Title:	Le-Huynh Truc-Ly's R Code and Templates
Version:	0.1.1
Author:	Truc-Ly Le-Huynh [aut, cre, cph]
Maintainer:	Truc-Ly Le-Huynh <trucly.lehuynh@gmail.com>
Description:	Miscellaneous R functions (for graphics, data import, data transformation, and general utilities) and templates (for exploratory analysis, Bayesian modeling, and crafting scientific manuscripts).
License:	MIT + file LICENSE
URL:	https://github.com/le-huynh/lehuynh, https://le-huynh.github.io/lehuynh/
BugReports:	https://github.com/le-huynh/lehuynh/issues
Encoding:	UTF-8
RoxygenNote:	7.2.3
Suggests:	testthat (≥ 3.0.0), writexl
Config/testthat/edition:	3
Imports:	brms, stats, ggplot2, usethis, ggpubr, purrr, stringr, magrittr, readxl, dplyr, fs, rio, tibble
NeedsCompilation:	no
Packaged:	2024-06-04 15:44:47 UTC; trucl
Repository:	CRAN
Date/Publication:	2024-06-05 14:50:02 UTC

Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

The result of calling rhs(lhs).

Examples

c(1, 2, 3) %>% mean()

Min-Max Standardization

Description

Normalize / Standardize / Scale the data to the fixed range from 0 to 1. The minimum value of data gets transformed into 0. The maximum value gets transformed into 1. Other values get transformed into decimals between 0 and 1.

Usage

MinMaxScaling(x, y = x)

Arguments

Details

Min-max scaling is a normalization technique that transforms the values in a vector to a standardized range. The scaling is performed using the formula:

scaled_x = \frac{x - \min(y)}{\max(y) - \min(y)}

Value

A numeric vector of the same length as x, with values scaled to the range from 0 to 1.

Examples

dat1 = seq(from = 5, to = 30, length.out = 6)

MinMaxScaling(dat1)

dat2 = c(7, 13, 22)

MinMaxScaling(x = dat2, y = dat1)

Save a plot - Elsevier figure size

Description

Save a plot using ggplot2::ggsave(). Plot size follows instructions of Elsevier journals.

Usage

ggsave_elsevier(
  filename,
  plot,
  width = c("one_column", "one_half_column", "full_page"),
  height,
  ...
)

Arguments

Details

Instruction of Elsevier about sizing of artwork.

• Image width:

  • single column: 90 mm (255 pt)

  • 1.5 column: 140 mm (397 pt)

  • double column (full width): 190 mm (539 pt)

• Image height: maximum 240 mm.

Value

An image file containing the saved plot.

See Also

ggplot2::ggsave()

Examples

library(ggplot2)

fig <- ggplot(mtcars, aes(y = mpg, x = disp)) +
    geom_point(aes(colour = factor(cyl)))

## For demo, a temp. file path is created with the file extension .png
png_file <- tempfile(fileext = ".png")

ggsave_elsevier(png_file, plot = fig, width = "full_page", height = 120)

Import multiple files of the same format

Description

This function imports multiple data files of the same format from a specified directory, optionally filtered by a pattern in the filenames.

Usage

import_data(path, file_format, pattern = NULL, ...)

Arguments

Value

A named list where each element is the imported data from a file, with names corresponding to the filenames without the path and file extension.

Examples

## For demo, temp. file paths is created with the file extension .csv
csv_file1 <- tempfile(pattern = "test", fileext = ".csv")
csv_file2 <- tempfile(pattern = "file", fileext = ".csv")
csv_file3 <- tempfile(pattern = "test", fileext = ".csv")

## create CSV files to import
write.csv(head(cars), csv_file1)
write.csv(head(mtcars), csv_file2)
write.csv(head(iris), csv_file3)

## Import all CSV files in the directory
data_list <- import_data(path = tempdir(), file_format = "*.csv")

## Import all CSV files with names containing "test"
data_list <- import_data(path = tempdir(), file_format = "*.csv", pattern = "test")

Import Excel file with multiple sheets

Description

This function imports an Excel file with multiple sheets and returns a named list of imported sheets.

Usage

import_excel(file_path)

Arguments

Value

A named list where each element is the imported sheet from the Excel file, with names corresponding to the sheet names.

Examples

## For demo, a temp. file path is created with the file extension .xlsx
excel_file <- tempfile(fileext = ".xlsx")

## create Excel file with multiple sheets to import
writexl::write_xlsx(list(cars = head(cars), mtcars = head(mtcars)),
                    excel_file)

import_excel(file_path = excel_file)

Le-Huynh's ggplot2 theme

Description

Le-Huynh's ggplot2 theme: white background, black axis, black text

Usage

lehuynh_theme(base_size = 11, base_family = "", ...)

Arguments

Value

An object as returned by ggplot2::theme()

See Also

ggplot2::theme(), ggplot2::theme_bw()

Examples

library(ggplot2)

fig <- ggplot(mtcars, aes(y = mpg, x = disp)) +
    geom_point(aes(colour = factor(cyl)))

fig

fig + lehuynh_theme()

Create a new project

Description

This function sets up a new project within an active R project for reproducible purposes.

Usage

new_project()

Details

The project includes:

• README.md: the top level description of content in the project

• Makefile

• different folders to hold all data, code, results of data analysis, and documents related to the project

• templates: manuscript.Rmd, code.R, etc.

Value

A project containing folders and files for reproducible purposes.

Note

The function should be executed within an active project.

Recommended workflow:

1. Create a GitHub repository for the new project. At Initialize this repository with a README, choose NO.

2. Create a new RStudio Project via ⁠git clone⁠.

3. Use function new_project() to generate folders and file templates.

References

Reproducibile Research Tutorial Series by Pat Schloss.

Examples

if(interactive()){
  new_project()
}

Fitted versus observed plot for brmsfit Objects

Description

Plot fitted versus observed values, including confidence interval (gray area) around best fit line (linear regression line) and prediction interval (dashed line).

Usage

ppc_brms(
  object,
  xtitle = "Observed value",
  ytitle = "Fitted value",
  dy = c(0.1, 0.1),
  dx = c(0.1, 0.1),
  cor = FALSE,
  equation = FALSE,
  xcor = NULL,
  ycor = NULL,
  xequ = NULL,
  yequ = NULL,
  ...
)

Arguments

Value

A ggplot object

Examples

## Not run: 

library(brms)

mod <- brm(count ~ zAge + zBase * Trt + (1|patient) + (1|obs),
           data = epilepsy,
           family = poisson())

ppc_brms(mod)
ppc_brms(mod, dy = c(0.02, 0.1), dx = c(0.005, 0.1))
ppc_brms(mod, cor = TRUE, equation = TRUE, yequ = 100)

## End(Not run)

Create a new folder for #tidytuesday challenge

Description

This function sets up a new folder for #tidytuesday challenge within an active project. It creates a directory for the specified year and week, along with sub-directories for data, code, and plots. Template files are also added.

Usage

tidytuesday(year, week)

Arguments

Details

The folder includes:

• README.md: plots for #tidytuesday challenge

• different folders to hold all data, code, plots of data analysis

• templates

Value

A folder containing folders and files for #tidytuesday challenge.

Note

Ensure that this function is called within an active project.

Examples

if(interactive()){
  tidytuesday(year = 2021, week = 25)
}

Calculate TSI (Trophic state index)

Description

Calculate TSI. TSI range: 0 - 100.

Usage

tsi(x, type = c("chla", "TP", "TN", "SD"))

Arguments

Details

Trophic state classification (Carlson, 1996)

• <30-40, Oligotrophy

• 40-50, mesotrophy

• 50-70, eutrophy

• 70-100, hypereutrophy

Type of variable used to calculate TSI:

• SD: Secchi depth, meter

• chla: chlorophyll, ug/L or mg/m3

• TP: total Phosphorus, ug/L or mg/m3

• TN: total Nitrogen, mg/L

Carlson (1977): TSI-SD, TSI-Chla, TSI-TP

USEPA (2000): TSI-TN

Value

a numeric value.

References

Carlson, R. E. (1977). A trophic state index for lakes. Limnology and Oceanography, 22(2), 361-369.

Carlson, R. E., & Simpson, J. (1996). A Coordinator's Guide to Volunteer Lake Monitoring Methods. North American Lake Management Society, 73-92.

USEPA. (2000). Nutrient Criteria Technical Guidance Manual: Lakes and Reservoirs, 42-44.

Examples

chla <- c(0.12, 0.34, 0.94, 6.4)

tsi(chla, type = "chla")

tsi(chla, type = "TP")