NCmisc-package: Miscellaneous Functions for Creating Adaptive Functions and...

In NCmisc: Miscellaneous Functions for Creating Adaptive Functions and Scripts

Miscellaneous Functions for Creating Adaptive Functions and Scripts

Description

A set of handy functions. Includes a versatile one line progress bar, one line function timer with detailed output, time delay function, text histogram, object preview, CRAN package search, simpler package installer, Linux command install check, a flexible Mode function, top function, simulation of correlated data, and more.

Details

Package:	NCmisc
Type:	Package
Version:	1.2.0
Date:	2022-10-14
License:	GPL (>= 2)

A package of general purpose functions that might save time or help tidy up code. Some of these functions are similar to existing functions but are simpler to use or have more features (e.g, timeit and loop.tracker reduce an initialisation, 'during' and close three-line call structure, to a single function call. Also, some of these functions are useful for building packages and pipelines, for instance: Header(), to provide strong visual deliniation between procedures in console output, by an ascii bordered heading; loop.tracker() to track the progress of loops (called with only 1 line of code), with the option to periodically backup a key object during the loop; estimate.memory() to determine whether the object may exceed some threshold before creating it, timeit(), a one line wrapper for proftools which gives a detailed breakdown of time taken, and time within each function called during a procedure; and check.linux.install() to verify installation status of terminal commands before using system(), top() to examine current memory and CPU usage [using the system 'top' command]. prv() is useful for debugging as it allows a detailed preview of objects, and is as easy as placing print statements within loops/functions but gives more information, and gives compact output for large objects. For testing sim.cor() provides a simple way to simulate a correlated data matrix, as often this is more realistic than completely random data. Otherwise summarise.r.datasets gives a list of all available datasets and their structure and dimensionality.

List of key functions:

• check.linux.install Check whether a given system command is installed (e.g, bash)

• comma.list Nicely format output lists with comma separation and length control

• comify Function to add commas for large numbers

• cor.with simulate a variable with a specified correlation to an existing variable

• Dim same as dim() function but works for more objects, including vectors

• dup.pairs Obtain an ordered index of all instances of values with duplicates

• estimate.memory Estimate the memory required for an object

• exists.not.function same as exists() function but ignores functions

• extend.pc Extend an interval by percentage

• fakeLines Create randomized lines of text for testing

• force.percentage Force argument to be a decimal percentage

• force.scalar Force argument to be a scalar

• get.distinct.cols Return up to 22 distinct colours

• getRepositories Return list of available repositories

• has.method Determine whether a function can be applied to an S4 class/object

• headl A good way to preview large lists

• Header Print heading text with a border

• is.vec.logical Test whether vector is logical independent of type

• is.vec.numeric Test whether vector is numeric independent of type

• list.functions.in.file Show all functions used in an R script file, by package

• list.to.env Inserts new variables in current environment from a named list

• loess.scatter Draw a scatterplot with a fit line

• loop.tracker Creates a progess bar within a loop with only 1 line

• Mode Find the mode(s) of a vector

• must.use.package Do everything possible to load an R package

• narm Return an object with missing values removed

• nearest.to Similar to base match function but picks nearest instead of exact match

• Numerify Convert only suitable columns to numeric format in data.frame

• out.of Simplify outputting fractions/percentages

• p.to.Z Convert p-values to Z-scores

• packages.loaded quietly test whether packages are loaded without using require

• pad.left Print a vector with appropriate padding so each has equal char length

• pctile Find data thresholds corresponding to percentiles

• ppa Posterior probability for p-values

• preview same as prv, but enter arguments as strings

• prv.large tidy representation for large matrices/data.frames

• prv compact preview of objects (more complete than 'print')

• replace.missing.df replace missing values in data.frame automatically

• Rfile.index Create an index file for an R function file

• rmv.names Remove names from object

• rmv.spc Remove leading and trailing spaces (or other character)

• search.cran Search all CRAN packages for those containing keyword(s)

• sim.cor simulate a correlated dataset

• simple.date generate a string with compact summary of date/time

• spc Print a character a specified number of times

• standardize Convert a numeric vector to Z-scores

• Substitute multivariable version of substitute (base)

• summary2 Extension of base:summary that adds SD, SE and keeps names fixed and cleaner

• summarise.r.datasets show and summarise all available example datasets

• table2d Extension of base:table that forces fixed rows and columns

• textogram Make an ascii histogram in the console

• timeit Times an expression, with breakdown of time spent in functions

• toheader Return a string with each first letter of each word in upper case

• top report on CPU and memory usage, overall or by process

• Unlist Unlist a list, starting only from a set depth

• wait Wait for a period of time

• which.outlier Return indexes of univariate outliers

• Z.to.p Convert Z-scores to p-values

Author(s)

Nicholas Cooper

Maintainer: Nicholas Cooper <[e-mail]>

See Also

reader ~~

Examples

#text histogram suited to working from a console without GUI graphics
textogram(rnorm(10000),range=c(-3,3))
# wait 0.2 seconds
wait(0.2,silent=FALSE) 
# see whether a system command is installed
check.linux.install("sed") 
# a nice progress bar
max <- 100; for (cc in 1:max) { loop.tracker(cc,max); wait(0.004,"s") }
# nice header
Header(c("SPACE","The final frontier"))
# memory req'd for proposed or actual object
estimate.memory(matrix(rnorm(100),nrow=10)) 
# a mode function (there isn't one included as part of base)
Mode(c(1,2,3,3,4,4,4))
# search for packages containing text, eg, 'misc'
search.cran("misc", repos="http://cran.ma.imperial.ac.uk/") 
# simulate a correlated dataset
corDat <- sim.cor(200,5)
cor(corDat) # show correlation matrix
prv(corDat) # show compact preview of matrix
# Dim() versus dim()
Dim(1:10); dim(1:10)
# find nearest match in a vector:
nearest.to(1:100, 50.5)

NCmisc documentation built on Oct. 17, 2022, 5:09 p.m.