---
title: Testing the VI.ggplot() within the BrailleR package"
author: "A. Jonathan R. Godfrey"
bibliography: BrailleRPublications.bib
vignette: >
  %\VignetteIndexEntry{qplot}
  %\VignetteEngine{knitr::rmarkdown}
output: knitr:::html_vignette
---


This vignette  contained many more plots in its initial development. The set has been cut back considerably to offer meaningful testing only, and because much of the material was moved over to a book called [BrailleR in Action](https://R-Resources.massey.ac.nz/BrailleRInAction/). Doing so also had an advantage of speeding up the package creation, testing, and installation.
N.B.  the commands here are either exact copies of the commands presented in Wickham (2009) or some minor alterations to them.    Notably, some code given in the book no longer works. This is given a `#!`    


The `ggplot2` package has  a `summary` method that often but not always offers something to show that things have changed from one plot to another. Summary 
commands are included below but commented out.

```{r GetLibraries}     
library(BrailleR)   
library(ggplot2)   
dsmall = diamonds[1:100,]   
```  

```{r g1}     
g1 = qplot(carat, price, data = diamonds)   
# summary(g1)   
g1  
# VI(g1)   ### automatic since BrailleR v0.32.0
```  


If the user does not actually plot the graph, they can still find out what it will look like once it is plotted by using the `VI()` command on the graph object. This became unnecessary from version 0.32.0 of BrailleR.

N.B. All `VI()` commands can now be deleted from this document.

```{r g2}          
g2 = qplot(carat, price, data = dsmall, colour = color)    
# summary(g2)   
g2
```  



```{r g3}     
g3 = qplot(carat, price, data = dsmall, shape = cut)    
# summary(g3)   
g3
```  

```{r g4}     
# to get semi-transparent points   
g4 = qplot(carat, price, data = diamonds, alpha = I(1/100))    
# summary(g4)   
g4
```  

```{r g5}     
# to add a smoother (default is loess for n<1000)   
g5 = qplot(carat, price, data = dsmall, geom = c("point", "smooth"))    
# summary(g5)   
g5
#! g5a = qplot(carat, price, data = dsmall, geom = c("point", "smooth"), span = 1)    
library(splines)    
#! g5b = qplot(carat, price, data = dsmall, geom = c("point", "smooth"), method = "lm")    
#! g5c = qplot(carat, price, data = dsmall, geom = c("point", "smooth"), method = "lm", formula = y ~ ns(x,5))    
```  

```{r g6, include=FALSE}     
# continuous v categorical   
g6 = qplot(color, price / carat, data = diamonds, geom = "jitter", alpha = I(1 / 50))    
# summary(g6)   
g6
# VI(g6)     ### automatic since BrailleR v0.32.0
g6a = qplot(color, price / carat, data = diamonds, geom = "boxplot")    
# summary(g6a)   
g6a
```  

```{r g7}     
# univariate plots   
g7a = qplot(carat, data = diamonds, geom = "histogram")    
# summary(g7a)   
g7a
g7b = qplot(carat, data = diamonds, geom = "histogram", binwidth = 1, xlim = c(0,3))    
g7b
g7c = qplot(carat, data = diamonds, geom = "histogram", binwidth = 0.1, xlim = c(0,3))
g7c
g7d = qplot(carat, data = diamonds, geom = "histogram", binwidth = 0.01, xlim = c(0,3))    
# summary(g7d)   
g7d
```  

```{r g8, include=FALSE}
g8 = qplot(carat, data = diamonds, geom = "density")    
# summary(g8)   
g8
```  

```{r g9, include=FALSE}     
# data is separated by implication using the following...   
g9 = qplot(carat, data = diamonds, geom = "density", colour = color)    
# summary(g9)   
g9
g10 = qplot(carat, data = diamonds, geom = "histogram", fill = color)    
# summary(g10)   
g10
```  

```{r g11}     
# bar charts for categorical variable   
g11a = qplot(color, data = diamonds)    
# summary(g11a)   
g11a
g11b = qplot(color, data = diamonds, geom = "bar")    
# summary(g11b)   
g11b
g12a = qplot(color, data = diamonds, geom = "bar", weight = carat)   
# summary(g12a)   
g12a
g12b = qplot(color, data = diamonds, geom = "bar", weight = carat) + scale_y_continuous("carat")    
# summary(g12b)   
g12b
```  

```{r g13}     
# time series plots   
g13a = qplot(date, unemploy / pop, data = economics, geom = "line")    
# summary(g13a)   
g13a
g13b = qplot(date, uempmed, data = economics, geom = "line")    
# summary(g13b)   
g13b
```  

```{r g14, include=FALSE}     
# path plots   
year <- function(x) as.POSIXlt(x)$year + 1900    
g14a = qplot(unemploy / pop, uempmed, data = economics, geom = c("point", "path"))    
# summary(g14a)   
g14a
#g14b = qplot(unemploy / pop, uempmed, data = economics, geom = "path", colour = year(date)) + scale_area()    
#summary(g14b)   
```  

```{r g15, include=FALSE}     
# facets is the ggplot term for trellis' panels   
g15a = qplot(carat, data = diamonds, facets = color ~ ., geom = "histogram", binwidth = 0.1, xlim = c(0, 3))    
# summary(g15a)   
g15a
g15b = qplot(carat, ..density.., data = diamonds, facets = color ~ ., geom = "histogram", binwidth = 0.1, xlim = c(0, 3))   
# summary(g15b)   
g15b
```  

```{r g16}     
# rescaling of the axes   
g16 = qplot(carat, price, data = dsmall, log = "xy")   
# summary(g16)   
g16
```  

```{r g17, include=FALSE}     
# Facets syntax without a "." before the "~" causes grief
g17 = qplot(displ, hwy, data=mpg, facets =~ year) + geom_smooth()    
# summary(g17)   
g17
```  
