Nothing
test_file
In normfluodbf: Cleans and Normalizes FLUOstar DBF and DAT Files from 'Liposome' Flux Assays
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
("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.
# 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")
# 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")
# 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")
# 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")
#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")
#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")
#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")
#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.
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normfluodbf documentation built on Sept. 28, 2024, 1:06 a.m.
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knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
("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.
# 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")
# 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")
# 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")
# 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")
#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")
#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")
#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")
#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.
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