Life data analysis examines the behavior of systems over time. Often
termed Weibull data analysis, due to the common use of the Weibull
distribution, this field involves iterative data wrangling, modeling,
and visualization. Interactive Weibull modeling offers numerous
advantages, such as the ability to explore subsamples and uncover hidden
data structures. WeibullR.plotly
(Govan 2023b) is an open-source software package
designed for creating interactive Weibull Probability Plots. It aims to
provide more flexibility for exploratory Weibull analysis than
traditional static plotting. The primary users of this project are
analysts and engineers involved in life data, survival, and reliability
analysis.
WeibullR.plotly
is developed in R (R Core Team 2023), leveraging
WeibullR
(Silkworth and Symynck
2022), a package dedicated to Life Data Analysis, and
plotly
(Sievert 2020), an
interactive web-based graphing library. This combination leverages the
strengths of both tools, making WeibullR.plotly
ideal for
embedding in web-based applications, such as learnr
(Aden-Buie et al. 2023) interactive tutorials or
shiny
(Chang et al. 2024) web
applications. Examples include WeibullR.learnr
(Govan 2023a), a learnr module for Life Data
Analysis, and WeibullR.shiny
(Govan
2023c), a shiny app designed for Weibull Analysis.
WeibullR.plotly
is available on the Comprehensive R
Archive Network (CRAN) as an R package at https://CRAN.R-project.org/package=WeibullR.plotly.
To install the release verion in R, use:
install.packages(“WeibullR.plotly”)
To install the latest development version:
devtools::install_github(‘paulgovan/WeibullR.plotly’)
To build a Weibull Probability Plot, fit a wblr
object
to a life data set using the WeibullR
package, then
generate plots with the plotly_wblr
function.
library(WeibullR)
library(WeibullR.plotly)
failures<-c(30, 49, 82, 90, 96)
obj<-wblr.conf(wblr.fit(wblr(failures)))
plotly_wblr(obj, main='Weibull Probability Plot', xlab='Years', ylab='Failure Probability', confCol='blue', signif=4, grid=FALSE)
Create contour plots using the plotly_contour
function
with a wblr
object.
plotly_contour(obj, main='Weibull Contour Plot', col='red', signif=4, grid=FALSE)
Customize labels, colors, and grids to tailor the plots to specific needs. Refer to the package documentation for a comprehensive list of options.
Full documentation and working examples are available at: https://paulgovan.github.io/WeibullR.plotly/.
The project documentation includes guidance on installing
WeibullR.plotly
and its dependencies, demonstrations of how
to use the package functions. Unit tests for ensuring code reliability
and performance, and further learning resources for getting started with
the package.
Engineers and analysts are encouraged to use and contribute to the project. The repository includes a Contributor Code of Conduct. Issues and feature requests can be submitted through Issues or Pull Requests here: https://github.com/paulgovan/WeibullR.plotly/issues.