exec/messycode.R

In Rclean: A Tool for Writing Cleaner, more Transparent Code

### Messy code is a fabricated example
### intended to capture the essentials
### of a typical, lazy scripter's R code.
### It is, however, tremendously more 
### organized than the vast majority of
### scripts.

### Depedencies are loaded throughout the script.
### Also, some depencies that are loaded are often 
### not used anymore but are still present.
library('gdata')
source("sourced.R")

### User defined functions
myfunc <- function(x){
    cos(x) * pi
}

### Read data from some random file path
### Here, a relative path is being used, but
### typically, file paths are given from root.
data.16 <- read.csv("../example/data/projects/2016/july_biomass_survey.csv")

### Some datasets are loaded and no longer used.
### Like this one
data.16.2 <- read.csv('../example/data/projects/data_forestplot/dataset_v2_june_from_collaborator1.csv')

### Create a bunch of intermediate objects
data.v1.1to4 <- data.16[,1:4]
data.v1.1to4. <- data.v1.1to4
data.v1.1to4 <- data.v1.1to4 * 2
data.v1.1to4.2 <- data.v1.1to4 * 2
data.16[,1:4] <- data.v1.1to4.2

### Very rarely, R scripts will have control
### statements
if (any(is.na(data.16.2))){
    data.16.2[is.na(data.16.2)] <- 0
}# specifying the else is not required


### Conduct some analyses
library('vegan')
d1 <- vegdist(data.16[,1:2])
d2 <- vegdist(data.16[,2:3])
mant1 <- mantel(d1,d2)
mant2 <- mantel(d2,d1)
mant11 <- mantel(d1,d1)
fit1 <- lm(Sepal.Length~Sepal.Width,data=data.16)
lm.summary.1 <- summary(fit1)
anova.summary <- anova(fit1)
out.summary <- as.data.frame(anova.summary)


### for loops are also uncommon
for (i in 1:ncol(data.v1.1to4)){
    colnames(data.v1.1to4)[i] <- paste0("var", i)
}

### write some data to file
write.csv(data.v1.1to4,'../example/data/projects/data_forestplot/save1.csv',row.names = F)


### write lm and anova output to file
capture.output(lm.summary.1, file="../example/data/projects/lm_table_1.txt")
write.csv(out.summary, file="../example/data/projects/table_2.csv")

### use the defined function
val <- myfunc(exp(1))

### write some figures to file
### Here's another random, unused package
library('txtplot')

png('../example/projects/fig1_biplot.png')
plot(data.16[,1:2])
dev.off()

png('../example/projects/fig1_biplot_t2.png')
plot(data.16[,1:2]*2)
dev.off()

png('../example/projects/fig2_biplot.png')
plot(data.16[,2:3])
dev.off()