---
title: "Convert CBMs to Standard"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Convert CBMs to Standard}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

The CHOIR Body Map does not use the same numbering scheme for male and female
body maps (as of August 2021). 

<!--![Incorrectly labeled bodymaps](img/mislabeled-bodymaps.png)-->
```{r load_img}
# mislabeled_cbm_img <- function() {
#   # magick::image_read(system.file("img/mislabeled-bodymaps.png", "CHOIRBM"))
#   filename <- "img/mislabeled-bodymaps.png"
#   system.file(filename, package = "CHOIRBM", lib.loc = .libPaths()[1])
# }
# knitr::include_graphics("inst/img/mislabeled-bodymaps.png")
```

Therefore, for mixed gender analysis (such as 
examining differences in segment endorsements between men and women), it is 
necessary to convert maps to the same standard. This vignette demonstrates how
to re-number the female body map to the male numbering scheme.

```{r setup}
library(CHOIRBM)
```

```{r example}
## basic example code
# generate example data <- don't do this if you have data already, load it 
# into R with read.csv, read.delim, etc.
GENDER = as.character(c("Male", "Female", "Female"))
BODYMAP_CSV = as.character(c("112,125","112,113","128,117"))
cbind(GENDER, BODYMAP_CSV)

# convert the female bodymaps to a standard
BODYMAP_CSV[GENDER == "Female"] <- convert_bodymaps(
  BODYMAP_CSV[GENDER == "Female"]
  )
sampledata <- data.frame(GENDER, BODYMAP_CSV)
sampledata
```

To save your fixed data, run:
```{r example2, eval=FALSE}
write.csv(sampledata, "filepath/filename.csv")
```