1, .5),
  hjust = c(0.5, 0, 0, 1),
  vjust = c(0.5, 1, 0, 0.5),
  angle = c(0, 0, 45, -45),
  color = c("black", "blue", "black", "red"),
  fill = c("cornsilk", "white", "lightblue1", "white")
)

fun <- function(labels) {
  df$label = labels
  ggplot(df, aes(x, y, label = label, angle = angle, color = color,
                 hjust = hjust, vjust = vjust)) +
    geom_richtext2(
      fill = NA, label.color = NA, # remove background and outline
      label.padding = grid::unit(rep(0, 4), "pt") # remove padding
    ) +
    geom_point(color = "black", size = 2) +
    scale_color_identity() +
    xlim(0, 1) +
    ylim(0, 1)
}
fun(labels1)
fun(labels2)
# labels without frame or background are also possible
library(ggplot2)

labels1 = c(
  "Some text **in bold.**",
  "Linebreaks<br>Linebreaks<br>Linebreaks",
  "*x*<sup>2</sup> + 5*x* + *C*<sub>*i*</sub>",
  "Some <span style='color:blue'>blue text **in bold.**</span><br>And *italics text.*<br>
    And some <span style='font-size:18pt; color:black'>large</span> text."
)

labels2 <- c(
  "gC m^{-2} d^{-1}",
  "gC m^-2 d^-1",
  "gC m_{-2} d_{-1}",
  "gC m_-2 d_-1"
  # "gC \n mm/d"
)

df <- data.frame(
  x = c(.2, .1, .5, .9),
  y = c(.8, .4, .1, .5),
  hjust = c(0.5, 0, 0, 1),
  vjust = c(0.5, 1, 0, 0.5),
  angle = c(0, 0, 45, -45),
  color = c("black", "blue", "black", "red"),
  fill = c("cornsilk", "white", "lightblue1", "white")
)

fun <- function(labels) {
  df$label = labels
  ggplot(df, aes(x, y, label = label, angle = angle, color = color,
                 hjust = hjust, vjust = vjust)) +
    geom_richtext2(
      fill = NA, label.color = NA, # remove background and outline
      label.padding = grid::unit(rep(0, 4), "pt") # remove padding
    ) +
    geom_point(color = "black", size = 2) +
    scale_color_identity() +
    xlim(0, 1) +
    ylim(0, 1)
}
fun(labels1)
fun(labels2)
# labels without frame or background are also possible

geom_spike

Description

geom_spike

Usage

geom_spike(
  mapping = NULL,
  data = NULL,
  stat = "spike",
  position = "identity",
  ...,
  halfwin = 3,
  sd.times = 3,
  trs = NA,
  verbose = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_spike(
  mapping = NULL,
  data = NULL,
  stat = "spike",
  position = "identity",
  ...,
  halfwin = 3,
  sd.times = 3,
  trs = NA,
  verbose = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

halfwin

halfwin of movmean, rtrend::movmean()

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Examples

library(data.table)
library(ggplot2)
data("GPP_US_MMS")
dat = melt(GPP_US_MMS[, .(date, SM, GPP)], "date")

ggplot(dat, aes(date, value)) + 
  geom_line() + 
  geom_movmean(halfwin = 5, linewidth = 1, alpha = 0.7, color = "pink") + 
  # geom_movmean(halfwin = 5, show.diff=TRUE, linewidth = 0.2, alpha = 0.7, color = "red") + 
  geom_spike(halfwin = 2, sd.times = 6, color = "red", verbose = TRUE) +
  # geom_spike(halfwin = 5, trs = 3, color = "blue") +
  facet_wrap(~variable, scales = "free_y") 
library(data.table)
library(ggplot2)
data("GPP_US_MMS")
dat = melt(GPP_US_MMS[, .(date, SM, GPP)], "date")

ggplot(dat, aes(date, value)) + 
  geom_line() + 
  geom_movmean(halfwin = 5, linewidth = 1, alpha = 0.7, color = "pink") + 
  # geom_movmean(halfwin = 5, show.diff=TRUE, linewidth = 0.2, alpha = 0.7, color = "red") + 
  geom_spike(halfwin = 2, sd.times = 6, color = "red", verbose = TRUE) +
  # geom_spike(halfwin = 5, trs = 3, color = "blue") +
  facet_wrap(~variable, scales = "free_y")

geom_taylor

Description

geom_taylor

Usage

geom_taylor(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  obs.colour = "black",
  obs.size = 5,
  show.obs.label = TRUE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
geom_taylor(
  mapping = NULL,
  data = NULL,
  stat = "identity",
  position = "identity",
  ...,
  obs.colour = "black",
  obs.size = 5,
  show.obs.label = TRUE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

obs.colour

color of observed point.

obs.size

size of observed point.

show.obs.label

logical, whether to show the label of observed point.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Examples

library(ggplot2)
library(dplyr)

data = dummy_model %>%
  group_by(model, variable) %>%
  group_modify(~taylor_data(.$obs, .$mod)) #%>% as.data.table()
print(data)

mar = 0.01
p = ggplot(data) +
  geom_taylor(aes2(sd.obs, sd.mod, R, color = model), obs.colour = "black", obs.size = 5) +
  # geom_point(aes(color = model), size = 5) +
  facet_wrap(~variable) +
  labs(color = NULL) +
  theme_bw() +
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    legend.position = c(1, 1) - c(1, 1/3)*mar,
    legend.justification = c(1, 1)
  )
p
# p = last_plot()
# Ipaper::write_fig(p, "Rplot.pdf")
library(ggplot2)
library(dplyr)

data = dummy_model %>%
  group_by(model, variable) %>%
  group_modify(~taylor_data(.$obs, .$mod)) #%>% as.data.table()
print(data)

mar = 0.01
p = ggplot(data) +
  geom_taylor(aes2(sd.obs, sd.mod, R, color = model), obs.colour = "black", obs.size = 5) +
  # geom_point(aes(color = model), size = 5) +
  facet_wrap(~variable) +
  labs(color = NULL) +
  theme_bw() +
  theme(
    panel.grid.major = element_blank(),
    panel.grid.minor = element_blank(),
    legend.position = c(1, 1) - c(1, 1/3)*mar,
    legend.justification = c(1, 1)
  )
p
# p = last_plot()
# Ipaper::write_fig(p, "Rplot.pdf")

ggplot_legend

Description

ggplot_legend

Usage

ggplot_legend(g)
ggplot_legend(g)

Arguments

g

A ggplot object

Value

A grob object

ggplot_multiaxis

Description

ggplot_multiaxis

Usage

ggplot_multiaxis(..., linewidth = 1.4, tck = 0.2, x = -0.02)

ggplot_multiAxis(..., linewidth = 1.4, tck = 0.2, x = -0.02)
ggplot_multiaxis(..., linewidth = 1.4, tck = 0.2, x = -0.02)

ggplot_multiAxis(..., linewidth = 1.4, tck = 0.2, x = -0.02)

Arguments

...

ggplot2 objects, which should have axis.tick.y.right and axis.title.y.left

linewidth

line width of right axis line

tck

tick length of right axis

Examples

library(ggplot2)
library(rlang)
library(gg.layers)

plot_1var <- function(d, var, color = "black", lwd = 0.4, alpha = 0.6) {
  p <- ggplot(d, aes(date, !!sym(var))) +
    geom_line(color = color, linewidth = lwd, alpha = alpha) +
    # facet_wrap(~site) +
    scale_x_date(date_breaks = "1 year", date_labels = "%Y") +
    theme(
      panel.background = element_rect(fill = "transparent", color = "black"),
      plot.margin = margin(r = 5, l = 5, t = 2, b = 2),
      axis.ticks.y.left = element_line(color = color),
      axis.text.y.left = element_text(color = color),
      axis.title.y.left = element_text(color = color),
      axis.ticks.y.right = element_line(color = color),
      axis.text.y.right = element_text(color = color),
      axis.title.y.right = element_text(color = color, margin = margin(l = 2, r = 5)),
      panel.grid.major = element_blank(), # get rid of major grid
      panel.grid.minor = element_blank()
    ) # get rid of minor grid
  p
}

# GPP_US_MMS = d[year(date) >= 2013]
# usethis::use_data(GPP_US_MMS)
p_gpp <- plot_1var(GPP_US_MMS, "GPP", color = "green")
p_sm <- plot_1var(GPP_US_MMS, "SM", color = "red")
p_prcp <- plot_1var(GPP_US_MMS, "prcp", color = "blue")

p <- ggplot_multiaxis(p_gpp, p_sm, p_prcp, x = -0.02, linewidth = 1.2)
p
library(ggplot2)
library(rlang)
library(gg.layers)

plot_1var <- function(d, var, color = "black", lwd = 0.4, alpha = 0.6) {
  p <- ggplot(d, aes(date, !!sym(var))) +
    geom_line(color = color, linewidth = lwd, alpha = alpha) +
    # facet_wrap(~site) +
    scale_x_date(date_breaks = "1 year", date_labels = "%Y") +
    theme(
      panel.background = element_rect(fill = "transparent", color = "black"),
      plot.margin = margin(r = 5, l = 5, t = 2, b = 2),
      axis.ticks.y.left = element_line(color = color),
      axis.text.y.left = element_text(color = color),
      axis.title.y.left = element_text(color = color),
      axis.ticks.y.right = element_line(color = color),
      axis.text.y.right = element_text(color = color),
      axis.title.y.right = element_text(color = color, margin = margin(l = 2, r = 5)),
      panel.grid.major = element_blank(), # get rid of major grid
      panel.grid.minor = element_blank()
    ) # get rid of minor grid
  p
}

# GPP_US_MMS = d[year(date) >= 2013]
# usethis::use_data(GPP_US_MMS)
p_gpp <- plot_1var(GPP_US_MMS, "GPP", color = "green")
p_sm <- plot_1var(GPP_US_MMS, "SM", color = "red")
p_prcp <- plot_1var(GPP_US_MMS, "prcp", color = "blue")

p <- ggplot_multiaxis(p_gpp, p_sm, p_prcp, x = -0.02, linewidth = 1.2)
p

GOF

Description

Good of fitting

Usage

GOF(obs, sim, w, include.cv = FALSE, include.r = TRUE)

KGE(obs, sim, w = c(1, 1, 1), ...)

NSE(obs, sim, w, ...)
GOF(obs, sim, w, include.cv = FALSE, include.r = TRUE)

KGE(obs, sim, w = c(1, 1, 1), ...)

NSE(obs, sim, w, ...)

Arguments

obs

Numeric vector, observations

sim

Numeric vector, corresponding simulated values

w

Numeric vector, weights of every points. If w included, when calculating mean, Bias, MAE, RMSE and NSE, w will be taken into considered.

include.cv

If true, cv will be included.

include.r

If true, r and R2 will be included.

...

ignored

Value

RMSE root mean square error
NSE NASH coefficient
MAE mean absolute error
AI Agreement index (only good points (w == 1)) participate to calculate. See details in Zhang et al., (2015).
Bias bias
Bias_perc bias percentage
n_sim number of valid obs
cv Coefficient of variation
R2 correlation of determination
R pearson correlation
pvalue pvalue of R

References

https://en.wikipedia.org/wiki/Coefficient_of_determination
https://en.wikipedia.org/wiki/Explained_sum_of_squares
https://en.wikipedia.org/wiki/Nash%E2%80%93Sutcliffe_model_efficiency_coefficient
Zhang Xiaoyang (2015), http://dx.doi.org/10.1016/j.rse.2014.10.012

Examples

obs = rnorm(100)
sim = obs + rnorm(100)/4
GOF(obs, sim)

obs = rnorm(100)
sim = obs + rnorm(100)/4
GOF(obs, sim)

guide_coloursteps2 #' @param title A title for the guide.

Description

guide_coloursteps2 #' @param title A title for the guide.

Usage

guide_coloursteps2(
  title = waiver(),
  theme = NULL,
  alpha = NA,
  even.steps = TRUE,
  show.limits = NULL,
  direction = NULL,
  reverse = FALSE,
  order = 0,
  available_aes = c("colour", "color", "fill"),
  barheight = unit(0.9, "npc"),
  ...
)

guide_colorsteps2(
  title = waiver(),
  theme = NULL,
  alpha = NA,
  even.steps = TRUE,
  show.limits = NULL,
  direction = NULL,
  reverse = FALSE,
  order = 0,
  available_aes = c("colour", "color", "fill"),
  barheight = unit(0.9, "npc"),
  ...
)
guide_coloursteps2(
  title = waiver(),
  theme = NULL,
  alpha = NA,
  even.steps = TRUE,
  show.limits = NULL,
  direction = NULL,
  reverse = FALSE,
  order = 0,
  available_aes = c("colour", "color", "fill"),
  barheight = unit(0.9, "npc"),
  ...
)

guide_colorsteps2(
  title = waiver(),
  theme = NULL,
  alpha = NA,
  even.steps = TRUE,
  show.limits = NULL,
  direction = NULL,
  reverse = FALSE,
  order = 0,
  available_aes = c("colour", "color", "fill"),
  barheight = unit(0.9, "npc"),
  ...
)

Arguments

theme

A theme object for rendering the guide.

alpha

Alpha transparency level.

even.steps

Logical; should the steps be evenly spaced?

show.limits

Logical; should the limits be shown?

direction

Direction of the guide ("horizontal" or "vertical").

reverse

Logical; should the guide be reversed?

order

Order of the guide.

available_aes

Available aesthetics for this guide.

barheight

Height of the color bar. Deprecated in ggplot2 3.5.0.

...

Additional arguments passed to the guide. #' @example R/examples/ex-stat_cut.R

layer_barchart

Description

layer_barchart

Usage

layer_barchart(
  mapping = NULL,
  data = NULL,
  brks,
  cols,
  x = 0,
  y = 0,
  width = unit(0.5, "npc"),
  height = unit(0.5, "npc"),
  just = c(0, 0),
  fontsize = 12,
  theme = NULL,
  ...
)

geom_barchart(
  mapping = NULL,
  data = NULL,
  brks,
  cols,
  x = 0,
  y = 0,
  width = unit(0.5, "npc"),
  height = unit(0.5, "npc"),
  just = c(0, 0),
  fontsize = 12,
  theme = NULL,
  ...
)
layer_barchart(
  mapping = NULL,
  data = NULL,
  brks,
  cols,
  x = 0,
  y = 0,
  width = unit(0.5, "npc"),
  height = unit(0.5, "npc"),
  just = c(0, 0),
  fontsize = 12,
  theme = NULL,
  ...
)

geom_barchart(
  mapping = NULL,
  data = NULL,
  brks,
  cols,
  x = 0,
  y = 0,
  width = unit(0.5, "npc"),
  height = unit(0.5, "npc"),
  just = c(0, 0),
  fontsize = 12,
  theme = NULL,
  ...
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

x

A numeric vector or unit object specifying x-location.

y

A numeric vector or unit object specifying y-location.

width

A numeric vector or unit object specifying width.

height

A numeric vector or unit object specifying height.

just

Adjustment for column placement. Set to 0.5 by default, meaning that columns will be centered about axis breaks. Set to 0 or 1 to place columns to the left/right of axis breaks. Note that this argument may have unintended behaviour when used with alternative positions, e.g. position_dodge().

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

Examples

library(gg.layers)
library(ggplot2)
library(rcolors)

data("d_trendPerc")
d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) # %>% as.data.frame()

brks = seq(0.9, 1, 0.025)
nbrk = length(brks) - 1
cols <- get_color(rcolors$amwg256, nbrk)

# the part of not significant
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  layer_barchart(aes(z = perc), 
    width = unit(0.3, "npc"), 
    height = unit(0.3, "npc"), 
    brks = brks, cols = cols)
library(gg.layers)
library(ggplot2)
library(rcolors)

data("d_trendPerc")
d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) # %>% as.data.frame()

brks = seq(0.9, 1, 0.025)
nbrk = length(brks) - 1
cols <- get_color(rcolors$amwg256, nbrk)

# the part of not significant
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  layer_barchart(aes(z = perc), 
    width = unit(0.3, "npc"), 
    height = unit(0.3, "npc"), 
    brks = brks, cols = cols)

layer_PosNeg

Description

layer_PosNeg

Usage

layer_PosNeg(mapping = NULL, data = NULL, x = 0, y = 0, size = 12, ...)

add_PosNeg(
  z,
  x = 0.5,
  y = 0.5,
  height.factor = 1.2,
  cols = c("blue", "red"),
  alpha = 0.8,
  ...
)

layer_PosNeg_sign(
  mapping = NULL,
  data = NULL,
  x = 0.5,
  y = 0.5,
  height.factor = 1.2,
  size = 12,
  ...
)

add_PosNeg_sign(
  z,
  mask,
  x = 0.5,
  y = 0.5,
  height.factor = 1.2,
  cols = c("blue", "red"),
  alpha = 0.8,
  ...
)
layer_PosNeg(mapping = NULL, data = NULL, x = 0, y = 0, size = 12, ...)

add_PosNeg(
  z,
  x = 0.5,
  y = 0.5,
  height.factor = 1.2,
  cols = c("blue", "red"),
  alpha = 0.8,
  ...
)

layer_PosNeg_sign(
  mapping = NULL,
  data = NULL,
  x = 0.5,
  y = 0.5,
  height.factor = 1.2,
  size = 12,
  ...
)

add_PosNeg_sign(
  z,
  mask,
  x = 0.5,
  y = 0.5,
  height.factor = 1.2,
  cols = c("blue", "red"),
  alpha = 0.8,
  ...
)

Arguments

...

other parameters to element_grob_text

make_colorbar

Description

make_colorbar

Usage

make_colorbar(
  at,
  labels = NULL,
  labeller = format,
  space = "right",
  width = 2,
  height = 1,
  col = NULL,
  alpha = 1,
  pretty = FALSE,
  equispaced = TRUE,
  tick.number = 7,
  tck = 0.3,
  tck.padding = 0,
  raster = FALSE,
  interpolate = FALSE,
  tri.upper = NA,
  tri.lower = NA,
  legend.line = element_line(linewidth = 0.8),
  legend.box = element_rect(linewidth = 0.5),
  hjust = 0.5,
  vjust = 0.5,
  size = 12,
  family = "Times",
  legend.text.location = c(0.5, 0.5),
  legend.margin = bb_margin(),
  title = NULL,
  legend.text = element_text(hjust = 0.5),
  legend.title = element_text(),
  fct.title.height = 1.8,
  padding.left = unit(2, "points"),
  padding.right = unit(2, "points"),
  ...,
  draw = FALSE,
  vp = NULL
)
make_colorbar(
  at,
  labels = NULL,
  labeller = format,
  space = "right",
  width = 2,
  height = 1,
  col = NULL,
  alpha = 1,
  pretty = FALSE,
  equispaced = TRUE,
  tick.number = 7,
  tck = 0.3,
  tck.padding = 0,
  raster = FALSE,
  interpolate = FALSE,
  tri.upper = NA,
  tri.lower = NA,
  legend.line = element_line(linewidth = 0.8),
  legend.box = element_rect(linewidth = 0.5),
  hjust = 0.5,
  vjust = 0.5,
  size = 12,
  family = "Times",
  legend.text.location = c(0.5, 0.5),
  legend.margin = bb_margin(),
  title = NULL,
  legend.text = element_text(hjust = 0.5),
  legend.title = element_text(),
  fct.title.height = 1.8,
  padding.left = unit(2, "points"),
  padding.right = unit(2, "points"),
  ...,
  draw = FALSE,
  vp = NULL
)

Arguments

legend.box

arrangement of multiple legends ("horizontal" or "vertical")

hjust, vjust

used in grid::grid.layout()

legend.margin

the margin around each legend (margin()); inherits from margins.

title

all title elements: plot, axes, legends (element_text(); inherits from text)

legend.text

cex:
col:
font:
fontfamily: The font family
fontface: The font face (bold, italic, ...)
lineheight:

legend.title

title of legend (element_text(); inherits from title)

padding.left, padding.right

padding in the left and right of the legend

...

additional element specifications not part of base ggplot2. In general, these should also be defined in the ⁠element tree⁠ argument. Splicing a list is also supported.

draw

A logical value indicating whether graphics output should be produced.

vp

A Grid viewport object (or NULL).

Examples

library(ggplot2)
library(rcolors)
library(magrittr)
library(glue)

## example 01
spaces <- c("right", "left", "top", "bottom") # %>% set_names(., .)

make_cbar <- function(brks, space, outfile = NULL) {
  # brks <- 1:5
  nbrk <- length(brks) - 1
  cols <- rcolors::get_color("amwg256", nbrk)

  g <- make_colorbar(
    at = brks, col = cols,
    space = space, title = space
  )
  if (!is.null(outfile)) {
    if (require(Ipaper))
      Ipaper::write_fig(g, outfile, 10, 6)
  }
  g
}

brks = 1:5 %>% c(-Inf, ., Inf)
spaces <- c("right", "left", "top", "bottom")
ps = lapply(spaces, function(space) {
  fout = glue("cbar_{space}.pdf")
  fout = NULL
  make_cbar(brks, space, fout)
})
g = cowplot::plot_grid(plotlist = ps)
# g = patchwork::wrap_plots(ps)
# grid.newpage(); grid.draw(g)
# Ipaper::write_fig(g, "Rplot.pdf", 10, 6) # uncomment if want to show figure


## example 02
brks = c(-Inf, -1, 0, 1, 3, 6, 9, Inf)
# brks = 1:10
nbrk = length(brks) - 1
cols = get_color(rcolors$amwg256, nbrk)

spaces = c("right", "left", "top", "bottom") #%>% set_names(., .)

params <- list(
  at = brks, col = cols, height = 1,
  tck = 0.4,
  # padding.left = unit(2, "points"),
  # padding.right = unit(2, "points"),
  space = spaces[1],
  # legend.line = element_line(size = 0.1, linetype = 1, color = "black"),
  # legend.text = element_text(hjust = 0.5),
  legend.text.location = c(0.2, 0.5),
  # legend.margin = bb_margin(t = 0.1),
  # legend.text.just = c(0.5, 0.5),
  # title = NULL,
  title = "d/decade",
  fct.title.height = 3,
  legend.title = element_text(size = 14)
  # legend.box = element_rect(size = 0.5),
  # legend.line = element_line(size = 1),
  # legend.text = list(fontfamily = "Times", cex = 1.1),
  # hjust = 0.5
)
cbar <- do.call(make_colorbar, params)
# write_fig(cbar, "a.pdf", 0.9, 6)

# cowplot::plot_grid(plotlist = lst)
p <- ggplot(mtcars, aes(mpg, disp)) + geom_point() +
  facet_wrap(~cyl)
p + cbar

p <- ggplot(mtcars, aes(mpg, disp)) + geom_point() +
  facet_wrap(~cyl, nrow = 2)
add_colorbar(p, cbar)

## Test the bottom
params$space = "bottom"
params$title = ""
cbar2 <- do.call(make_colorbar, params)
add_colorbar(p, cbar2, space = "bottom",
             title = "(mm/y)",
             legend.title = element_text(hjust = -5, vjust = -3, family = "Times"))

# Another option
title = element_grob_text(element_text(family = "Times", hjust = 1, vjust = 0, size = 12),
  label = "(mm/y)", x = 0.98, y = 0.09)
add_colorbar(p, cbar2, space = "bottom") %>% add_grob(title)


library(ggplot2)
library(rcolors)
library(magrittr)
library(glue)

## example 01
spaces <- c("right", "left", "top", "bottom") # %>% set_names(., .)

make_cbar <- function(brks, space, outfile = NULL) {
  # brks <- 1:5
  nbrk <- length(brks) - 1
  cols <- rcolors::get_color("amwg256", nbrk)

  g <- make_colorbar(
    at = brks, col = cols,
    space = space, title = space
  )
  if (!is.null(outfile)) {
    if (require(Ipaper))
      Ipaper::write_fig(g, outfile, 10, 6)
  }
  g
}

brks = 1:5 %>% c(-Inf, ., Inf)
spaces <- c("right", "left", "top", "bottom")
ps = lapply(spaces, function(space) {
  fout = glue("cbar_{space}.pdf")
  fout = NULL
  make_cbar(brks, space, fout)
})
g = cowplot::plot_grid(plotlist = ps)
# g = patchwork::wrap_plots(ps)
# grid.newpage(); grid.draw(g)
# Ipaper::write_fig(g, "Rplot.pdf", 10, 6) # uncomment if want to show figure


## example 02
brks = c(-Inf, -1, 0, 1, 3, 6, 9, Inf)
# brks = 1:10
nbrk = length(brks) - 1
cols = get_color(rcolors$amwg256, nbrk)

spaces = c("right", "left", "top", "bottom") #%>% set_names(., .)

params <- list(
  at = brks, col = cols, height = 1,
  tck = 0.4,
  # padding.left = unit(2, "points"),
  # padding.right = unit(2, "points"),
  space = spaces[1],
  # legend.line = element_line(size = 0.1, linetype = 1, color = "black"),
  # legend.text = element_text(hjust = 0.5),
  legend.text.location = c(0.2, 0.5),
  # legend.margin = bb_margin(t = 0.1),
  # legend.text.just = c(0.5, 0.5),
  # title = NULL,
  title = "d/decade",
  fct.title.height = 3,
  legend.title = element_text(size = 14)
  # legend.box = element_rect(size = 0.5),
  # legend.line = element_line(size = 1),
  # legend.text = list(fontfamily = "Times", cex = 1.1),
  # hjust = 0.5
)
cbar <- do.call(make_colorbar, params)
# write_fig(cbar, "a.pdf", 0.9, 6)

# cowplot::plot_grid(plotlist = lst)
p <- ggplot(mtcars, aes(mpg, disp)) + geom_point() +
  facet_wrap(~cyl)
p + cbar

p <- ggplot(mtcars, aes(mpg, disp)) + geom_point() +
  facet_wrap(~cyl, nrow = 2)
add_colorbar(p, cbar)

## Test the bottom
params$space = "bottom"
params$title = ""
cbar2 <- do.call(make_colorbar, params)
add_colorbar(p, cbar2, space = "bottom",
             title = "(mm/y)",
             legend.title = element_text(hjust = -5, vjust = -3, family = "Times"))

# Another option
title = element_grob_text(element_text(family = "Times", hjust = 1, vjust = 0, size = 12),
  label = "(mm/y)", x = 0.98, y = 0.09)
add_colorbar(p, cbar2, space = "bottom") %>% add_grob(title)

scale_fill_gradientn2

Description

scale_fill_gradientn2

Usage

scale_fill_gradientn2(
  ...,
  colours,
  values = NULL,
  space = "Lab",
  na.value = "transparent",
  guide = colourbar_triangle(),
  oob = censor2,
  aesthetics = "colour",
  colors
)
scale_fill_gradientn2(
  ...,
  colours,
  values = NULL,
  space = "Lab",
  na.value = "transparent",
  guide = colourbar_triangle(),
  oob = censor2,
  aesthetics = "colour",
  colors
)

Arguments

...

Arguments passed on to continuous_scale

scale_name

The name of the scale that should be used for error messages associated with this scale.

breaks

One of:

NULL for no breaks
waiver() for the default breaks computed by the transformation object
A numeric vector of positions
A function that takes the limits as input and returns breaks as output (e.g., a function returned by scales::extended_breaks()). Note that for position scales, limits are provided after scale expansion. Also accepts rlang lambda function notation.

minor_breaks

One of:

NULL for no minor breaks
waiver() for the default breaks (none for discrete, one minor break between each major break for continuous)
A numeric vector of positions
A function that given the limits returns a vector of minor breaks. Also accepts rlang lambda function notation. When the function has two arguments, it will be given the limits and major break positions.

n.breaks

An integer guiding the number of major breaks. The algorithm may choose a slightly different number to ensure nice break labels. Will only have an effect if breaks = waiver(). Use NULL to use the default number of breaks given by the transformation.

labels

One of the options below. Please note that when labels is a vector, it is highly recommended to also set the breaks argument as a vector to protect against unintended mismatches.

NULL for no labels
waiver() for the default labels computed by the transformation object
A character vector giving labels (must be same length as breaks)
An expression vector (must be the same length as breaks). See ?plotmath for details.
A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.

limits

One of:

NULL to use the default scale range
A numeric vector of length two providing limits of the scale. Use NA to refer to the existing minimum or maximum
A function that accepts the existing (automatic) limits and returns new limits. Also accepts rlang lambda function notation. Note that setting limits on positional scales will remove data outside of the limits. If the purpose is to zoom, use the limit argument in the coordinate system (see coord_cartesian()).

rescaler

A function used to scale the input values to the range [0, 1]. This is always scales::rescale(), except for diverging and n colour gradients (i.e., scale_colour_gradient2(), scale_colour_gradientn()). The rescaler is ignored by position scales, which always use scales::rescale(). Also accepts rlang lambda function notation.

oob

One of:

Function that handles limits outside of the scale limits (out of bounds). Also accepts rlang lambda function notation.
The default (scales::censor()) replaces out of bounds values with NA.
scales::squish() for squishing out of bounds values into range.
scales::squish_infinite() for squishing infinite values into range.

trans

Deprecated in favour of transform.

call

The call used to construct the scale for reporting messages.

super

The super class to use for the constructed scale

colours, colors

Vector of colours to use for n-colour gradient.

values

if colours should not be evenly positioned along the gradient this vector gives the position (between 0 and 1) for each colour in the colours vector. See rescale() for a convenience function to map an arbitrary range to between 0 and 1.

space

colour space in which to calculate gradient. Must be "Lab" - other values are deprecated.

na.value

Colour to use for missing values

guide

Type of legend. Use "colourbar" for continuous colour bar, or "legend" for discrete colour legend.

oob

function that handles limits outside of the scale limits

aesthetics

Character string or vector of character strings listing the name(s) of the aesthetic(s) that this scale works with. This can be useful, for example, to apply colour settings to the colour and fill aesthetics at the same time, via aesthetics = c("colour", "fill").

st_hatched_polygon

Description

st_hatched_polygon

Usage

st_hatched_polygon(x, density = 2, angle = 45, fillOddEven = FALSE)
st_hatched_polygon(x, density = 2, angle = 45, fillOddEven = FALSE)

Arguments

x

sf polygon object

density

the density of shading lines, in lines per inch. The default value of NULL means that no shading lines are drawn. A zero value of density means no shading nor filling whereas negative values and NA suppress shading (and so allow color filling).

angle

the slope of shading lines, given as an angle in degrees (counter-clockwise).

fillOddEven

logical controlling the polygon shading mode: see below for details. Default FALSE.

Value

An hatched area, sf lines

References

Examples

library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d = d_trendPerc %>% subset(perc >= 0.99) %>% .[, 1:2]
poly = st_point2poly(d)
hatches = st_hatched_polygon(poly) #
ggplot(hatches) + geom_sf()
library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d = d_trendPerc %>% subset(perc >= 0.99) %>% .[, 1:2]
poly = st_point2poly(d)
hatches = st_hatched_polygon(poly) #
ggplot(hatches) + geom_sf()

st_point2poly

Description

st_point2poly

Usage

st_point2poly(xyz, crs = 4326)

df2rast(xyz)

rast2poly(r, crs = 4326)

st_dissolve(x, by = NULL, ...)
st_point2poly(xyz, crs = 4326)

df2rast(xyz)

rast2poly(r, crs = 4326)

st_dissolve(x, by = NULL, ...)

Arguments

xyz

matrix or data.frame with at least three columns: x and y coordinates, and values (z). There may be several 'z' variables (columns)

crs

one of (i) character: a string accepted by GDAL, (ii) integer, a valid EPSG value (numeric), or (iii) an object of class crs.

References

https://gis.stackexchange.com/questions/192771/how-to-speed-up-raster-to-polygon-conversion-in-r

stat_cut

Description

stat_cut

Usage

stat_cut(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  breaks = NULL,
  include.lowest = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

StatCut
stat_cut(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  ...,
  breaks = NULL,
  include.lowest = FALSE,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

StatCut

Format

An object of class StatCut (inherits from StatIdentity, Stat, ggproto, gg) of length 6.

Examples

library(rcolors)
library(ggplot2)
library(magrittr)

df = data.frame(x = 1:10, y = 1:10, z = 1:10)

brks <- c(2, 4, 6, 8) %>% c(-Inf, ., Inf) # 这里要包含
nbrk <- length(brks) - 1
cols = get_color(rcolors$amwg256, nbrk)

ggplot(df, aes(x, y, z = x)) +
  stat_cut(aes(color = after_stat(level)), breaks = brks, geom = "point") +
  scale_color_manual(
    values = cols,
    guide = guide_coloursteps2(title = "lgd", barheight = unit(0.8, "npc"))
  )

## another option: use `scale_color_stepsn`
# example 2
# ! unable to accurately control the used colors
ggplot(df, aes(x, y, color = x)) +
  geom_point() +
  scale_color_stepsn(
    colors = cols,
    breaks = brks,
    guide = guide_coloursteps2(title = "lgd")
  ) +
  theme(
    legend.title = element_blank(),
    legend.margin = margin(l = -2)
  )

# example 3 
df <- expand.grid(X1 = 1:10, X2 = 1:10)
df$value <- df$X1 * df$X2

brks = c(10, 15, 25, 50)
nbrk <- length(brks) + 1
cols = get_color(rcolors$amwg256, nbrk)

# This can be changed with the `even.steps` argument
ggplot(df, aes(X1, X2)) +
  geom_tile(aes(fill = value)) +
  scale_fill_stepsn(
    colors = cols, breaks = brks,
    guide = guide_colorsteps2()
  ) +
  theme(
    legend.title = element_blank(),
    legend.margin = margin(l = -2)
  )
library(rcolors)
library(ggplot2)
library(magrittr)

df = data.frame(x = 1:10, y = 1:10, z = 1:10)

brks <- c(2, 4, 6, 8) %>% c(-Inf, ., Inf) # 这里要包含
nbrk <- length(brks) - 1
cols = get_color(rcolors$amwg256, nbrk)

ggplot(df, aes(x, y, z = x)) +
  stat_cut(aes(color = after_stat(level)), breaks = brks, geom = "point") +
  scale_color_manual(
    values = cols,
    guide = guide_coloursteps2(title = "lgd", barheight = unit(0.8, "npc"))
  )

## another option: use `scale_color_stepsn`
# example 2
# ! unable to accurately control the used colors
ggplot(df, aes(x, y, color = x)) +
  geom_point() +
  scale_color_stepsn(
    colors = cols,
    breaks = brks,
    guide = guide_coloursteps2(title = "lgd")
  ) +
  theme(
    legend.title = element_blank(),
    legend.margin = margin(l = -2)
  )

# example 3 
df <- expand.grid(X1 = 1:10, X2 = 1:10)
df$value <- df$X1 * df$X2

brks = c(10, 15, 25, 50)
nbrk <- length(brks) + 1
cols = get_color(rcolors$amwg256, nbrk)

# This can be changed with the `even.steps` argument
ggplot(df, aes(X1, X2)) +
  geom_tile(aes(fill = value)) +
  scale_fill_stepsn(
    colors = cols, breaks = brks,
    guide = guide_colorsteps2()
  ) +
  theme(
    legend.title = element_blank(),
    legend.margin = margin(l = -2)
  )

stat_gof

Description

stat_gof

Usage

stat_gof(
  mapping = NULL,
  data = NULL,
  geom = GeomRichTextNpc,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  show.bias = TRUE,
  label.format = fmt_gof,
  x = 0.05,
  y = 0.95,
  inherit.aes = TRUE,
  ...
)

geom_gof(
  mapping = NULL,
  data = NULL,
  stat = StatGOF,
  position = "identity",
  ...,
  show.bias = TRUE,
  label.format = fmt_gof,
  x = 0,
  y = 1,
  hjust = 0,
  vjust = 1,
  size = 5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_reg(
  mapping = NULL,
  data = NULL,
  formula = y ~ x,
  digits = 2,
  units = "",
  format = paste0("Slope = {str_num(slope, digits)}{unit}",
    ", p-value = {str_num(pvalue, digits)}"),
  fun_slope = NULL,
  x = 0,
  y = 1,
  hjust = 0,
  vjust = 1,
  mar = 0.03,
  height.factor = 1.2,
  family = "Times",
  color = NULL,
  position = "dodge",
  ...
)
stat_gof(
  mapping = NULL,
  data = NULL,
  geom = GeomRichTextNpc,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  show.bias = TRUE,
  label.format = fmt_gof,
  x = 0.05,
  y = 0.95,
  inherit.aes = TRUE,
  ...
)

geom_gof(
  mapping = NULL,
  data = NULL,
  stat = StatGOF,
  position = "identity",
  ...,
  show.bias = TRUE,
  label.format = fmt_gof,
  x = 0,
  y = 1,
  hjust = 0,
  vjust = 1,
  size = 5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

stat_reg(
  mapping = NULL,
  data = NULL,
  formula = y ~ x,
  digits = 2,
  units = "",
  format = paste0("Slope = {str_num(slope, digits)}{unit}",
    ", p-value = {str_num(pvalue, digits)}"),
  fun_slope = NULL,
  x = 0,
  y = 1,
  hjust = 0,
  vjust = 1,
  mar = 0.03,
  height.factor = 1.2,
  family = "Times",
  color = NULL,
  position = "dodge",
  ...
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

position

"dodge" or "identity"

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

show.bias

whether to show bias

label.format

format string for label, default fmt_gof

x

A numeric vector or unit object specifying x-values.

y

A numeric vector or unit object specifying y-values.

inherit.aes

...

stat

The statistical transformation to use on the data for this layer, as a string.

hjust

Horizontal justification (in $[0, 1]$ )

vjust

Vertical justification (in $[0, 1]$ )

formula

an object of class "formula" (or one that can be coerced to that class): a symbolic description of the model to be fitted. The details of model specification are given under ‘Details’.

digits

the number of significant digits to be passed to format(coef(x), .) when print()ing.

units

A Vector with the length of subplots

family

The typeface to use. The validity of this value will depend on the graphics device being used for rendering the plot. See the systemfonts vignette for guidance on the best way to access fonts installed on your computer. The values "sans", "serif", and "mono" should always be valid and will select the default typeface for the respective styles. However, what is considered default is dependant on the graphics device and the operating system.

Details

b: the object returned by broom::tidy()
s: the object returned by broom::glance()
- ⁠*R*^2 = {str_num(s$r.squared, digits)}⁠
slope:
pvalue:
pcode: significant code, e.g., ⁠**⁠, *, -

Value

No return. This function is used to calculate data for gglot2 ⁠geom_*⁠, just like ggplot2::stat_smooth().

Examples

library(ggplot2)
library(data.table)

dat <- data.table(mtcars)
dat$cyl <- as.factor(dat$cyl)
table(dat$cyl)

ggplot(dat, aes(wt, mpg, color = cyl)) +
    geom_point() +
    stat_reg(data = dat[cyl != 4], y = 1, mar = 0, position = "none") +
    facet_wrap(~cyl)

ggplot(dat, aes(wt, mpg, color = cyl)) +
  geom_point() +
  stat_reg(data = dat[cyl != 4], y = 1,
               position = "dodge",
               height.factor = 1.2,
               unit = "gC m^-2 d^-1")

ggplot(dat, aes(wt, mpg, color = cyl)) +
  geom_point() +
  stat_reg(data = dat[cyl != 4], y = 1,
               position = "none",
               height.factor = 1.2,
               unit = "gC m^-2 d^-1") +
  facet_wrap(~cyl)


ggplot(dat, aes(wt, mpg, color = cyl)) +
    geom_point() +
    stat_gof(x = 0, y = 1) +
    # stat_reg(data = subset(dat, cyl == 4), y = 1, color = "red") +
    # stat_reg(data = subset(dat, cyl == 6), y = 0.8) +
    facet_wrap(~cyl)
library(ggplot2)
library(data.table)

dat <- data.table(mtcars)
dat$cyl <- as.factor(dat$cyl)
table(dat$cyl)

ggplot(dat, aes(wt, mpg, color = cyl)) +
    geom_point() +
    stat_reg(data = dat[cyl != 4], y = 1, mar = 0, position = "none") +
    facet_wrap(~cyl)

ggplot(dat, aes(wt, mpg, color = cyl)) +
  geom_point() +
  stat_reg(data = dat[cyl != 4], y = 1,
               position = "dodge",
               height.factor = 1.2,
               unit = "gC m^-2 d^-1")

ggplot(dat, aes(wt, mpg, color = cyl)) +
  geom_point() +
  stat_reg(data = dat[cyl != 4], y = 1,
               position = "none",
               height.factor = 1.2,
               unit = "gC m^-2 d^-1") +
  facet_wrap(~cyl)


ggplot(dat, aes(wt, mpg, color = cyl)) +
    geom_point() +
    stat_gof(x = 0, y = 1) +
    # stat_reg(data = subset(dat, cyl == 4), y = 1, color = "red") +
    # stat_reg(data = subset(dat, cyl == 6), y = 0.8) +
    facet_wrap(~cyl)

stat_gof2

Description

stat_gof2

Usage

stat_gof2(
  mapping = NULL,
  data = NULL,
  geom = GeomRichTextNpc,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  show.bias = TRUE,
  label.format = fmt_gof,
  x = 0.05,
  y = 0.95,
  inherit.aes = TRUE,
  ...
)

geom_gof2(
  mapping = NULL,
  data = NULL,
  stat = StatGOF2,
  position = "identity",
  ...,
  show.bias = TRUE,
  label.format = fmt_gof,
  eval.flood = FALSE,
  x = 0,
  y = 1,
  hjust = 0,
  vjust = 1,
  size = 5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
stat_gof2(
  mapping = NULL,
  data = NULL,
  geom = GeomRichTextNpc,
  position = "identity",
  na.rm = FALSE,
  show.legend = NA,
  show.bias = TRUE,
  label.format = fmt_gof,
  x = 0.05,
  y = 0.95,
  inherit.aes = TRUE,
  ...
)

geom_gof2(
  mapping = NULL,
  data = NULL,
  stat = StatGOF2,
  position = "identity",
  ...,
  show.bias = TRUE,
  label.format = fmt_gof,
  eval.flood = FALSE,
  x = 0,
  y = 1,
  hjust = 0,
  vjust = 1,
  size = 5,
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function. Cannot be jointy specified with nudge_x or nudge_y.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

label.format

default value: "*NSE* = {str_num(NSE,2)}, *R^2* = {str_num(R2, 2)} \n *RMSE* = {str_num(RMSE,2)}".

label.format will be evaluated by glue::glue(). Variables inside {} will be evaluated. All variables returned by GOF() are supported.

x

A numeric vector or unit object specifying x-values.

y

A numeric vector or unit object specifying y-values.

inherit.aes

...

stat

The statistical transformation to use on the data for this layer, as a string.

Value

No return. This function is used to calculate data for gglot2 ⁠geom_*⁠, just like ggplot2::stat_smooth().

required axes

obs: observed
sim: simulated

Examples

library(ggplot2)
library(data.table)

dates <- seq(as.Date("2010-01-01"), length.out = 32, by = "day")
dat <- data.table(mtcars) %>% cbind(date = dates, .)
dat$cyl <- as.factor(dat$cyl)
# table(dat$cyl)

ggplot(dat, aes(date, mpg, color = cyl)) +
  stat_gof2(aes(obs = mpg, sim = wt), x = 0, y = 1) +
  geom_point() +
  facet_wrap(~cyl)

## Example 2
dat = GPP_US_MMS
ggplot(dat, aes(date, GPP)) +
  geom_line() +
  stat_gof2(aes(obs=GPP, sim=SM), x = 0, y = 1)

## 
dat = data.table(
  obs = c(10, 12, 15, 14, 13, 16, 18, 20, 19, 22),
  sim = c(11, 13, 14, 15, 12, 17, 17, 21, 20, 20),
  sim2 = c(11, 13, 14, 15, 12, 17, 17, 21, 20, 25),
  group = rep(c("A", "B"), each = 5)
)

showtext::showtext_auto()
fmt_gof <- "*NSE* = {str_num(NSE,2)}, *R^2* = {str_num(R2, 2)}"

p = ggplot(dat, aes(obs, sim)) +
  geom_point() +
  stat_gof2(aes(obs = obs, sim = sim), x = 0, y = 1, 
    eval.flood = TRUE, show.bias = FALSE, label.format = fmt_gof, size = 6) + 
  stat_gof2(aes(obs = obs, sim = sim2), x = 0, y = 0.9, 
    eval.flood = TRUE, show.bias = FALSE, label.format = fmt_gof, size = 6)

# write_fig(p, "d:/Rplot.pdf", 10, 5)
library(ggplot2)
library(data.table)

dates <- seq(as.Date("2010-01-01"), length.out = 32, by = "day")
dat <- data.table(mtcars) %>% cbind(date = dates, .)
dat$cyl <- as.factor(dat$cyl)
# table(dat$cyl)

ggplot(dat, aes(date, mpg, color = cyl)) +
  stat_gof2(aes(obs = mpg, sim = wt), x = 0, y = 1) +
  geom_point() +
  facet_wrap(~cyl)

## Example 2
dat = GPP_US_MMS
ggplot(dat, aes(date, GPP)) +
  geom_line() +
  stat_gof2(aes(obs=GPP, sim=SM), x = 0, y = 1)

## 
dat = data.table(
  obs = c(10, 12, 15, 14, 13, 16, 18, 20, 19, 22),
  sim = c(11, 13, 14, 15, 12, 17, 17, 21, 20, 20),
  sim2 = c(11, 13, 14, 15, 12, 17, 17, 21, 20, 25),
  group = rep(c("A", "B"), each = 5)
)

showtext::showtext_auto()
fmt_gof <- "*NSE* = {str_num(NSE,2)}, *R^2* = {str_num(R2, 2)}"

p = ggplot(dat, aes(obs, sim)) +
  geom_point() +
  stat_gof2(aes(obs = obs, sim = sim), x = 0, y = 1, 
    eval.flood = TRUE, show.bias = FALSE, label.format = fmt_gof, size = 6) + 
  stat_gof2(aes(obs = obs, sim = sim2), x = 0, y = 0.9, 
    eval.flood = TRUE, show.bias = FALSE, label.format = fmt_gof, size = 6)

# write_fig(p, "d:/Rplot.pdf", 10, 5)

geom_interval

Description

geom_interval

Usage

stat_interval(
  mapping = NULL,
  data = NULL,
  geom = GeomInterval,
  position = "identity",
  interval = 0.8,
  fun_middle = "median",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

geom_interval(
  mapping = NULL,
  data = NULL,
  stat = "interval",
  position = "identity",
  ...,
  fun_middle = "median",
  interval = 0.8,
  alpha.line = 0.7,
  param_ensemble = list(),
  param_slope = list(alpha = 1, linewidth = 1),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
stat_interval(
  mapping = NULL,
  data = NULL,
  geom = GeomInterval,
  position = "identity",
  interval = 0.8,
  fun_middle = "median",
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

geom_interval(
  mapping = NULL,
  data = NULL,
  stat = "interval",
  position = "identity",
  ...,
  fun_middle = "median",
  interval = 0.8,
  alpha.line = 0.7,
  param_ensemble = list(),
  param_slope = list(alpha = 1, linewidth = 1),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

geom

A Geom ggproto subclass, for example GeomPoint.
A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".
For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

interval

interval of confidence interval, default is 0.8

fun_middle

function to calculate middle value, default is median

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

alpha.line

alpha of ensemble line

param_ensemble

list of parameters for ensemble line

param_slope

list of parameters for slope line

Examples

library(ggplot2)
df <- CMIP6_HWD

p <- ggplot(df, aes(year, value, color = prob, fill = prob))

# both line and fill
p + geom_interval(alpha = 0.2, alpha.line = 1, 
  linewidth = 0.7, linetype = 2, # for ensemble line
  param_slope = list(linewidth = 1, alpha = 1, linetype = 1), # slope line
  interval = 0.8, fun_middle = "mean")

# only line
p + geom_interval(
  fill = "NA",
  alpha = 0.4, interval = 0.8, fun_middle = "mean", linewidth = 0.4
) +
  theme(legend.key = element_rect(fill = "NA"))

# only fill
p + geom_interval(
  color = "NA", key_glyph = "polygon2",
  alpha = 0.4, interval = 0.8, fun_middle = "mean", linewidth = 0.4
) +
  theme(legend.key = element_rect(fill = "NA"))
library(ggplot2)
df <- CMIP6_HWD

p <- ggplot(df, aes(year, value, color = prob, fill = prob))

# both line and fill
p + geom_interval(alpha = 0.2, alpha.line = 1, 
  linewidth = 0.7, linetype = 2, # for ensemble line
  param_slope = list(linewidth = 1, alpha = 1, linetype = 1), # slope line
  interval = 0.8, fun_middle = "mean")

# only line
p + geom_interval(
  fill = "NA",
  alpha = 0.4, interval = 0.8, fun_middle = "mean", linewidth = 0.4
) +
  theme(legend.key = element_rect(fill = "NA"))

# only fill
p + geom_interval(
  color = "NA", key_glyph = "polygon2",
  alpha = 0.4, interval = 0.8, fun_middle = "mean", linewidth = 0.4
) +
  theme(legend.key = element_rect(fill = "NA"))

prob density

Description

prob density

Usage

stat_prob_2d(
  mapping = NULL,
  data = NULL,
  geom = "density_2d",
  position = "identity",
  ...,
  contour = TRUE,
  contour_var = "density",
  n = 100,
  h = NULL,
  adjust = c(1, 1),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)
stat_prob_2d(
  mapping = NULL,
  data = NULL,
  geom = "density_2d",
  position = "identity",
  ...,
  contour = TRUE,
  contour_var = "density",
  n = 100,
  h = NULL,
  adjust = c(1, 1),
  na.rm = FALSE,
  show.legend = NA,
  inherit.aes = TRUE
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

geom

Use to override the default connection between stat_prob_2d.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

...

Arguments passed on to geom_contour

binwidth

The width of the contour bins. Overridden by bins.

bins

Number of contour bins. Overridden by breaks.

breaks

One of:

Numeric vector to set the contour breaks
A function that takes the range of the data and binwidth as input and returns breaks as output. A function can be created from a formula (e.g. ~ fullseq(.x, .y)).

Overrides binwidth and bins. By default, this is a vector of length ten with pretty() breaks.

contour

If TRUE, contour the results of the 2d density estimation.

contour_var

Character string identifying the variable to contour by. Can be one of "density", "ndensity", or "count". See the section on computed variables for details.

n

Number of grid points in each direction.

h

Bandwidth (vector of length two). If NULL, estimated using MASS::bandwidth.nrd().

adjust

A multiplicative bandwidth adjustment to be used if 'h' is 'NULL'. This makes it possible to adjust the bandwidth while still using the a bandwidth estimator. For example, adjust = 1/2 means use half of the default bandwidth.

na.rm

If FALSE, the default, missing values are removed with a warning. If TRUE, missing values are silently removed.

show.legend

inherit.aes

Examples

library(ggplot2)
 
# Data
n = 200
set.seed(1)
a <- data.frame( x=rnorm(n, 10, 1.9), y=rnorm(n, 10, 1.2) )
b <- data.frame( x=rnorm(n, 14.5, 1.9), y=rnorm(n, 14.5, 1.9) )
c <- data.frame( x=rnorm(n, 9.5, 1.9), y=rnorm(n, 15.5, 1.9) )
data <- rbind(a,b,c)

# Show the area only
ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(fill = ..level.., color =..level.. ), geom = "polygon")

ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(fill = ..level..), geom = "polygon", color = "white")

ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(color =..level.. ), geom = "path")
library(ggplot2)
 
# Data
n = 200
set.seed(1)
a <- data.frame( x=rnorm(n, 10, 1.9), y=rnorm(n, 10, 1.2) )
b <- data.frame( x=rnorm(n, 14.5, 1.9), y=rnorm(n, 14.5, 1.9) )
c <- data.frame( x=rnorm(n, 9.5, 1.9), y=rnorm(n, 15.5, 1.9) )
data <- rbind(a,b,c)

# Show the area only
ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(fill = ..level.., color =..level.. ), geom = "polygon")

ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(fill = ..level..), geom = "polygon", color = "white")

ggplot(data, aes(x=x, y=y) ) +
  stat_prob_2d(aes(color =..level.. ), geom = "path")

geom_signHatch

Description

geom_signHatch

Usage

stat_signHatch(
  mapping = NULL,
  data = NULL,
  geom = "sf",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  density = 1,
  angle = 45
)

geom_signHatch(
  mapping = aes(),
  data = NULL,
  stat = "signHatch",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  density = 1,
  angle = 45
)
stat_signHatch(
  mapping = NULL,
  data = NULL,
  geom = "sf",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  density = 1,
  angle = 45
)

geom_signHatch(
  mapping = aes(),
  data = NULL,
  stat = "signHatch",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  density = 1,
  angle = 45
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

geom

A Geom ggproto subclass, for example GeomPoint.
A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".
For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

You can also set this to one of "polygon", "line", and "point" to override the default legend.

inherit.aes

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

density

angle

the slope of shading lines, given as an angle in degrees (counter-clockwise).

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

Aesthetics

geom_signHatch() requires the following aesthetics:

x:
y:
mask:

Examples

library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) #%>% as.data.frame()

ggplot() +
    geom_raster(data = d_trendPerc, aes(x, y, fill = perc)) +
    # geom_sf(data = shp) +
    geom_signHatch(data = d_mask, aes(x, y, mask = mask), color = "red")
library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) #%>% as.data.frame()

ggplot() +
    geom_raster(data = d_trendPerc, aes(x, y, fill = perc)) +
    # geom_sf(data = shp) +
    geom_signHatch(data = d_mask, aes(x, y, mask = mask), color = "red")

stat_signPattern

Description

stat_signPattern

Usage

stat_signPattern(
  mapping = NULL,
  data = NULL,
  geom = "sf_pattern",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)
stat_signPattern(
  mapping = NULL,
  data = NULL,
  geom = "sf_pattern",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

show.legend

inherit.aes

...

other parameters to ggpattern::geom_sf_pattern()

Examples

library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) # %>% as.data.frame()

# significant part; geom_sf_pattern still has bug unsolved.
ggplot() +
  geom_raster(data = d_trendPerc, aes(x, y, fill = perc)) +
  stat_signPattern(data = d_mask, aes(x, y, mask = mask),
                   fill = "transparent", color = "red",
                   pattern_density = 0.02)

# insignificant
ggplot() +
    geom_raster(data = d_trendPerc, aes(x, y, fill = perc)) +
    stat_signPattern(data = d_mask, aes(x, y, mask = !mask),
                     fill = "transparent", color = "red",
                     pattern_density = 0.02) #-> p
# Ipaper::write_fig(p, "temp.pdf")
library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) # %>% as.data.frame()

# significant part; geom_sf_pattern still has bug unsolved.
ggplot() +
  geom_raster(data = d_trendPerc, aes(x, y, fill = perc)) +
  stat_signPattern(data = d_mask, aes(x, y, mask = mask),
                   fill = "transparent", color = "red",
                   pattern_density = 0.02)

# insignificant
ggplot() +
    geom_raster(data = d_trendPerc, aes(x, y, fill = perc)) +
    stat_signPattern(data = d_mask, aes(x, y, mask = !mask),
                     fill = "transparent", color = "red",
                     pattern_density = 0.02) #-> p
# Ipaper::write_fig(p, "temp.pdf")

stat_signPoint

Description

stat_signPoint

Usage

stat_signPoint(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  fact = 1
)

geom_signPoint(
  mapping = aes(),
  data = NULL,
  stat = "signPoint",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  fact = 1
)
stat_signPoint(
  mapping = NULL,
  data = NULL,
  geom = "point",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  fact = 1
)

geom_signPoint(
  mapping = aes(),
  data = NULL,
  stat = "signPoint",
  position = "identity",
  show.legend = NA,
  inherit.aes = TRUE,
  ...,
  fact = 1
)

Arguments

mapping

data

The data to be displayed in this layer. There are three options:

If NULL, the default, the data is inherited from the plot data as specified in the call to ggplot().

A data.frame, or other object, will override the plot data. All objects will be fortified to produce a data frame. See fortify() for which variables will be created.

geom

A Geom ggproto subclass, for example GeomPoint.
A string naming the geom. To give the geom as a string, strip the function name of the geom_ prefix. For example, to use geom_point(), give the geom as "point".
For more information and other ways to specify the geom, see the layer geom documentation.

position

A position adjustment to use on the data for this layer. This can be used in various ways, including to prevent overplotting and improving the display. The position argument accepts the following:

The result of calling a position function, such as position_jitter(). This method allows for passing extra arguments to the position.
A string naming the position adjustment. To give the position as a string, strip the function name of the position_ prefix. For example, to use position_jitter(), give the position as "jitter".
For more information and other ways to specify the position, see the layer position documentation.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

You can also set this to one of "polygon", "line", and "point" to override the default legend.

inherit.aes

...

Static aesthetics that are not mapped to a scale, but are at a fixed value and apply to the layer as a whole. For example, colour = "red" or linewidth = 3. The geom's documentation has an Aesthetics section that lists the available options. The 'required' aesthetics cannot be passed on to the params. Please note that while passing unmapped aesthetics as vectors is technically possible, the order and required length is not guaranteed to be parallel to the input data.
When constructing a layer using a ⁠stat_*()⁠ function, the ... argument can be used to pass on parameters to the geom part of the layer. An example of this is stat_density(geom = "area", outline.type = "both"). The geom's documentation lists which parameters it can accept.
Inversely, when constructing a layer using a ⁠geom_*()⁠ function, the ... argument can be used to pass on parameters to the stat part of the layer. An example of this is geom_area(stat = "density", adjust = 0.5). The stat's documentation lists which parameters it can accept.
The key_glyph argument of layer() may also be passed on through .... This can be one of the functions described as key glyphs, to change the display of the layer in the legend.

fact

postive integer. Plot one point in fact steps.

stat

A Stat ggproto subclass, for example StatCount.
A string naming the stat. To give the stat as a string, strip the function name of the stat_ prefix. For example, to use stat_count(), give the stat as "count".
For more information and other ways to specify the stat, see the layer stat documentation.

Aesthetics

geom_signPoint() requires the following aesthetics:

x:
y:
mask (optional): Boolean, mask=TRUE is regarded as significant. Only plot regions with mask = TRUE.

Examples

library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) # %>% as.data.frame()

# the part of not significant
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_signPoint(aes(mask = !mask), fact = 2, shape = 4)

# significant
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_signPoint(aes(mask = mask), fact = 2)

## Another option
fact = 2
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_point(data = ~ resample_points(.x, fact))
library(gg.layers)
library(ggplot2)
data("d_trendPerc")

d_mask <- mutate(d_trendPerc, mask = perc <= 0.99) # %>% as.data.frame()

# the part of not significant
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_signPoint(aes(mask = !mask), fact = 2, shape = 4)

# significant
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_signPoint(aes(mask = mask), fact = 2)

## Another option
fact = 2
ggplot(data = d_mask, aes(x, y)) +
  geom_raster(aes(fill = perc)) +
  geom_point(data = ~ resample_points(.x, fact))

markdown superscript and subscript

Description

markdown superscript and subscript

Usage

str_mk(x)

label_mk(labels, ...)
str_mk(x)

label_mk(labels, ...)

Arguments

x

character vector

labels

character vector

...

ignored

Author(s)

Dongdong Kong

Examples

x <- c(
  "gC m^{-2} d^{-1}",
  "gC m^-2 d^-1",
  "gC m_{-2} d_{-1}",
  "gC m_-2 d_-1",
  "gC \n mm/d"
)
str_mk(x)
## use str_mk in ggplot
library(ggplot2)

d <- data.frame(
  x = 1:3, y = 1:3,
  varname = c("T_min", "T_max", "T_avg")
)

ggplot(d, aes(x, y)) +
  geom_point() +
  geom_richtext(aes(label = varname), x = 2, y = 2) +
  facet_wrap(~varname, labeller = label_mk) +
  theme(
    strip.text = element_markdown(face = "bold")
  )
x <- c(
  "gC m^{-2} d^{-1}",
  "gC m^-2 d^-1",
  "gC m_{-2} d_{-1}",
  "gC m_-2 d_-1",
  "gC \n mm/d"
)
str_mk(x)
## use str_mk in ggplot
library(ggplot2)

d <- data.frame(
  x = 1:3, y = 1:3,
  varname = c("T_min", "T_max", "T_avg")
)

ggplot(d, aes(x, y)) +
  geom_point() +
  geom_richtext(aes(label = varname), x = 2, y = 2) +
  facet_wrap(~varname, labeller = label_mk) +
  theme(
    strip.text = element_markdown(face = "bold")
  )

Rounding of Numbers, and convert to string

Description

Rounding of Numbers, and convert to string

Usage

str_num(x, digits = 2)
str_num(x, digits = 2)

Arguments

x

a numeric vector. Or, for round and signif, a complex vector.

digits

integer indicating the number of decimal places (round) or significant digits (signif) to be used. For round, negative values are allowed (see ‘Details’).

Examples

format(round(2, 2)) # 2
str_num(2, 2) # 2.00
format(round(2, 2)) # 2
str_num(2, 2) # 2.00

Package 'gg.layers'

Help Index

add_colorbar

Description

Usage

Arguments

add grob to a plot

Description

Usage

Arguments

Examples

colourbar_triangle

Description

Usage

Arguments

References

Examples

draw horizontal and vertical polygons

Description

Usage

Arguments

Examples

geom_annotation

Description

Usage

Arguments

Examples

geom_annotation

Description

Usage

Arguments

Examples

A box and whiskers plot (in the style of Tukey)

Description

Usage

Arguments

Aesthetics

Summary statistics

References

See Also

Examples

geom_hspan

Description

Usage

Arguments

Examples

geom_latFreq

Description

Usage

Arguments

Examples

geom_mk

Description

Usage

Arguments

Value

Examples

geom_movmean

Description

Usage

Arguments

Examples

Draw precipitation bar on the top of the panel

Description

Usage

Arguments

Aesthetics

Author(s)

Examples

geom_raster_filled

Description

Usage

Arguments

Text with Normalised Parent Coordinates

Description

Usage

Arguments

Aesthetics

See Also

Examples