cmstatr

cmstatr: An R Package for Statistical Analysis of Composite Material Data - Published in JOSS (2020)

https://github.com/cmstatr/cmstatr

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An R Package for Statistical Analysis of Composite Material Data

README.Rmd

---
output: github_document
---



```{r, echo = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/"
)
```

# cmstatr 


[![R-CMD-check](https://github.com/cmstatr/cmstatr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/cmstatr/cmstatr/actions/workflows/R-CMD-check.yaml)
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[![DOI](https://joss.theoj.org/papers/10.21105/joss.02265/status.svg)](https://doi.org/10.21105/joss.02265)
[![CRAN_Status_Badge](https://www.r-pkg.org/badges/version/cmstatr)](https://cran.r-project.org/package=cmstatr)
[![](https://cranlogs.r-pkg.org/badges/cmstatr)](https://cran.r-project.org/package=cmstatr)


# What It Does
The `cmstatr` package provides functions for performing statistical analysis
of composite material data. The statistical methods implemented are those
described in [CMH-17-1G](https://www.cmh17.org/).
This package focuses on calculating basis values (lower tolerance
bounds) for material strength properties, as well as performing the
associated diagnostic tests. Functions are also provided for testing
for equivalency between alternate samples and the "qualification"
or "baseline" samples.

Additional details about the package are available in the paper by
Kloppenborg (2020,
[https://doi.org/10.21105/joss.02265](https://doi.org/10.21105/joss.02265)).

There is a companion package `cmstatrExt` which provides statistical methods
that are not included in CMH-17, but which may be of use to practitioners.
For more information, please see the
[`cmstatrExt` Website](https://cmstatrext.cmstatr.net).

# Installation
To install `cmstatr` from CRAN, simply run:

```r
install.packages("cmstatr")
```

If you want the latest development version, you can install it
from `github` using `devtools`. This will also install the dependencies
required to build the vignettes. Optionally, change the value of the
argument `ref` to install `cmstatr` from a different branch of the
repository.

```r
install.packages(c("devtools", "rmarkdown", "dplyr", "tidyr"))
devtools::install_github("cmstatr/cmstatr", build_vignettes = TRUE,
                         ref = "master",
                         build_opts = c("--no-resave-data", "--no-manual"))
```

# Usage
To compute a B-Basis value from an example data set packaged
with `cmstatr` you can do the following:

```{r message=FALSE}
library(dplyr)
library(cmstatr)

carbon.fabric.2 %>%
  filter(test == "FC") %>%
  filter(condition == "RTD") %>%
  basis_normal(strength, batch)
```

For more examples of usage of the `cmstatr` package,
see the tutorial vignette, which can be
[viewed online](https://www.cmstatr.net/articles/cmstatr_Tutorial.html),
or can be loaded as follows, once the package is installed:

```r
vignette("cmstatr_Tutorial")
```

There is also a vignette showing some examples of the types of graphs
that are typically produced when analyzing composite materials.
You can view this
[vignette online](https://www.cmstatr.net/articles/cmstatr_Graphing.html),
or you can load this vignette with:

```r
vignette("cmstatr_Graphing")
```

# Philosophical Notes
This package expects
[`tidy data`](https://doi.org/10.18637/jss.v059.i10).
That is, individual observations should be in rows and variables in columns.

Where possible, this package uses general solutions. Look-up tables are avoided
wherever possible.

# Issues
If you've found a bug, please open an issue in this repository and
describe the bug. Please
include a [reproducible example](https://reprex.tidyverse.org/) of the bug.
If you're able to fix the bug, you can do so by submitting a pull request.

If your bug is related to a particular data set, sharing that data set will
help to fix the bug. If you cannot share the data set, please strip any
identifying information and optionally scale the data by an unspecified
factor so that the bug can be reproduced and diagnosed.


# Contributing
Contributions to `cmstatr` are always welcomed. For small changes (fixing typos
or improving the documentation), go ahead and submit a pull request. For more
significant changes, such as new features, please discuss the proposed change
in an issue first.

## Contribution Guidelines
- Please create a git branch for each pull request (PR)
- Before submitting a pull request, please make sure that `R CMD check`
  passes with no errors, warnings or notes
- New and modified code should follow the style guide enforced by the
  [`lintr`](https://cran.r-project.org/package=lintr)
  package
- Document all exported functions using
  [`roxygen2`](https://cran.r-project.org/package=roxygen2)
- Write tests using [`testthat`](https://cran.r-project.org/package=testthat).
  If your contribution fixes a bug, then the test(s) that you add should fail
  before your bug-fix patch is applied and should pass after the code is
  patched.
- For changes that affect the user, add a bullet at the top of `NEWS.md` below
  the current development version
  
## Development
Testing is performed using `testthat`. Edition 3 of that package is used and
parallel processing enabled. If you wish to use more than two CPUs, set the
environment variable `TESTTHAT_CPUS` to the number of CPUs that you want to
use. One way of doing this is to create the file `.Rprofile` with the following
contents. This file is ignored both by `git` and also in `.Rbuildingore`.

```r
Sys.setenv(TESTTHAT_CPUS = 8)
```

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