library(loon.shiny)
Shiny
The shiny
R
package simplifies the creation of interactive analysis
web pages.
A shiny
application is composed of two components, a
ui
(user interface) and a server
function.
This ui
/server
pair are passed as arguments to
the shinyApp
function that creates a shiny
app. The ui
(user interface) creates the layout of the app,
guiding its users about the analysis by determining the objects that
appear and how they can be manipulated on such application. The
server
function reacts to modifications on the
ui
, defining the logic of the app. As the user interacts
with the page, the server
function reacts to make changes
in the display.
Loon
The loon
R
package provides an interactive visualization toolkit for
unconstrained, unscripted, and open-ended data exploration. It is
intended for data analysts themselves.
An important part of loon
’s interactivity is the
loon inspector which can can make changes specialized
to different loon
plots. Typically, the loon
inspector has a single instance. The inspector will adapt its display to
whichever of the different base loon
graphics
(scatterplots, graphs, histograms, serial axe plots, etc) is its focus
(e.g., the graphic display that last received a mouse or window focus
event.
For loon
users, it is a challenge to provide a
curated analysis that is still somewhat interactive. Snapshots
of different steps of the analysis are easily accommodated via
RMarkdown
, etc. but interaction is not.
Loon.shiny
Loon.shiny
transforms loon
widgets to
appear (with their inspector) in a shiny
web app.
loon
has a powerful inspector involving almost many
of the components considered essential for interaction on each graphic.
With loon.shiny
, this powerful interface can be inserted
into a shiny
app to provide a multitude of interactions at
once.
loon.shiny
provides analysts who explore data in
loon
the ability to incorporate selected interactive
components of that analysis in Rmarkdown
. In addition to
extending the possibilities for reproducible research, this can further
empower the viewer of that research to explore other possibilities
within the document itself.
The idea behind the implementation: In
loon.shiny
, loon
widgets are transformed to
static loonGrob
s created by the R
base
grid
package to provide low-level, general purpose graphics
functions. Note that, a loonGrob
contains all elements of a
loon
plot even some not drawn contents, i.e. deactivated
elements, hidden layers. All these essential contents are stored inside
an empty grob
possessing the argument values necessary to
draw them. When the server
function is fired, the
interactivity is realized by editing and redisplaying these
loonGrob
s.
Consider the classic iris
data set.
library(loon.shiny)
library(dplyr)
library(magrittr)
# Loon scatterplot
<- with(iris,
p l_plot(x = Petal.Width,
y = Sepal.Width,
color = Species)
)# Modify glyph to radial axes glyph.
'glyph'] <- l_glyph_add_serialaxes(p, data = iris)
p[# Fit a linear regression on each group (species)
for(s in unique(iris$Species)) {
# sub data set
<- iris %>%
subdata filter(Species == s)
# fitted line
<- lm(Sepal.Width ~ Petal.Width, data = subdata)
fit <- subdata$Petal.Width
x <- predict(fit, interval = "confidence")
pred <- order(x)
ord # Loon pipe model (connected with %T>%)
# Check ```help(`%T>%`)``` for more details
<- p %T>%
p # fitted line
l_layer_line(x = x[ord],
y = pred[, "fit"][ord],
color = "firebrick",
linewidth = 1.5,
index = "end") %T>%
# confidence interval
l_layer_line(x = c(x[ord], rev(x[ord]), x[ord][1]),
y = c(pred[, "lwr"][ord], rev(pred[, "upr"][ord]), pred[, "lwr"][ord][1]),
color = "grey50",
linewidth = 2,
index = "end")
}loon.shiny(p, plotRegionWidth = "400px")
The left panel is a scatterplot which receives mouse can be utilized
for direct manipulations. The right panel is an inspector, mainly for
indirect manipulations. Compared with the loon
one, it is
different that is composed of a world view window and six buttons
(Plot
, Linking
, Select
,
Modify
, Layer
and Glyph
). Each
channel will be popped up by pressing the corresponding button. Due to
very limited layout space, such design can make the inspector look
fresh.
Plot
panel:
Zooming and Panning: In loon
, they both are realized
by direct manipulation with cooperation of mouse and modifier keys
<shift>
. While, in shiny
, function
plotOutput()
cannot trace right click and scrolling yet.
Hence, we build two slider bars to control x
and
y
limits.
Axes: channel axes
is a central control of non-data
elements display, such as turning on/off labels, scales and guides or
flipping the horizontal and vertical axes.
Scale to: channel scale to
re-scales the plot
interior to some range: range of selected
points, range of
all points in the plot
and range of all plots objects in
all layers (world
).
Linking
panel: since we only have one graph, no
linking is required here. We will talk more about this in next
section.
Select
panel: channel select
is mainly
utilized to modify points selection. There are two main channels,
static
and dynamic
.
For static
, there are three buttons,
all
, none
and invert
indicating
to select all visible points, deselect all points and invert the current
selection status respectively.
For dynamic
, it is often used to switch the
selection mode.
select
: the brushing box is used for highlighting
points
deselect
: any highlighted points fall into brushing
box will be downlighted;
invert
: the status of points sweeped by brushing box
will be inverted, highlighted to downlighted, downlighted to
highlighted.
There are several noticeable difference here:
The select
panel in loon.shiny
does not
involve a by
channel. In loon
, users can
select by either brushing
or sweeping
.
However, in shiny
, the mode brushing
or
sweeping
is pre-defined in function
plotOutput()
and there is no way to update it. Once the app
is rendered, the select mode is set and cannot be switched.
Loon.shiny
has a sticky
radio box. It
is the same with <shift>
key in loon
(the usage of <shift>
key in loon can be found in loon
vignette or loon
talk). This is because shiny
does not include trace
functions to record key press so far.
by color
channel is replaced by check box in
shiny
, since shiny
does not include functions
to automatically generate new buttons in server
function.
However, such changes give an unexpected benefit, color names can be
detected easily.
Modify
panel: Except the layout, modify
panel largely restores the design of the loon
.
Color
: color
buttons are used to modify
element colors and the color picker widget provides users more
choice.
Activate
: activate
helps to deactivate
or reactivate elements. Deactivate
buttons turn selected
objects invisible and reactivate
buttons reactivate all
deactivated points.
Move
: Move
selected points to common
horizontal position, to vertical position, and etc (see loon
talk for more details).
Glyph
: Change the shape of the points.
Size
: Decrease or increase point size.
Layer
panel: this panel a simplified version of loon
layer tab. The top select box indicates which layer is under
activation and the buttons below are used to, move layer up or down a
level, make layer visible or invisible, add layer group (deprecated
now), delete layer and scale plot region to layer. The last command is
to customize the layer label.Glyph
panel: it is to modify the appearance of glyphs.
Note that different glyphs have very different glyph settings. For
example, the settings of serial axes glyphs include whether to show
enclosing box, display axes labels and fill the glyph region.Arbitrarily many plots may be created and linked in
loon
. Package loon.shiny
successfully inherits
such facility.
Following graph illustrates compound plots. The three graphs are
histogram of variable Sepal.Length
, scatterplot of
Sepal.Width
versus Sepal.Length
and swapped
histogram of variable Sepal.Width
(from top to bottom, from
left to right). They are colored by species and linked each other.
<- l_plot(iris, linkingGroup = "iris",
p1 showLabels = FALSE)
<- l_hist(iris$Sepal.Length, linkingGroup = "iris",
p2 showLabels = FALSE,
showStackedColors = TRUE)
<- l_hist(iris$Sepal.Width, color = iris$Species,
p3 linkingGroup = "iris",
showLabels = FALSE, swapAxes = TRUE,
showStackedColors = TRUE)
loon.shiny(list(p1, p2, p3),
layout_matrix = matrix(c(2,NA,1,3), nrow = 2, byrow = TRUE),
plotRegionWidth = "400px")
Loon
inspector is a singleton which means there is only
one instance of it. Each kind of graphics (scatterplots, graphs,
histograms, serial axes plots, etc) has its own specified inspector. The
shown one depends on which display receives the last mouse gesture input
or window focus event. However, such design in shiny
can be
very complex. Instead, we build a navigation bar menu. The inspector can
be switched by toggling tabpanel on the bar menu or the
last mouse gesture (<double click
>)
input.
If we brush on any of these plots, the corresponding elements on the
rest will be highlighted instantaneously. Linking status can be checked
via linking
panel.
The principal feature of loon
plots which effect the
linking of displays is the setting of a common
linkingGroup
. LinkingGroup
is used to identify
which group this plot joins. If it is set as “none”, then this plot will
not be linked with any of them.
LinkingStates
are states to be linked in the same
linkingGroup
. Unlike loon
, programming is
forbidden once the app is rendered. Thus, we list all the states can be
modified in the linking
panel. All elements in these three
pictures share the same selected/checked states. Suppose one un-checks
the selected
check box in scatterplot linking
panel, and then brushes the points on scatterplot, the corresponding
elements in other two histograms will not be highlighted
anymore.