Given a dataset with alluvial structure, stat_flow
calculates the centroids
(x
and y
) and heights (ymin
and ymax
) of the flows between each pair
of adjacent axes.
stat_flow(
mapping = NULL,
data = NULL,
geom = "flow",
position = "identity",
decreasing = NULL,
reverse = NULL,
absolute = NULL,
discern = FALSE,
negate.strata = NULL,
aes.bind = NULL,
infer.label = FALSE,
min.y = NULL,
max.y = NULL,
na.rm = FALSE,
show.legend = NA,
inherit.aes = TRUE,
...
)
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.
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)
).
The geometric object to use display the data; override the default.
Position adjustment, either as a string naming the adjustment
(e.g. "jitter"
to use position_jitter
), or the result of a call to a
position adjustment function. Use the latter if you need to change the
settings of the adjustment.
Logical; whether to arrange the strata at each axis
in the order of the variable values (NA
, the default),
in ascending order of totals (largest on top, FALSE
), or
in descending order of totals (largest on bottom, TRUE
).
Logical; if decreasing
is NA
,
whether to arrange the strata at each axis
in the reverse order of the variable values,
so that they match the order of the values in the legend.
Ignored if decreasing
is not NA
.
Defaults to TRUE
.
Logical; if some cases or strata are negative,
whether to arrange them (respecting decreasing
and reverse
)
using negative or absolute values of y
.
Passed to to_lodes_form()
if data
is in
alluvia format.
A vector of values of the stratum
aesthetic to be
treated as negative (will ignore missing values with a warning).
At what grouping level, if any, to prioritize differentiation
aesthetics when ordering the lodes within each stratum. Defaults to
"none"
(no aesthetic binding) with intermediate option "flows"
to bind
aesthetics after stratifying by axes linked to the index axis (the one
adjacent axis in stat_flow()
; all remaining axes in stat_alluvium()
)
and strongest option "alluvia"
to bind aesthetics after stratifying by
the index axis but before stratifying by linked axes (only available for
stat_alluvium()
). Stratification by any axis is done with respect to the
strata at that axis, after separating positive and negative strata,
consistent with the values of decreasing
, reverse
, and absolute
.
Thus, if "none"
, then lode orderings will not depend on aesthetic
variables. All aesthetic variables are used, in the order in which they are
specified in aes()
.
Logical; whether to assign the stratum
or alluvium
variable to the label
aesthetic. Defaults to FALSE
, and requires that
no label
aesthetic is assigned. This parameter is intended for use only
with data in alluva form, which are converted to lode form before the
statistical transformation. Deprecated; use
ggplot2::after_stat()
instead.
Numeric; bounds on the heights of the strata to be
rendered. Use these bounds to exclude strata outside a certain range, for
example when labeling strata using ggplot2::geom_text()
.
Logical:
if FALSE
, the default, NA
lodes are not included;
if TRUE
, NA
lodes constitute a separate category,
plotted in grey (regardless of the color scheme).
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.
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. borders()
.
Additional arguments passed to ggplot2::layer()
.
stat_alluvium
, stat_flow
, and stat_stratum
require one
of two sets of aesthetics:
x
and at least one of alluvium
and stratum
any number of axis[0-9]*
(axis1
, axis2
, etc.)
Use x
, alluvium
, and/or stratum
for data in lodes format
and axis[0-9]*
for data in alluvia format (see alluvial-data
).
Arguments to parameters inconsistent with the format will be ignored.
Additionally, each stat_*()
accepts the following optional
aesthetics:
y
weight
order
group
label
y
controls the heights of the alluvia,
and may be aggregated across equivalent observations.
weight
applies to the computed variables (see that section below)
but does not affect the positional aesthetics.
order
, recognized by stat_alluvium()
and stat_flow()
, is used to
arrange the lodes within each stratum. It tolerates duplicates and takes
precedence over the differentiation aesthetics (when aes.bind
is not
"none"
) and lode guidance with respect to the remaining axes. (It replaces
the deprecated parameter lode.ordering
.)
group
is used internally; arguments are ignored.
label
is used to label the strata or lodes and must take a unique value
across the observations within each stratum or lode.
These and any other aesthetics are aggregated as follows:
Numeric aesthetics, including y
, are summed.
Character and factor aesthetics, including label
,
are assigned to strata or lodes provided they take unique values across the
observations within each (and are otherwise assigned NA
).
These can be used with
ggplot2::after_stat()
to control aesthetic evaluation.
n
number of cases in lode
count
cumulative weight of lode
prop
weighted proportion of lode
stratum
value of variable used to define strata
deposit
order in which (signed) strata are deposited
lode
lode label distilled from alluvia
(stat_alluvium()
and stat_flow()
only)
flow
direction of flow "to"
or "from"
from its axis
(stat_flow()
only)
The numerical variables n
, count
, and prop
are calculated after the
data are grouped by x
and weighted by weight
(in addition to y
).
The integer variable deposit
is used internally to sort the data before
calculating heights. The character variable lode
is obtained from
alluvium
according to distill
.
stat_stratum
, stat_alluvium
, and stat_flow
order strata and lodes
according to the values of several parameters, which must be held fixed
across every layer in an alluvial plot. These package-specific options set
global values for these parameters that will be defaulted to when not
manually set:
ggalluvial.decreasing
(each stat_*
): defaults to NA
.
ggalluvial.reverse
(each stat_*
): defaults to TRUE
.
ggalluvial.absolute
(each stat_*
): defaults to TRUE
.
ggalluvial.cement.alluvia
(stat_alluvium
): defaults to FALSE
.
ggalluvial.lode.guidance
(stat_alluvium
): defaults to "zigzag"
.
ggalluvial.aes.bind
(stat_alluvium
and stat_flow
): defaults to
"none"
.
See base::options()
for how to use options.
The previously defunct parameters weight
and aggregate.wts
have been
discontinued. Use y
and cement.alluvia
instead.
ggplot2::layer()
for additional arguments and
geom_alluvium()
and
geom_flow()
for the corresponding geoms.
Other alluvial stat layers:
stat_alluvium()
,
stat_stratum()
# illustrate positioning
ggplot(as.data.frame(Titanic),
aes(y = Freq,
axis1 = Class, axis2 = Sex, axis3 = Age,
color = Survived)) +
stat_stratum(geom = "errorbar") +
geom_line(stat = "flow") +
stat_flow(geom = "pointrange") +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) +
scale_x_discrete(limits = c("Class", "Sex", "Age"))
# alluvium--flow comparison
data(vaccinations)
gg <- ggplot(vaccinations,
aes(x = survey, stratum = response, alluvium = subject,
y = freq, fill = response)) +
geom_stratum(alpha = .5) +
geom_text(aes(label = response), stat = "stratum")
# rightward alluvial aesthetics for vaccine survey data
gg + geom_flow(stat = "alluvium", lode.guidance = "forward")
# memoryless flows for vaccine survey data
gg + geom_flow()
# size filter examples
gg <- ggplot(vaccinations,
aes(y = freq,
x = survey, stratum = response, alluvium = subject,
fill = response, label = response)) +
stat_stratum(alpha = .5) +
geom_text(stat = "stratum")
# omit small flows
gg + geom_flow(min.y = 50)
# omit large flows
gg + geom_flow(max.y = 100)
# negate missing entries
ggplot(vaccinations,
aes(y = freq,
x = survey, stratum = response, alluvium = subject,
fill = response, label = response,
alpha = response != "Missing")) +
stat_stratum(negate.strata = "Missing") +
geom_flow(negate.strata = "Missing") +
geom_text(stat = "stratum", alpha = 1, negate.strata = "Missing") +
scale_alpha_discrete(range = c(.2, .6)) +
guides(alpha = "none")
#> Warning: Using alpha for a discrete variable is not advised.
# \donttest{
# aesthetics that vary betwween and within strata
data(vaccinations)
vaccinations$subgroup <- LETTERS[1:2][rbinom(
n = length(unique(vaccinations$subject)), size = 1, prob = .5
) + 1][vaccinations$subject]
ggplot(vaccinations,
aes(x = survey, stratum = response, alluvium = subject,
y = freq, fill = response, label = response)) +
geom_flow(aes(alpha = subgroup)) +
scale_alpha_discrete(range = c(1/3, 2/3)) +
geom_stratum(alpha = .5) +
geom_text(stat = "stratum")
#> Warning: Using alpha for a discrete variable is not advised.
# can even set aesthetics that vary both ways
ggplot(vaccinations,
aes(x = survey, stratum = response, alluvium = subject,
y = freq, label = response)) +
geom_flow(aes(fill = interaction(response, subgroup)), aes.bind = "flows") +
scale_alpha_discrete(range = c(1/3, 2/3)) +
geom_stratum(alpha = .5) +
geom_text(stat = "stratum")
#> Warning: Using alpha for a discrete variable is not advised.
# }