Package 'caMisc' reference manual

Title:	Different Functions
Description:	More about what it does (maybe more than one line)
Authors:	Christoffer Moesgaard Albertsen [aut, cre], Technical University of Denmark [cph]
Maintainer:	Christoffer Moesgaard Albertsen <[email protected]>
License:	BSD_2_clause + file LICENSE
Version:	1.0.2
Built:	2024-11-16 05:05:18 UTC
Source:	https://github.com/calbertsen/caMisc

Add shade to a color name

Description

Add shade to a color name

Usage

addShade(name, shade = 0)
addShade(name, shade = 0)

Arguments

`name`	name of the color
`shade`	shade value (between 0 and 1). For zero, the same color is returned.

Value

a new color name

Author(s)

Christoffer Moesgaard Albertsen

Add tint to a color name

Description

Add tint to a color name

Usage

addTint(name, tint = 0)
addTint(name, tint = 0)

Arguments

`name`	name of the color
`tint`	tint value (between 0 and 1). For 0, the same color is returned

Value

a new color name

Author(s)

Christoffer Moesgaard Albertsen

Add tone to a color name

Description

Add tone to a color name

Usage

addTone(name, tone = 0)
addTone(name, tone = 0)

Arguments

`name`	name of the color
`tone`	tone value (between 0 and 1). For 0, the same color is returned.

Value

a new color name

Author(s)

Christoffer Moesgaard Albertsen

Add alpha value to a color name

Description

Add alpha value to a color name

Usage

addTrans(name, alpha = 1)
addTrans(name, alpha = 1)

Arguments

`name`	name of the color
`alpha`	alpha value (between 0 and 1)

Value

a new color name

Author(s)

Christoffer Moesgaard Albertsen

Draw figure axis inside plot

Description

Draw figure axis inside plot

Usage

axisInside(side)
axisInside(side)

Arguments

side

side of plot to draw on

Value

Nothing, but plots as side effect

Author(s)

Christoffer Moesgaard Albertsen

Beanplot of something

Description

Beanplot of something

Usage

beanplot(x, ...)
beanplot(x, ...)

Arguments

`x`	Some object
`...`	Other arguments

Value

Creates a plot

Author(s)

Christoffer Moesgaard Albertsen

Add text with background to plot

Description

Add text with background to plot

Usage

bgtext(
  x,
  y,
  labels,
  ...,
  cex = 1,
  font = NULL,
  bg = "white",
  bgex = 1,
  border = NA
)
bgtext(
  x,
  y,
  labels,
  ...,
  cex = 1,
  font = NULL,
  bg = "white",
  bgex = 1,
  border = NA
)

Arguments

`x`	x-coordinate
`y`	y-coordinate
`labels`	label to add
`...`	arguments passed to text
`cex`	size of text
`font`	font of text
`bg`	background color
`bgex`	background extend factor
`border`	border color of background

Author(s)

Christoffer Moesgaard Albertsen

Download and build an R package from GitHub

Description

Download and build an R package from GitHub

Usage

buildFromGithub(
  repo,
  ref,
  subdir = NULL,
  buildArgs = c("--no-build-vignettes")
)
buildFromGithub(
  repo,
  ref,
  subdir = NULL,
  buildArgs = c("--no-build-vignettes")
)

Arguments

`repo`	GitHub user and repository separated by /
`ref`	Reference to commit or branch. Default is master
`subdir`	Path to subdir containing the package. Should be NULL if the package is in the top directory
`buildArgs`	Character vector of arguments passed to R CMD build. Default is "–no-build-vignettes"

Value

Nothing

Author(s)

Christoffer Moesgaard Albertsen

Convert number to display text

Description

Convert number to display text

Usage

displayNum(
  x,
  capitalize = FALSE,
  big.mark = ",",
  decimal.mark = ".",
  small.mark = "",
  digits = 0
)
displayNum(
  x,
  capitalize = FALSE,
  big.mark = ",",
  decimal.mark = ".",
  small.mark = "",
  digits = 0
)

Arguments

`x`	number
`capitalize`	Capitalize first letter?

Value

LaTeX code for the fraction

Author(s)

Text representation of number

DTU color palette

Description

DTU color palette

Usage

dtucols(x)
dtucols(x)

Arguments

`x`	name of colors to return

Value

color codes

Author(s)

Christoffer Moesgaard Albertsen

Convert to a DZSlides presentation

Description

Format for converting from R Markdown to a DZSlides presentation.

Usage

dzslides_presentation(
  incremental = FALSE,
  fig_width = 8,
  fig_height = 6,
  fig_retina = if (!fig_caption) 2,
  fig_caption = FALSE,
  dev = "png",
  smart = TRUE,
  self_contained = TRUE,
  highlight = "default",
  mathjax = "default",
  template = "default",
  css = NULL,
  includes = NULL,
  keep_md = FALSE,
  lib_dir = NULL,
  md_extensions = NULL,
  pandoc_args = NULL,
  ...
)
dzslides_presentation(
  incremental = FALSE,
  fig_width = 8,
  fig_height = 6,
  fig_retina = if (!fig_caption) 2,
  fig_caption = FALSE,
  dev = "png",
  smart = TRUE,
  self_contained = TRUE,
  highlight = "default",
  mathjax = "default",
  template = "default",
  css = NULL,
  includes = NULL,
  keep_md = FALSE,
  lib_dir = NULL,
  md_extensions = NULL,
  pandoc_args = NULL,
  ...
)

Arguments

`incremental`	should lists be incremental?
`fig_width`	figure width
`fig_height`	figure height
`fig_retina`	retina figure?
`fig_caption`	figure caption?
`dev`	figure device
`smart`	smart?
`self_contained`	self contained?
`highlight`	highlighting style
`mathjax`	mathjax
`template`	template path
`css`	extra css
`includes`	extra includes
`keep_md`	keep markdown file?
`lib_dir`	...
`md_extensions`	markdown extensions to use
`pandoc_args`	extra pandoc arguments
`...`	other arguments

Value

R Markdown output format to pass to render

Author(s)

Christoffer Moesgaard Albertsen

Examples

## Not run: 

library(rmarkdown)

# simple invocation
render("pres.Rmd", dzslides_presentation())

# specify an option for incremental rendering
render("pres.Rmd", dzslides_presentation(incremental = TRUE))

## End(Not run)
##' @export
## Not run: 

library(rmarkdown)

# simple invocation
render("pres.Rmd", dzslides_presentation())

# specify an option for incremental rendering
render("pres.Rmd", dzslides_presentation(incremental = TRUE))

## End(Not run)
##' @export

Format date with locale

Description

Format date with locale

Usage

formatDate(x, format = "", locale = Sys.getlocale("LC_TIME"), ...)
formatDate(x, format = "", locale = Sys.getlocale("LC_TIME"), ...)

Arguments

`x`	date
`format`	format to use
`locale`	locale to use
`...`	passed to strftime

Value

formatted date string

Author(s)

Christoffer Moesgaard Albertsen

Create coverage table from list of gcov objects

Description

Create coverage table from list of gcov objects

Usage

gcovTable(x, ...)
gcovTable(x, ...)

Arguments

`x`	list of gcov objects
`...`	additional arguments passed to formatC

Value

A coverage table

Author(s)

Christoffer Moesgaard Albertsen

Get a pixel matrix from an image file

Description

Get a pixel matrix from an image file

Usage

getPixelMatrix(file, grey = FALSE)
getPixelMatrix(file, grey = FALSE)

Arguments

`file`	Path to image file
`grey`	Should output be greyscale?

Value

A matrix of pixel values (0-255)

Author(s)

Christoffer Moesgaard Albertsen

Calculate gradient of a function

Description

Calculate gradient of a function

Usage

grad(
  func,
  x,
  h = abs(1e-04 * x) + 1e-04 * (abs(x) < sqrt(.Machine$double.eps/7e-07)),
  ...
)
grad(
  func,
  x,
  h = abs(1e-04 * x) + 1e-04 * (abs(x) < sqrt(.Machine$double.eps/7e-07)),
  ...
)

Arguments

`func`	function
`x`	parameter values
`h`	step size
`...`	passed to func

Value

gradient vector

Emulate green blindness in colors

Description

Based on https://personal.sron.nl/~pault/data/colourschemes.pdf

Usage

greenBlindness(red, green, blue, alpha = 1, names = NULL, maxColorValue = 255)
greenBlindness(red, green, blue, alpha = 1, names = NULL, maxColorValue = 255)

Arguments

`red`	Red RGB value (or color HEX code or name - alpha is ignored)
`green`	Green RGB value
`blue`	Blue RGB value
`alpha`	alpha value to use
`names`	Names for the resulting vector
`maxColorValue`	Maximum color value for red, green, blue

Value

New colors

Author(s)

Christoffer Moesgaard Albertsen

Plot image from file

Description

Plot image from file

Usage

imagePlot(
  x,
  objectFit = c("fill", "contain", "cover", "none", "scale-down"),
  halign = c("c", "l", "r"),
  valign = c("c", "t", "b"),
  maxWidthPct = 1,
  maxHeightPct = 1,
  add = FALSE,
  noMargin = TRUE,
  ...
)
imagePlot(
  x,
  objectFit = c("fill", "contain", "cover", "none", "scale-down"),
  halign = c("c", "l", "r"),
  valign = c("c", "t", "b"),
  maxWidthPct = 1,
  maxHeightPct = 1,
  add = FALSE,
  noMargin = TRUE,
  ...
)

Arguments

`x`	path to image
`objectFit`	How the image should fill the plot: "fill", "contain", "cover", "none","scale-down"
`halign`	Horizontal alignment: c, l, r
`valign`	Vertical alignment: c, t, b
`noMargin`	Plot with oma and mar set to zero
`...`	other arguments

Value

Plots the image

Author(s)

Christoffer Moesgaard Albertsen

Download, build, and install package dependencies

Description

Download, build, and install package dependencies

Usage

installDependencies(
  descriptionPath,
  buildArgs = c("--no-build-vignettes"),
  installArgs = c(),
  dependencies = c("Depends", "Imports", "LinkingTo")
)
installDependencies(
  descriptionPath,
  buildArgs = c("--no-build-vignettes"),
  installArgs = c(),
  dependencies = c("Depends", "Imports", "LinkingTo")
)

Arguments

`descriptionPath`	Path to a DESCRIPTION file
`buildArgs`	Character vector of arguments passed to R CMD build.
`installArgs`	Character vector of arguments passed to R CMD INSTALL.
`dependencies`	Character vector of dependency types to install ("Depends","Imports","LinkingTo","Enhances", or "Suggests")

Value

Nothing

Author(s)

Christoffer Moesgaard Albertsen

Download, build, and install an R package from GitHub

Description

Download, build, and install an R package from GitHub

Usage

installFromGithub(
  repo,
  ref,
  subdir = NULL,
  buildArgs = c("--no-build-vignettes"),
  installArgs = c(),
  dependencies = c("Depends", "Imports", "LinkingTo"),
  https = TRUE
)
installFromGithub(
  repo,
  ref,
  subdir = NULL,
  buildArgs = c("--no-build-vignettes"),
  installArgs = c(),
  dependencies = c("Depends", "Imports", "LinkingTo"),
  https = TRUE
)

Arguments

`repo`	GitHub user and repository separated by /
`ref`	Reference to commit or branch. Default is master
`subdir`	Path to subdir containing the package. Should be NULL if the package is in the top directory
`buildArgs`	Character vector of arguments passed to R CMD build.
`installArgs`	Character vector of arguments passed to R CMD INSTALL.
`dependencies`	Character vector of dependency types to install ("Depends","Imports","LinkingTo","Enhances", or "Suggests")

Value

Nothing

Author(s)

Christoffer Moesgaard Albertsen

Calculate jacobian of a function

Description

Calculate jacobian of a function

Usage

jacobian(
  func,
  x,
  h = abs(1e-04 * x) + 1e-04 * (abs(x) < sqrt(.Machine$double.eps/7e-07)),
  ...
)
jacobian(
  func,
  x,
  h = abs(1e-04 * x) + 1e-04 * (abs(x) < sqrt(.Machine$double.eps/7e-07)),
  ...
)

Arguments

`func`	function
`x`	parameter values
`h`	step size
`...`	passed to func

Value

jacobian matrix

Add map legend for choropleth map

Description

Add map legend for choropleth map

Usage

makeMapLegend(x, cols, txt)
makeMapLegend(x, cols, txt)

Arguments

`x`	Variable values plotted
`cols`	Colors
`txt`	Title / description

Author(s)

Christoffer Moesgaard Albertsen

Make a pixel matrix/array square

Description

Make a pixel matrix/array square

Usage

makeSquare(p, value = 0, asp = 1)
makeSquare(p, value = 0, asp = 1)

Arguments

`p`	Pixel matrix/array
`value`	Value of added pixels

Author(s)

Christoffer Moesgaard Albertsen

Create a package skeleton

Description

Create a package skeleton

Usage

packageSkeleton(pkg, path = file.path("."))
packageSkeleton(pkg, path = file.path("."))

Arguments

`pkg`	Name of the new package
`path`	(existing) Directory of package

Value

Used for side effects

Author(s)

Christoffer Moesgaard Albertsen

Bootstrap particle filter

Description

Function to run a bootstrap particle filter for user defined model.

Usage

particlefilter(N, T, G, M, F = NULL, envir = .GlobalEnv, seed = NULL)
particlefilter(N, T, G, M, F = NULL, envir = .GlobalEnv, seed = NULL)

Arguments

`N`	Number of particles
`T`	Number of time steps
`G`	Function to simulate hidden states (of dimension p) given previous (See Details)
`M`	Function to calculate log-likelihood of data for a given particle
`F`	Do not use!
`envir`	Environment the functions should be evaluated in (containing data and parameters)
`seed`	Random seed to start the filter

Details

The G function should be of the form G <- function(t,X) and return a numeric vector of simulate values from $X_t | X_{t-1} = X$ . For $t = 1$ the function will be called as G(1,NULL). The M function should be of the form M <- function(t, X) and return the density of the observation at time t given the latent state $X_t$

Value

A list with a p x N x T array X containing the simulated particles (X) and a vector of length T with the negative log-likelihood contribution at each time point.

Author(s)

Christoffer Moesgaard Albertsen [email protected]

Examples

## Univariate example
env <- new.env()
env$pars <- list(sdobs = 0.4, sdstate = 0.3)
local({xx <- cumsum(rnorm(100,0,pars$sdstate))},env)
local({dat <- xx + rnorm(100,0,pars$sdobs)},env)
G <- function(t,X){
            if(t == 1){
               return(rnorm(1,0,pars$sdstate))
            }else{
               return(rnorm(1,X,pars$sdstate))
            }
}
M <- function(t,X){
    return(dnorm(dat[t],X,pars$sdobs, TRUE))
}
pest <- particlefilter(N = 1000, T = 100,
                 G=G,M=M,
                 envir=env, seed=1)
## Not run: 
plot(env$dat)
lines(apply(pest$X[1,,],2,mean),col="red")
lines(apply(pest$X[1,,],2,mean) + 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(apply(pest$X[1,,],2,mean) - 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(env$xx)

## End(Not run)

## Bivariate example
env <- new.env()
env$pars <- list(sdobs = 0.4, sdstate = 0.3)
local({xx <- cbind(cumsum(rnorm(100,0,pars$sdstate)),
             cumsum(rnorm(100,0,pars$sdstate)))},env)
local({dat <- xx + matrix(rnorm(2 * 100,0,pars$sdobs),ncol=2)},env)
G <- function(t,X){
            if(t == 1){
               return(rnorm(2,0,pars$sdstate))
            }else{
               return(rnorm(2,X,pars$sdstate))
            }
}
M <- function(t,X){
    return(sum(dnorm(dat[t,],X,pars$sdobs,TRUE)))
}
pest <- particlefilter(N = 1000, T = 100,
                 G=G,M=M,
                 envir=env, seed=1)
## Not run: 
layout(cbind(1,c(2,3)))
plot(env$dat)
lines(env$xx)
lines(apply(pest$X,c(3,1),mean),col="red")
plot(env$dat[,1])
lines(apply(pest$X[1,,],2,mean),col="red")
lines(apply(pest$X[1,,],2,mean) + 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(apply(pest$X[1,,],2,mean) - 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(env$xx[,1])
plot(env$dat[,2])
lines(apply(pest$X[2,,],2,mean),col="red")
lines(apply(pest$X[2,,],2,mean) + 2 * apply(pest$X[2,,],2,sd),col="red",lty=2)
lines(apply(pest$X[2,,],2,mean) - 2 * apply(pest$X[2,,],2,sd),col="red",lty=2)
lines(env$xx[,2])

## End(Not run)
## Univariate example
env <- new.env()
env$pars <- list(sdobs = 0.4, sdstate = 0.3)
local({xx <- cumsum(rnorm(100,0,pars$sdstate))},env)
local({dat <- xx + rnorm(100,0,pars$sdobs)},env)
G <- function(t,X){
            if(t == 1){
               return(rnorm(1,0,pars$sdstate))
            }else{
               return(rnorm(1,X,pars$sdstate))
            }
}
M <- function(t,X){
    return(dnorm(dat[t],X,pars$sdobs, TRUE))
}
pest <- particlefilter(N = 1000, T = 100,
                 G=G,M=M,
                 envir=env, seed=1)
## Not run: 
plot(env$dat)
lines(apply(pest$X[1,,],2,mean),col="red")
lines(apply(pest$X[1,,],2,mean) + 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(apply(pest$X[1,,],2,mean) - 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(env$xx)

## End(Not run)

## Bivariate example
env <- new.env()
env$pars <- list(sdobs = 0.4, sdstate = 0.3)
local({xx <- cbind(cumsum(rnorm(100,0,pars$sdstate)),
             cumsum(rnorm(100,0,pars$sdstate)))},env)
local({dat <- xx + matrix(rnorm(2 * 100,0,pars$sdobs),ncol=2)},env)
G <- function(t,X){
            if(t == 1){
               return(rnorm(2,0,pars$sdstate))
            }else{
               return(rnorm(2,X,pars$sdstate))
            }
}
M <- function(t,X){
    return(sum(dnorm(dat[t,],X,pars$sdobs,TRUE)))
}
pest <- particlefilter(N = 1000, T = 100,
                 G=G,M=M,
                 envir=env, seed=1)
## Not run: 
layout(cbind(1,c(2,3)))
plot(env$dat)
lines(env$xx)
lines(apply(pest$X,c(3,1),mean),col="red")
plot(env$dat[,1])
lines(apply(pest$X[1,,],2,mean),col="red")
lines(apply(pest$X[1,,],2,mean) + 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(apply(pest$X[1,,],2,mean) - 2 * apply(pest$X[1,,],2,sd),col="red",lty=2)
lines(env$xx[,1])
plot(env$dat[,2])
lines(apply(pest$X[2,,],2,mean),col="red")
lines(apply(pest$X[2,,],2,mean) + 2 * apply(pest$X[2,,],2,sd),col="red",lty=2)
lines(apply(pest$X[2,,],2,mean) - 2 * apply(pest$X[2,,],2,sd),col="red",lty=2)
lines(env$xx[,2])

## End(Not run)

Read content of .gcov file

Description

Read content of .gcov file

Usage

read_gcov(file)
read_gcov(file)

Arguments

file

path to .gcov file

Value

a gcov object

Author(s)

Christoffer Moesgaard Albertsen

Read valgrind Massif output

Description

Read valgrind Massif output

Usage

read_massif(file, keep_details = FALSE)
read_massif(file, keep_details = FALSE)

Arguments

`file`	file to read
`keep_details`	keep details?

Value

massif S3 object

Author(s)

Christoffer Moesgaard Albertsen

Calculate solar angles

Description

Calculate solar angles

Usage

solarPosition(date, lat, lon)
solarPosition(date, lat, lon)

Arguments

`date`	date (UTC) in the format "YYY-mm-dd HH:MM:SS"
`lat`	latitude of observer
`lon`	longitude of observer

Value

list of values

Author(s)

Christoffer Moesgaard Albertsen Modified from https://doi.org/10.1016/j.renene.2021.03.047

Print number as (LaTeX) fraction

Description

Print number as (LaTeX) fraction

Usage

tofrac(x, dollar = TRUE)
tofrac(x, dollar = TRUE)

Arguments

`x`	number
`dollar`

Value

LaTeX code for the fraction

Author(s)

Christoffer Moesgaard Albertsen

Turn pixel into grey scale

Description

Turn pixel into grey scale

Usage

toGreyscale(p)
toGreyscale(p)

Arguments

`p`	Pixel matrix/array

Value

A grey scale pixel matrix/array

Author(s)

Christoffer Moesgaard Albertsen

`x`	vector of values
`collap`	rule for collapsing

Package 'caMisc'

Help Index

Add shade to a color name

Description

Usage

Arguments

Value

Author(s)

Add tint to a color name

Description

Usage

Arguments

Value

Author(s)

Add tone to a color name

Description

Usage

Arguments

Value

Author(s)

Add alpha value to a color name

Description

Usage

Arguments

Value

Author(s)

Draw figure axis inside plot

Description

Usage

Arguments

Value

Author(s)

Beanplot of something

Description

Usage

Arguments

Value

Author(s)

Add text with background to plot

Description

Usage

Arguments

Author(s)

Download and build an R package from GitHub

Description

Usage

Arguments

Value

Author(s)

Collapse vector to string

Description

Usage

Arguments

Value

Author(s)

Convert number to display text

Description

Usage

Arguments

Value

Author(s)

DTU color palette

Description

Usage

Arguments

Value

Author(s)

Convert to a DZSlides presentation

Description

Usage

Arguments

Value

Author(s)

Examples

Format number

Description

Usage

Arguments

Value

Author(s)