FinanceGraphs-Customization

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
suppressPackageStartupMessages(require(dplyr))
suppressPackageStartupMessages(require(data.table))
suppressPackageStartupMessages(require(ggplot2))
suppressPackageStartupMessages(require(FinanceGraphs))
options(datatable.print.keys=FALSE, datatable.print.class=FALSE)
knitr::opts_chunk$set(fig.width = 7)

Overview of Aesthetics Organization

Managing a consistent look across graphs is not easy, as there are so many parameters that are possible to change. ggplot2 does a great job allowing every detail to be customized, especially with the use of themes. However, adding all those customizations are burdensome, and ad-hoc changes to them can involve a great deal of programming. Ideally, we would like to keep our favorite looks in one place with an easy ability to change just a few pieces in an ad-hoc manner.

The functions in the package attempt to ease that burden with a middle layer of named aesthetic groups. Aesthetics can be managed just like any other data, so internal to the package is a data.table with the following character columns, plus a few others:

|Column|Description| |:-------|:------------------------| |Category|An "aesthetic set" key grouping together various subparts of a graph.| |(Ordering) Variable|Any string that can sorted to keep the aesthetics in a desired order| |Type|The type of aesthetic (e.g. color, size, symbol, etc) |Value|The actual aesthetic to be used. If a number, then each function casts appropriately| |used|Where the function is used|

Each FinanceGraphs function has internal aesthetic names (and defaults) that a user can modify, either persistently or temporarily. For example, the basic set of colors for categories is "lines", which are the line colors for fgts_dygraph() or the category colors for fg_scatplot.

fg_get_aes("lines", n_max=6)

Changing the look of graphs is as easy as changing the values in that internal dataset. In some cases (e.g. in fg_scatplot()) a user can make an entire new aesthetic set with a new (unique) name and directly specify it in the function call. The package keeps those changes persistently (by default), so each users' preferences should only need to be specified once.

Getting current aesthetics

There are two ways to get the aesthetic sets for every graph in the package:

For example, here are the a few aesthetic sets for fg_eventStudy(). This function just produces a summary, so for example there are actually 14 different line colors in "lines".

print(fg_print_aes_list("fg_eventStudy"))

Each set can have multiple rows, as in

fg_get_aes("espath_ls", n_max=6)

These correspond directly to ggplot2 aesthetics, such as the linetypes in linetypes. Some other notes:

Colors in particular may be examined using the fg_display_colors() function as in

fg_display_colors("lines")

Adding or customizing aesthetics

Any of the default aethetic sets can be customized across calls to the functions and invocations of the package using fg_update_aes() New aesthetics sets can also be added for those functions (e.g. fg_scatplot()) where different aesthetic sets can be specified at runtime.

Modifying or adding aesthetics sets is done by creating (or copying and editing) a data.frame obtained from fg_get_aes() As a simple example, suppose we have three related classes of assets, one of which we wish to highlight and the others are related, but less important. Here is how the default colors would look:

onedt <- function(offset,category) { data.table(x=seq(1,10),y=seq(1,10)-offset,id=rep(category,10))}
exampledta <- rbind(onedt(0,"A"),onedt(1,"B"),onedt(2,"C"))
fg_scatplot(exampledta,"y ~ x + color:id",title="default",psize=6)

Customizing default aesthetics

The procedure for changing those colors is as follows:

  1. Get an example data.frame using fg_get_aes()
  2. Modify the values you want to change in the value column
  3. Update the persistent package data using fg_update_aes()
head(oldcolors <- fg_get_aes("lines"),3)
oldcolors[c(1,2,3),"value"] <- alpha("blue", c(1,0.6,0.3))
# Note that we still keep "category" as "lines".  To add a new set, use a different name.
fg_update_aes( oldcolors )
fg_display_colors("lines")
fg_scatplot(exampledta,"y ~ x + color:id",title="default",psize=6)

Adding new aesthetics

To create our own aesthetics, we use the same procedure, but adding our own "category":

oldcolors[c(1,2,3),"value"] <- alpha("red", c(1,0.6,0.3))
oldcolors[c(1,2,3),"category"] <- rep("MyNewColors",3)
fg_update_aes( oldcolors )
fg_scatplot(exampledta,"y ~ x + color:id,MyNewColors",title="with new colors",psize=6)

Themes

Themes are the ggplot2 way of proscribing every single aesthetic detail in a graph. This package uses a default theme derived from theme_bw(), but it is quite easy to create or modify, and more importantly save, a custom theme for future use.

To do so, just call fg_replace_theme() as in the following example:

fg_replace_theme(theme_dark())
fg_scatplot(exampledta,"y ~ x + color:id,MyNewColors",title="New Theme, New Colors",psize=6)

Persistence

Saved Aesthetics, themes and dates of interest persist

This package manages aesthetic changes for you by caching the current aesthetic sets, themes, and dates of interest in local files, which are then loaded on package invocation. If you don't want save changes, then call fg_update_aes() and fg_replace_theme() with persist=FALSE parameters.

To reset all parameters back to the package defaults, run fg_reset_to_default_state()

fg_reset_to_default_state("all")
fg_scatplot(exampledta,"y ~ x + color:id",title="Back to old colors",psize=6)


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FinanceGraphs documentation built on June 22, 2026, 5:08 p.m.