New features and enhancements:
stat_slabinterval()
can
now be shared across sub-geometries:
.width
and level
computed variables
can now be used in slab / dots sub-geometries. These values correspond
to the smallest interval computed in the interval sub-geometry
containing that portion of the slab. This gives a more flexible
alternative to using cut_cdf_qi()
to create densities
filled according to a set of intervals (this approach which also works
on highest-density intervals, which cut_cdf_qi()
does not).
Examples in vignette("slabinterval")
have been updated to
use the new approach, and an example has been added to
vignette("dotsinterval")
showing how to color dots by
intervals.options(ggdist.experimental.slab_data_in_intervals = TRUE)
,
the pdf
and cdf
computed variables can now be
used in interval sub-geometries to get the PDF and CDF at the point
summary. pdf_min
, pdf_max
,
cdf_min
, and cdf_max
also give the PDF and CDF
at the lower and upper ends of the interval. An example in
vignette("lineribbon")
shows how to use this to make
lineribbon gradients whose color approximates density (as opposed to the
classic gradient fan chart examples already in that vignette, where
color approximates the CDF).scale_thickness_shared()
is now provided to allow the
thickness scale to be shared across geometries, making certain plot
types easier to create (e.g. plots of prior and posterior densities
together). See vignette("slabinterval")
for an
example.thickness
is less than 0 it is normalized to have a
minimum of zero when normalization is turned on; this makes it easier to
use slab functions that go below zero. A new example in
vignette("slabinterval")
shows how to use this to create raindrop plots.geom_dotsinterval(layout = "bin")
can now be set using the
order
aesthetic. This makes it possible to create “stacked”
dotplots by mapping a discrete variable onto the order
aesthetic (#132). As part of this change, bin_dots()
now
maintains the original data order within bins when
layout = "bin"
. See an example in
vignette("dotsinterval")
.verbose = TRUE
flag in
geom_dotsinterval()
outputs the selected
binwidth
in both data units and normalized parent
coordinates. This may be useful if you want to start with an
automatically-selected bin width and then adjust it manually. Though
note: if you just want to scale the selected bin width to fit within a
desired area, it is probably better to use scale
, and if
you want to provide constraints on the bin width, you can pass a
2-vector to binwidth
.expand
argument in stat_slabinterval()
can now take a length-two logical vector to control expansion to the
lower and upper limits respectively (#129). Thanks to @teunbrand.geom_dotsinterval()
now supports the
family
aesthetic for setting the font used to display its
dots (based on a conversation with @gdbassett).guide_rampbar()
for creating gradient-like
legends for continuous color/fill ramp scales, based on
ggplot2::guide_colorbar()
. See an example in
vignette("lineribbon")
.Bug fixes:
NA
s in the thickness
aesthetic of a slab, these are now rendered as gaps in the slab
(#129).Bug fixes:
point_interval
argument
of stat_slabinterval()
, a function with that name will be
searched for in the calling environment and the ggdist
package environment. The latter ensures that stat
s work
when ggdist is loaded but not attached to the search path (#128).New features and enhancements:
stat_sample_...
and stat_dist_...
families of stats have been merged (#83).
stat_dist_...
stats are deprecated in favor of
their stat_...
counterparts, which now understand the
dist
, args
, and
arg1
…arg9
aesthetics.xdist
and ydist
can now be used in place
of the dist
aesthetic to specify the axis one is mapping a
distribution onto (dist
may be deprecated in the
future).x
or y
aesthetics now raise a helpful error message suggesting you probably
want to use xdist
or ydist
.expand
parameter to
stat_slabinterval()
allows explicitly setting whether or
not the slab is expanded to the limits of the scale (rather than
implicitly setting this based on slab_type
).point_interval()
family of functions can now be
passed distributional
and posterior::rvar()
objects, meaning that means and modes (in addition to medians) and
highest-density intervals (in addition to quantile intervals) can now be
visualized for analytical distributions.
rvar
s will generate a .index
column when
passed to point_interval()
functions (#111). Based on a
suggestion from @mitchelloharawild.stat_ribbon()
provided as a shortcut stat for
stat_lineribbon()
with no line (#48). Also, if you supply
only an x
or y
aesthetic to
geom_lineribbon()
, you will get ribbons without a line
(#127).ul()
(upper limit) or ll()
(lower limit),
e.g. with point_interval()
explicitly or via
mean_ll()
, median_ll()
,
mode_ll()
, mean_ul()
,
median_ul()
, or mode_ul()
(#49).scale
more
often.1.07
for dot sizes
is now exposed as the default value of the dotsize
parameter instead of being applied internally. This fudge factor tends
(in my opinion) to make dotplots look a bit better due to the visual
distance between circles, but is (I think) better used as an explicit
value than an implicit one, hence the change. This may create subtle
changes to plots that use the dotsize
or
stackratio
parameters, but allows those parameters to have
a more precise geometric interpretation.Documentation:
stat_dotsinterval()
sub-family:
vignette("dotsinterval")
(#120).stat_slabinterval()
and geom_slabinterval()
family: each shortcut stat/geom now has its own documentation page that
comprehensively lists all parameters, aesthetics, and computed
variables, including those pulled in via ...
from
typically-paired geoms. These docs are auto-generated and should be easy
to maintain going forward. (#36)stat_lineribbon()
and
geom_lineribbon()
family now also has separate
documentation pages with a comprehensive listing of aesthetics and
parameters (#107).vignette("slabinterval")
using the new expand
parameter (#115).Deprecations and removals:
.prob
argument, a long-deprecated alias for
.width
, was removed.limits_function
, limits_args
,
slab_function
, slab_args
,
interval_function
, and interval_args
arguments
to stat_slabinterval()
were removed: these were largely
internal-use parameters only needed by subclasses of the base class for
creating shortcut stats, yet added a lot of noise to the documentation,
so these were replaced with the $compute_limits()
,
$compute_slabs()
, and $compute_intervals()
methods on the new AbstractStatSlabinterval
internal base
class.Bug fixes:
NA
s for analytical
distributions."bin"
and "weave"
layouts could be incorrect
with aesthetics mapped at a sub-bin level.stackratio
s that are not equal to 1
are
now accounted for in find_dotplot_binwidth()
(i.e. automatic dotplot bin width selection).fill_ramp
aesthetic ramps
them to the same color.Bug fixes:
distributional
>=
0.2.2.9000 (#91).stat_sample_slabinterval()
(#98).linearGradient()
function on R
< 4.1.geom_slabinterval()
.Breaking changes:
geom_slabinterval()
family geoms
when using position_dodge()
is now slightly different in
order to match up with how other geoms are positioned (#85). This may
slightly change existing charts that use
position = "dodge"
, and in some cases may cause slabs to be
drawn slightly outside plot boundaries, but makes it much easier to
combine geom_slabinterval()
with other geoms in the
expected way. If dodging more similar to the old approach is needed, use
the new “justification-preserving dodge”,
position_dodgejust()
, in place of
position_dodge()
.New features:
geom_slabinterval()
, side
,
justification
, and scale
can now be used as
aesthetics instead of parameters, allowing them to vary across slabs
within the same geom.fill
s within a slab in
geom_slabinterval()
can now be drawn as true gradients
rather than segmented polygons in R >= 4.1 by setting
fill_type = "gradient"
. This substantially improves the
appearance of gradient fills in graphics engines that support it
(#44).stat_dist_slabinterval()
and company now detect
discrete distributions and display them as histograms (#19).geom_dotsinterval()
now adjusts bin widths on discrete
distributions when they would result in bins that are taller than the
allocated space to ensure that they fit within the required space
(#42).geom_dotsinterval()
bin width by passing a vector of two
values to the binwidth
parameter.geom_dotsinterval()
has been factored out and exported as
find_dotplot_binwidth()
and bin_dots()
for
others to use (#77).curve_interval()
used a common (but naive)
approach to finding a cutoff on data depth to identify the X% “deepest”
curves, simply taking the envelope around the X% quantile of curves
ranked by depth. This is quite conservative and tends to create
intervals that are too wide; curve_interval()
now searches
for a cutoff in data depth such that X% of curves are contained within
its envelope (#67).point_interval()
and company now accept
distributional
objects and posterior::rvar()
s
(full support for distributional
objects requires
distributional
> 0.2.2).New documentation:
Substantial improvements to the documentation of aesthetics and
computed variables in geom_slabinterval()
,
stat_slabinterval()
, and company, listing all custom
aesthetics, computed variables, and their usage.
Several new examples in vignette("slabinterval")
,
including “rain cloud” plots and an example of histograms for discrete
analytical distributions.
Bug fixes:
stat_dist_slabinterval()
preserves group order
(#88).n
for
stat_sample_slabinterval()
.NA
handling across the
geoms (#74, #51).New features:
"weave"
and "swarm"
layouts for dots
geoms (#64). These provide alternative layouts that keep datapoints in
their actual positions on the data axis. The "weave"
layout
maintains rows but not columns and works well for quantile dotplots; the
"swarm"
layout uses the "compactswarm"
method
from beeswarm::beeswarm()
(courtesy James Trimble) and
works well on sample data. See the dotplot section of
vignette("slabinterval")
for comparisons.unit()
to specify bin widths manually
for dots geoms and stats, which can be helpful when you need dotplots
across facets to have the same bin width (#53).New documentation:
fill_ramp
in
vignette("lineribbon")
.vignette("slabinterval")
.vignette("slabinterval")
.Bug fixes:
New features:
pdf
and cdf
computed variables for the
stat_sample_slabinterval()
subfamily. See new examples of
usage in the last section of vignette("slabinterval")
.
(#11)cut_cdf_qi()
for creating (amongst other things)
interval-filled halfeyes, in the style of
bayesplot::mcmc_areas()
(#11)fill_ramp
and color_ramp
scales to
geom_slabinterval()
and geom_lineribbon()
families, making it easier to separate group colors from
interval/density/CDF colors. See new examples in
vignette("slabinterval")
,
vignette("lineribbon")
, and
vignette("freq-uncertainty-vis")
. (#16)brms::brmsprior
implementation for
parse_dist()
(#34)New documentation:
vignette("freq-uncertainty-vis")
now uses
distributional::dist_student_t()
(#14)vignette("slabinterval")
(#23)vignette("lineribbon")
(#22)interval_size_range
argument in
docs (#35)Bug fixes:
na.rm
support to
curve_interval()
(#22)New features and documentation:
curve_interval()
for generating curvewise (joint)
intervals for curve boxplots (#22)vignette("lineribbon")
describing
geom_lineribbon()
, stat_lineribbon()
,
stat_dist_lineribbon()
, and
curve_interval()
.Bug fixes:
dist
aesthetics that are factors (#25)vignette("slabinterval")
(#14).stat_dist_...
geoms now calculate pdf
and
cdf
columns to allow mashup geoms that involve both
functions, such as Correll-style gradient plots combined with violins,
as in Helske et al. (#11).stat_dist_...
geoms should now work with
gganimate
(#15).broom::augment()
defaulting to
se_fit = FALSE
.point_interval()
),
vignette("slabinterval")
, and
vignette("freq-uncertainty-vis")
. Tidybayes will retain all
other functions, and will re-export all ggdist
functions
for now.h
-suffix geoms are now deprecated. Those geoms
have been left in tidybayes
and give a deprecation warning
when used; they cannot be used from ggdist
directly.geom_interval()
, geom_pointinterval()
, and
geom_lineribbon()
no longer automatically set the
ymin
and ymax
aesthetics if
.lower
or .upper
are present in the data. This
allows them to work better with automatic orientation detection (and was
a bad feature to have existed in the first place anyway). The deprecated
tidybayes::geom_intervalh()
and
tidybayes::geom_pointintervalh()
still automatically set
those aesthetics, since they are deprecated anyway (so supporting the
old behavior is fine in these functions).geom_lineribbon()
/stat_lineribbon()
now
supports a step
argument for creating stepped lineribbons.
H/T to Solomon Kurz for the suggestion.ggdist
now has its own implementation of the scaled and
shifted Student’s t distribution (dstudent_t()
,
qstudent_t()
, etc), since it is very useful for visualizing
confidence distributions.