yamlet (version 0.6.5)

ggplot.decorated: Create a New ggplot for a Decorated Data Frame

Description

Creates a new ggplot object for a decorated data.frame. This is the ggplot() method for class 'decorated'. It creates a ggplot object using the default method, but reclassifies it as 'decorated_ggplot' so that a custom print method is invoked; see print.decorated_ggplot.

Usage

# S3 method for decorated
ggplot(data, ...)

Arguments

data

decorated, see decorate

...

passed to ggplot

Value

return value like ggplot but inheriting 'decorated_ggplot'

Details

This approach is similar to but more flexible than the method for ggready. For finer control, you can switch between 'data.frame' and 'decorated' using as_decorated (supplies null decorations) and as.data.frame (preserves decorations).

See Also

decorate resolve ggready

Other decorated_ggplot: ggplot_build.decorated_ggplot(), print.decorated_ggplot()

Other interface: classified.data.frame(), decorate.character(), decorate.data.frame(), desolve.decorated(), io_csv.character(), io_csv.data.frame(), io_res.character(), io_table.character(), io_table.data.frame(), io_yamlet.character(), io_yamlet.data.frame(), is_parseable.default(), mimic.default(), modify.default(), promote.default(), read_yamlet(), resolve.decorated(), selected.default(), write_yamlet()

Examples

# NOT RUN {
file <- system.file(package = 'yamlet', 'extdata','quinidine.csv')
library(ggplot2)
library(dplyr)
library(magrittr)
# par(ask = FALSE)

x <- decorate(file)
x %<>% filter(!is.na(conc))

# Manipulate class to switch among ggplot methods.
class(x)
class(data.frame(x))
class(as_decorated(data.frame(x)))

# The bare data.frame gives boring labels and unordered groups.
map <- aes(x = time, y = conc, color = Heart)
data.frame(x) %>% ggplot(map) + geom_point()

# Decorated data.frame uses supplied labels.
# Notice CHF levels are still not ordered.
x %>% ggplot(map) + geom_point()

# We can resolve guide for a chance to enrich the output with units.
# Notice CHF levels are now ordered.
x %<>% resolve
suppressWarnings( # because this complains for columns with no units
  x <- modify(x, title = paste0(label, '\n(', units, ')'))
)
x %>% ggplot(map) + geom_point()

# Or something fancier.
x %<>% modify(conc, title = 'conc_serum. (mg*L^-1.)')
x %>% ggplot(map) + geom_point()

# The y-axis title is deliberately given in spork syntax for elegant coercion:
library(spork)
x %<>% modify(conc, expression = as.expression(as_plotmath(as_spork(title))))
x %>% ggplot(map) + geom_point()
# Add a fancier label for Heart, and facet by a factor:
x %<>% modify(Heart, expression = as.expression(as_plotmath(as_spork('CHF^\\*'))))
x %>% ggplot(map) + geom_point() + facet_wrap(~Creatinine)

# ggready handles the units and plotmath implicitly for a 'standard' display:
x %>% ggready %>% ggplot(map) + geom_point() + facet_wrap(~Creatinine)

# Notice that instead of over-writing the label
# attribute, we are creating a stack of label
# substitutes (title, expression) so that
# label is still available as an argument
# if we want to try something else.  The
# print method by default looks for all of these.
# Precedence is expression, title, label, column name.
# Precedence can be controlled using
# options(decorated_ggplot_search = c(a, b, ...) ).

# Here we try a dataset with conditional labels and units.

file <- system.file(package = 'yamlet', 'extdata','phenobarb.csv')
x <- file %>% decorate %>% resolve
# Note that value has two elements for label and guide.
x %>% decorations(value)

# The print method defaults to the first, with warning.
map <- aes(x = time, y = value, color = event)
# }
# NOT RUN {
x %>% ggplot(map) + geom_point()
# }
# NOT RUN {
# If we subset appropriately, the relevant value is substituted.
x %>% filter(event == 'conc') %>% ggplot(map) + geom_point()

x %>% filter(event == 'conc') %>%
ggplot(aes(x = time, y = value, color = ApgarInd)) + geom_point()

x %>% filter(event == 'dose') %>%
ggplot(aes(x = time, y = value, color = Wt)) +
geom_point() +
scale_y_log10() +
scale_color_gradientn(colours = rainbow(4))
# }