Package 'inSilecoMisc'

Adjust the size of character strings

Description

Adjust the size of character strings by adding extra characters. It allows to constraint the size of the string or to add a specific number of extra characters.

Usage

adjustStrings(
  x,
  n,
  extra = 0,
  align = c("right", "left", "center"),
  add = FALSE
)

Arguments

x	a character vector, or a vector to be coerced to a character vector.
n	a positive integer indicating the size of character strings to be created or added.
extra	a character vector, or a vector to be coerced to a character vector that will be (partially) added to produced a string of a specific length.
align	either "right", "left" or "center". If "right", then strings will be right-aligned and so extra's characters will be added to the left. "right" is the opposite of "left" and if align = "center", then extra characters will be split in half and added on both sides.
add	a logical should extra be added, in which case n characters will be added to input strings.

Details

This function was originally created to help getting a fixed number of digits when naming files. The current version is more general, it allows to add any string before or after to adjust the size. Not that if a character is longer than expected, it will be adequately cut off.

Value

A character vector of the concatenated characters.

See Also

base::sprintf()

Examples

paste0('myfilename', adjustStrings(c(1:2,10,100), 3))
adjustStrings('# Comment ', 20, '#', align = "left")

---

Aggregate columns

Description

aggregateCol() performs summary statistics on a specific subset of columns.

Usage

aggregateCol(data, grp, names_aggreg = NULL, FUN = sum, ...)

Arguments

data	a data frame.
grp	an integer vector, one value per data column. Integers are used to group data columns, column with the same integer will be pooled together. Any integer is a valid group, 0 indicates that the column must be unchanged, NA removes columns.
names_aggreg	column names for aggregated columns.
FUN	a function to be applied to all groups of columns.
...	further arguments to be passed to FUN.

Details

grp is an integer vector, whose length is the number of columns of the input data frame, is used to assign a group to each column that explicit the sub-setting. Furthermore columns can be either kept as is using 0 or discarded using NA.

Value

A data frame with the grouped columns.

See Also

stats::aggregate() base::split

Examples

mat1 <- matrix(1:70,10)
grp1 <- c(NA,0, 1, 1, 2, 2, 2)
aggregateCol(mat1, grp1, FUN = mean)

---

Apply a function on character strings

Description

Apply a function on a given set of elements of a character string.

Usage

applyString(x, FUN, pos = NULL, pattern = NULL)

Arguments

x	a character vector, or a vector to be coerced to a character vector.
FUN	the function to be applied, see base::lapply().
pos	a vector indicating the elements position.
pattern	a pattern see base::gregexpr().

Value

A character vector.

Note

In case both pos or pattern, the latter is ignored.

Examples

applyString('cool',  pos = 1:2, FUN = toupper)
applyString(c('cool', 'pro'),  pattern = 'o', FUN = toupper)

---

Assign a class to columns

Description

Assign a class to a set of column of a data frame. This function is designed to ease the changes of column's class of a given data frame.

Usage

assignClass2df(x, colid, cls)

Arguments

x	a data frame or a R object to be coerced into a data frame.
colid	the identity of columns for which class are ti be changed.
cls	a character vector containing the classes' names to be used in the same order as colid. By default cls is repeated until its size equals colid's size.

Value

A data frame for which columns have the required classes.

Examples

df1 <- matrix(signif(runif(20),4), ncol=2)
df2 <- assignClass2df(df1, 2, 'character')
str(df1)
str(df2)

---

Assign an id to a list of characters or factors

Description

This function aims to assign an id to factor or similar character strings. Regarding factors, as.integer() does such task but the order obtained may differ.

Usage

assignIds(x, alphabetical = FALSE)

Arguments

x	an R object to be coerced into character type.
alphabetical	a logical indicating whether an alphabetical sorting must be applied.

Value

A vector of Ids.

Examples

assignIds(list(2,'f', 'd', 'f'))

---

Assign categories

Description

Assigns a category to each element of a vector for a given set of threshold values.

Usage

categorize(x, categ, lower = FALSE)

Arguments

x	a numeric, complex, character or logical vector.
categ	a set of threshold values used to assign categories.
lower	a logical. If TRUE threshold values (i.e. values within categ) belongs to the lower category rather than the upper (default behavior).

Value

A vector of categories assigned.

Examples

categorize(stats::runif(40), categ=c(0.5,0.75))
categorize(LETTERS[1:5], categ='C')
categorize(LETTERS[1:5], categ='C',  lower=TRUE)
categorize(LETTERS[floor(5*stats::runif(20))+1], categ=LETTERS[1:5], lower=TRUE)

---

Paste element and add elememt separators.

Description

Paste element and add elememt separators.

Usage

commaAnd(x, comma = ", ", and = " and ")

Arguments

x	vector of to be coerced to character strings (see paste()).
comma	element separator.
and	last element separator (for 3 elements in x and more).

Examples

commaAnd(c("Judith", "Peter", "Rebecca"))

---

Create a data frame from scratch or based on one or two data frames

Description

This function handles the creation of data frames based on intuitive parameters. It was originally designed to make row binding easier when columns differs among data frame by creating data frames with the same columns.

Usage

dfTemplate(cols, nrows = 1, col_classes = NULL, fill = NA)

dfTemplateMatch(x, y, yonly = FALSE, order = FALSE, ...)

Arguments

cols	either a number of column or a vector of character used as columns names of the data frame to be returned.
nrows	row number.
col_classes	vector of column classes for the desired data frame. By default, the class is determined by fill.
fill	character or number used to fill out the columns. Default is NA.
x	a data frame.
y	a data frame or a vector of strings use to specifies column names to be included in the data frame.
yonly	a logical. Should only y (or the names(y)) be used for the data frame to be returned? Default is set to FALSE meaning that both the names of x and the names of y are used.
order	a logical. Should column of the output data frame be ordered according to the template. Not that if there are more columns in x that are not in y, then if order = TRUE column of y will be added first (on the left of the output data frame).
...	further arguments to be passed to dfTemplate().

Value

Returns a data frame with the desired characteristics.

Functions

• dfTemplateMatch(): Returns a data frame that includes all columns specifies in y.

References

https://insileco.github.io/2019/02/03/creating-empty-data-frames-with-dftemplate-and-dftemplatematch/

Examples

dfTemplate(5, 2)
dfTemplate(5, 2, col_classes = "character")
dfA <- data.frame(col1 = c(1, 2), col2 = LETTERS[1:2])
dfB <- data.frame(col4 = c(1, 2), col2 = LETTERS[1:2])
dfTemplateMatch(dfA, c("col4", "col2"))
dfTemplateMatch(dfA, c("col4", "col2"), yonly = TRUE)
dfTemplateMatch(dfA, dfB, yonly = TRUE, order = TRUE)

---

Duplicates elements of a data frame

Description

Duplicates rows and columns of a given a data frame.

Usage

duplicateRow(x, id.el = 1, times = 1, append = FALSE)

duplicateCol(x, id.el = 1, times = 1, append = FALSE)

Arguments

x	a data frame.
id.el	identity of the elements to be duplicated.
times	number of times elements are duplicated. Could be a vector of the same length as id.el.
append	A logical. If TRUE, duplicated elements will be appended to the data frame otherwise duplicated elements remain next to their parent. Non-existing columns cannot be duplicated while non-existing rows can and produce NA.

Value

returns a data frame with duplicated rows.

Functions

• duplicateCol(): returns a data frame with duplicated columns.

Examples

data(iris, package = "datasets")
iris2 <- duplicateRow(iris, id.el = 1:50, times = 2)
iris3 <- duplicateCol(
iris,
id.el = c("Petal.Length", "Petal.Width"),
times = c(1, 2),
append = TRUE)

---

Find values in a given vector

Description

Given a set of values and a vector where the values must be found, findThem records the matched values and the position in the vector where the values have been searched for.

Usage

findThem(what, where, todf = FALSE, reportnomatch = FALSE)

Arguments

what	a vector a values to be searched for.
where	a vector where values will be searched on.
todf	a logical. Should the output object must be a data frame?
reportnomatch	a logical. If TRUE, values without match are reported #' in the data frame with a NA. Only available if todf is TRUE (default is FALSE).

Value

A list indicating matched positions for each elements of what. If no match is found then NA is returned. If todf is TRUE then a three-columns data frame is returned including values and positions in both what and where vectors.

See Also

which()

Examples

x <- stats::rpois(1000,10)
findThem(c(10,4,100), x)
findThem(c(10,4,100), x, todf=TRUE)
findThem(c(10,4,100), x, todf=TRUE, reportnomatch=TRUE)

---

Flexible bell-shaped function

Description

The gaussianShape() function computes a personnalisable Gaussian function. Default values are the same as in stats::dnorm().

Usage

gaussianShape(x, optx = 0, opty = 1/sqrt(2 * pi), width = 1, pow = 2)

Arguments

x	a numeric vector.
optx	x-values at which the maximum is reached.
opty	extremum value.
width	width of the bell.
pow	a real number.

Value

A vector containing values standing for categories into which elements of x have fallen.

See Also

stats::dnorm()

Examples

gaussianShape(0)
plot(gaussianShape(1:1000, 500, 2, 250, pow=5), type='l')

---

Extract digits from a character vector

Description

This function extracts all digits found in character vector and returns them as a list.

Usage

getDigits(x, collapse = NULL)

Arguments

x	a character vector where digits are sought, or an object which can be coerced by as.character to a character vector.
collapse	an optional character string to separate the results (see [base::paste()).

Value

A list of digits.

Examples

getDigits('txt012-34')

---

Extract file name, extension and basename ofrom a path.é

Description

Extract file name, extension and basename ofrom a path.é

Usage

getExtension(x, sep = .Platform$file.sep)

getFilename(x, sep = .Platform$file.sep)

getName(x, sep = .Platform$file.sep)

getBasename(x, sep = .Platform$file.sep)

getLocation(x, sep = .Platform$file.sep)

getDetails(x, sep = .Platform$file.sep)

Arguments

x	a character string. Note that getDetails() also supports vector of paths.
sep	file separator, default used the platform-specific file separator see .Platform().

Details

For more functionalities, have a look at package fs.

Value

Extract the file extension a character string (e.g. a path).

Functions

• getFilename(): Extract the file name from a character string, that is the base name and the file extension

• getName(): Extract the name of a file or a directory from a character string.

• getBasename(): Extract the base name of a file from a character string.

• getLocation(): Extract the location of the parent folfder from a character string.

• getDetails(): Return a data frame with basic information for all elements of a vector of paths.

Examples

getExtension("path1/path2/foo.R")
getFilename("path1/path2/foo.R")
getBasename("path1/path2/foo.R")
getLocation("path1/path2/foo.R")
getDetails("path1/path2/foo.R")
getDetails(list.files(recursive = TRUE)) 
getExtension("foo.R")
getBasename("foo.R")

---

Keep a selection of words or letters

Description

Select words or letters based on their position in character strings.

Usage

keepWords(
  str,
  slc = 1,
  collapse = " ",
  na.rm = FALSE,
  split_words = "[[:punct:][:space:]]+"
)

keepLetters(
  str,
  slc = 1,
  collapse = "",
  na.rm = FALSE,
  rm_punct = "[[:punct:][:space:]]+"
)

keepInitials(str, split_words = "[\n\t\r\f\b[:punct:] ]+", collapse = "")

wordCount(str, split_words = "[[:punct:][:space:]]+")

Arguments

str	an input character vector (or a list) from which words will be extracted.
slc	a vector of integer indicating the selected positions of the words (or letters) to be kept.
collapse	character string used to separate selected words (or letters), if NULL, then selection is not collapsed and a list is returned.
na.rm	a logical. Should missing values be removed?
split_words	a character string containing a regular expression used to split words.
rm_punct	a character string containing a regular expression used to remove punctuation characters.

Value

A vector (or a list) of the selected words.

Functions

• keepLetters(): A vector (or a list) of the selected letters.

• keepInitials(): A vector (or a list) of initials.

• wordCount(): A vector of the number of words for every character strings passed as an input.

See Also

strsplit()

Examples

keepWords(loremIpsum(), 1:3)
keepWords(c(loremIpsum(),'Another character string!'), slc = c(1,4))
keepWords(c(loremIpsum(),'A second character string.'), slc = c(1,4),
 na.rm = TRUE, collapse = '/')
strex <- c('Lorem ipsum', 'dolor sit', ' amet;')
keepLetters(strex, c(1,4))
keepLetters(strex, c(1,4), collapse = "")
keepInitials("National Basketball Association")
wordCount(c("two words!", "... and three words"))
wordCount(loremIpsum())

---

Logistic functions

Description

The logisic function describe the classical logistic function,

Usage

logistic(x, yneg = -1, ypos = 1, lambda = 1, pow = 1)

logistic2(x, yneg = -1, ypos = 1, lambda = 1, pow = 1, yzer = 0)

Arguments

x	a numerical vector.
yneg	asymptotic values when x tends to -Inf.
ypos	asymptotic values when y tends to -Inf.
lambda	scalar coefficient.
pow	x exponent.
yzer	values (for logistic2 only).

Details

The classic logistic equation is:

$f(x) = \frac{ypos-yneg}{1+e^{-\lambda x^{pow}}}$

A slightly different version is:

$f(x) = yneg + \frac{1}{\frac{1}{ypos-yneg}+(\frac{1}{yzer-yneg}-\frac{1}{ypos-yneg})e^{-\lambda x^{pow}}}$

Value

A numeric vector.

Functions

• logistic2(): A slightly different logistic function.

Source

https://en.wikipedia.org/wiki/Logistic_functionwikipedia.org/wiki/Logistic_function

---

Lorem ipsum.

Description

Returns a common form of the Lorem ipsum text an optionally a subset of it.

Usage

loremIpsum(n = NULL)

Arguments

n	the number of words to be kept.

Value

A character string with the desired piece of lorem ipsum.

References

https://en.wikipedia.org/wiki/Lorem_ipsum

Examples

loremIpsum(5)

---

Compute the mean along a vector

Description

This function is a simple moving window function.

Usage

meanAlong(vec, n)

Arguments

vec	a vector of numeric.
n	an integer indicating the size of the window.

Examples

meanAlong(1:10, 2)

---

Pre-formatted message functions

Description

Convenient wrappers around message() to sent styled notices to the user while a function/script is being executed.

Usage

msgInfo(..., appendLF = TRUE)

msgError(..., appendLF = TRUE)

msgSuccess(..., appendLF = TRUE)

msgWarning(..., appendLF = TRUE)

Arguments

...	text to be passed to paste().
appendLF	a logical. Should messages given as a character string have a new line appended ?

Value

Reports an info.

Functions

• msgError(): Reports an Error.

• msgSuccess(): Reports a success.

• msgWarning(): Reports a warning.

Note

All of these functions call message(), so for any function FUN() using #' them, suppressMessages(FUN()) is sufficient to mute all messages.

See Also

cli::symbol() message()

Examples

msgInfo("computing")
msgSuccess("done")
msgError("you got it wrong")
msgWarning("be careful")

---

Multiple match

Description

Seek all elements matching a given pattern in a character strings.

Usage

multiMatch(text, pattern)

Arguments

text	a character vector where matches are sought, or an object which can be coerced by as.character to a character vector, see regexec.
pattern	character string containing a regular expression to be matched in the given character vector, see regexec.

Details

multiMatch is essentially a wrapper around base::regexec() and base::regmatches() to find more than one match.

Value

A vector of character strings matching pattern argument.

Examples

multiMatch(loremIpsum(), " [[:alnum:]]{3} ")

---

Get a data frame of package and their installed version.

Description

Get a data frame of package and their installed version.

Usage

packagesUsed(vc_pkg)

Arguments

vc_pkg

a vector of string characters including package names to be added.

Value

A data frame of two columns. First is the name of the package; second the version installed.

Examples

packagesUsed(c('utils', 'methods'))

---

Reads YAML headers

Description

Reads YAML headers (typically found in Markdown files).

Usage

readYamlHeader(con)

Arguments

con	connection object or a character string.

Value

A named list, see yaml::yaml.load() for more details.

---

Rename object

Description

This function finds old names and replace them with new ones.

Usage

rename(x, old, new)

Arguments

x	an object from which names can be extracted see names().
old	a vector of character strings of old names.
new	a vector of character strings of new names.

Examples

tb <- data.frame(var1 = 2, var2 = "B")
rename(tb, "var1", "uptake")
rename(tb, c("var1", "var2"), c("uptake", "type"))

---

Scale a set of values

Description

This function maps a set of values to a range of integers (from 1 to a positive integer passed as an argument).

Usage

scaleWithin(x, n = 100, mn = min(x), mx = max(x))

Arguments

x	a numeric object of type numeric or coercible as one.
n	an integer designing The number of scaled values (between 1 and n).
mn	minimum value (mn and lower values are set to 1).
mx	maximum value (mx and higher values are set to n).

Details

This function was originally created to ease the creation of custom color scales. In such context, it is common practice to define a minium and a maximum for the set of values to be displayed values as well as a number of color to be used in the color scale (n). This is exactly what scaleWithin() does: minimum and maximum are by default the ones of the set of values x but can also be set using mn and mx in which case values below mn will be set to mn (and thus to 1 in the output) and values above mx will be set to mx (and thus to 1 in the output). Finally, the number of colors to be used used in is given by n.

Value

A numeric vector

Examples

x <- stats::rpois(20, 20)
scaleWithin(x, 20, 10, 30)
scaleWithin(matrix(x, 10, 2), mn = 20, mx = 30)

---

Generate a regular sequence based on the range of a vector

Description

Generate a regular sequence based on the range of a vector

Usage

seqRg(x, n, offset = 0, prop = TRUE)

seqCol(df)

seqRow(df)

Arguments

x	a vector.
n	the number of values in the output sequence.
offset	extend or reduce the range .
prop	a logical. If TRUE, then offset is a proportion of the range, otherwise offset is used as is.
df	a data frame or a matrix.

Functions

• seqCol(): a regular sequence based on the number of columns in a data frame.

• seqRow(): a regular sequence based on the number of rows in a data frame.

Examples

seqRg(runif(10), 10)
seqRg(1:10, 10, .5)
seqCol(matrix(1, 3, 2))

---

Set class of data frames columns

Description

This function is designed to ease the changes of column's class of a given data frame.

Usage

setColClass(x, colid, cls)

Arguments

x	a data frame or an R object to be coerced into a data frame.
colid	the identity of columns for which class are to be changed.
cls	a character vector containing the classes' names to be used in the same order as colid. By default, cls is repeated until its size equals colid's size.

Value

A data frame whose columns have the desired classes.

Examples

df1 <- matrix(signif(runif(20),4), ncol=2)
df2 <- setColClass(df1, 2, 'character')
str(df1)
str(df2)

---

A simple function to associated p-values with symbols

Description

The signifSymbols function takes one vector of p-values and returns a vector of symbols that correspond to thresholds that can be set. Default thresholds values and symbols are the most common ones.

Usage

signifSymbols(
  pvalue,
  thresholds = c(0.1, 0.05, 0.01, 0.001),
  symbols = c(".", "*", "**", "***"),
  notsignif = "n.s."
)

Arguments

pvalue	a p-value for which a symbol is requested.
thresholds	the threshold values that define category to which symbols are assigned.
symbols	list of symbols.
notsignif	symbols for non significant p-value.

Examples

signifSymbols(.012)
signifSymbols(.008)
lapply(c(.2, .08, .04, .008, 0.0001), signifSymbols)

---

Makes a data frame or a matrix square

Description

Add missing rows or columns based on names and Duplicates rows and columns of a given a data frame.

Usage

squaretize(x, fill = 0, reorder = TRUE)

Arguments

x	an object to be coerced into matrix.
fill	character string used to fill the additional rows and/or columns.
reorder	a logical. Should names must be used to order rows and columns?

Value

A square matrix.

Examples

mat <- matrix(1:12, 3, 4)
mat2 <- squaretize(mat)
matb <- matrix(1:12, 4, 3)
colnames(matb) <- LETTERS[1:3]
mat2b <- squaretize(matb)

---

Timer and Stopwatch

Description

Timer and Stopwatch

Usage

stopwatch(max_time = 1000, pause = 0.01, digits = 5)

timer(time, pause = 0.01, digits = 5)

Arguments

max_time	time in seconds after which the stopwatch is forced to stop, use Inf to run it endlessly.
pause	time duration of the pause between 2 time increments displayed (it should better be small).
digits	number of digits displayed.
time	initial time (in seconds) for the timer.

Functions

• timer(): Timer

Examples

## Not run: 
stopwatch(10)
stopwatch(20)

## End(Not run)

---

Write data frames in a document

Description

Write a data frame or a list of data frames in a markdown document converted #' in various format using pandoc.

Usage

tblDown(
  x,
  output_file = "./tables.docx",
  section = NULL,
  caption = NULL,
  title = NULL,
  row.names = FALSE,
  ...
)

Arguments

x	a data frame or a list of data frames.
output_file	path to the output file. Its extension will be used by pandoc to correctly render the final document in the write format.
section	a vector of character strings used as section titles (optional).
caption	a vector of character strings used as captions (optional).
title	a character string used as a title for the document (optional).
row.names	a logical. Should row names be added? See knitr::kable().
...	further arguments passed to knitr::kable().

Details

This function calls base::cat() and knitr::kable() to write a Markdown document containing a list of tables that is then converted into the desired format. For section and caption if the length differ then will be cut off or expanded.

Value

A data frame whose columns have the desired classes.

References

https://pandoc.org/MANUAL.html#tables

Examples

## Not run: 
data(CO2)
tblDown(list(CO2[1:2, ], CO2[3:6,]), section = "section")
tblDown(list(CO2[1:2, ], CO2[3:6,]), "./tables.pdf")

## End(Not run)

---

Search values or patterns in a vector

Description

Search values or patterns in a vector.

Usage

whichIs(x, y, isPattern = FALSE, ...)

Arguments

x	a vector of values or patterns to be searched for.
y	a vector where x values are searched for.
isPattern	should x be considered as a vector of patterns?
...	further arguments to be passed to base::which().

Value

A list of positions. Each element corresponds to the matches for a specific x value.

Examples

vec <- LETTERS[1:10]
spl <- sample(vec)
id <- unlist(whichIs(vec, spl))
identical(vec, spl[id])

---