---
title: "test_file"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{test_file}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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

```{r echo=FALSE, results="hide", message=FALSE}
("badger")
```

# 🎬 Introduction

-   To arrive at massive documentation like this for all seven functions, Microsoft Word was leveraged.
- Some hard-work is put into making a template for the first function.
-   The idea is to take one template and replace the function name with the MS word replace function.
-   This helps create massive documentation for testing functions.
-   All case scenarios pass and the pride factor here is these functions should yield correct column names thanks to a function called actual_cols_used().

# 🕵️ Normfluodat- MVP (Minimum Viable Product)

`r badger::badge_custom("normfluodat", "MVP", "green", "https://github.com/AlphaPrime7")`

- This function is considered the MVP. 
- This is a robust and trusted function and Users should use it.

```{r normfluodat, eval=F}
# Normal cases dat(1-4)
fpath <- system.file("extdata", "dat_2.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40, rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40, rows_used = c('A','B','C'), interval = 30)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40, rows_used = c('A','B','C'), interval = 60)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')

# Extreme cases dat(5-7)
fpath <- system.file("extdata", "dat_5.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A'), cols_used = c(1))
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A'), cols_used = c(1,2))

normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')
```

# 🕵️ Normfluodatlite

`r badger::badge_custom("normfluodatlite", "COOL", "green", "https://github.com/AlphaPrime7")`

```{r normfluodatlite, eval=F}
# Normal cases dat(1-4)
fpath <- system.file("extdata", "dat_1.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'hundred')
normalized_fluo_dat <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one')
normalized_fluo_dat <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40)
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')

# Extreme cases dat(5-7)
fpath <- system.file("extdata", "dat_5.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40)
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))

normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatlite(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')
```

# 🕵️ Normfluodatfull

`r badger::badge_custom("normfluodatfull", "WEIRD", "green", "https://github.com/AlphaPrime7")`

```{r normfluodatfull, eval=F}
# Normal cases dat(1-4)
fpath <- system.file("extdata", "dat_3.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'hundred')
normalized_fluo_dat <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one')
normalized_fluo_dat <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40)
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')

# Extreme cases dat(5-7)
fpath <- system.file("extdata", "dat_6.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal', norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'hundred')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'one')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'z-score')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'decimal')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), norm_scale = 'raw')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40)
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluodatfull(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')

```

# 🕵️ Normfluordat

`r badger::badge_custom("normfluordat", "BRUTEFORCE", "green", "https://github.com/AlphaPrime7")`


```{r normfluordat, eval=F}
# Normal cases dat(1-4)
fpath <- system.file("extdata", "dat_3.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40)
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')

# Extreme cases dat(5-7)
fpath <- system.file("extdata", "dat_5.dat", package = "normfluodbf", mustWork = TRUE)
normalized_fluo_dat <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), read_direction = 'horizontal')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40)
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3))
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'vertical')
normalized_fluo_dat_advv <- normfluordat(dat=fpath, tnp = 1, cycles = 40,rows_used = c('A','B','C'), cols_used = c(1,2,3), read_direction = 'horizontal')
```


# 🕵️ Normfluordbf

`r badger::badge_custom("normfluordbf", "DBF-MVP", "blue", "https://github.com/AlphaPrime7")`

```{r normfluordbf, eval=F}
#normfluordbf
fpath <- system.file("extdata", "liposomes_214.dbf", package = "normfluodbf", mustWork = TRUE)
norm_dbf <- normfluordbf(fpath, norm_scale = 'raw')
norm_dbf <- normfluordbf(fpath, norm_scale = 'decimal')
norm_dbf <- normfluordbf(fpath, norm_scale = 'one')
norm_dbf <- normfluordbf(fpath, norm_scale = 'hundred')
norm_dbf <- normfluordbf(fpath, norm_scale = 'z-score')
```

# 🕵️ Norm_tidy_dbf

`r badger::badge_custom("norm_tidy_dbf", "GRANDFATHERED", "blue", "https://github.com/AlphaPrime7")`

```{r norm_tidy_dbf, eval=F}
#norm_tidy_dbf
fpath <- system.file("extdata", "liposomes_214.dbf", package = "normfluodbf", mustWork = TRUE)
norm_dbf <- norm_tidy_dbf(fpath, norm_scale = 'raw')
norm_dbf <- norm_tidy_dbf(fpath, norm_scale = 'decimal')
norm_dbf <- norm_tidy_dbf(fpath, norm_scale = 'one')
norm_dbf <- norm_tidy_dbf(fpath, norm_scale = 'hundred')
norm_dbf <- norm_tidy_dbf(fpath, norm_scale = 'z-score')
```


# 🕵️ Time Attribute

`r badger::badge_custom("time_attribute", "Final-feature", "blue", "https://github.com/AlphaPrime7")`

```{r time_attribute, eval=F}
#Time attribute
#214
time_original = time_attribute(30,8,136,1276,40)
norm_dbf = cbind(time_original,norm_dbf)
#221
time_original = time_attribute(33,8,907,2161,40)
norm_dbf = cbind(time_original,norm_dbf)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one', interval = 30, first_end = 8, pause_duration = 136, end_time = 1276)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one', interval = 33, first_end = 8, pause_duration = 0, end_time = 2161)
normalized_fluo_dat_advv <- normfluodat(dat=fpath, tnp = 3, cycles = 40,rows_used = c('A','B','C'), read_direction = 'vertical', norm_scale = 'one', interval = 33)
for (i in 1:nrow(normalized_fluo_dat_advv)) {
  for(j in 1:ncol(normalized_fluo_dat_advv))
    if(j == 1){
      normalized_fluo_dat_advv[i,j] = normalized_fluo_dat_advv[i,j] + 30
    }
}
```

# 🕵️ Visualize

`r badger::badge_custom("ggplot_tnp", "knock-knock", "brown", "https://github.com/AlphaPrime7")`

```{r ggplot_tnp, eval=F}
#Visualize

#DAT
#z-score
ggplot_tnp(normalized_fluo_dat, c('Cycle_Number'), c('A1','B1','C1'),c(0,40),c(-1,3))

#hundred
ggplot_tnp(normalized_fluo_dat, c('Cycle_Number'), c('A1','B1','C1'),c(0,40),c(0,100))

#one
ggplot_tnp(normalized_fluo_dat, c('Cycle_Number'), c('A1','B1','C1'),c(0,40),c(0,1))

#raw & decimal (sliding scale)
ggplot_tnp(normalized_fluo_dat, c('Cycle_Number'), c('A1','B1','C1'),c(0,40),ylim = NULL)

#DBF
ggplot_tnp(norm_dbf, c('Cycle_Number'), c('A01','B01','C01'),c(0,40),ylim = NULL)
ggplot_tnp(norm_dbf, c('Time'), c('A01','B01','C01'),xlim = NULL, ylim = NULL)
```


# 🕵 Final Remarks

-   The MVP here is normfluodat and users should always use this function.
-   normfluodat will also provide the user with the option of seeing the raw file with raw fluorescence values. This also helps detect data corruption issues.
-   All the functions have been tested and passed almost every scenario.
-   This vignette is educative and indicates how testing can be done for large packages like this one.
-   Prompted by some failures after the update release, I got to work and noticed that this was the only way I could have a package I was proud of and that users could have the best experience.
-   There is room to find ways for automating this process but I am NOT working on that.
