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.