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Merge pull request #36 from R4EPI/cran-release-02-2023
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cran release 02 2023
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aspina7 authored Feb 4, 2025
2 parents 6a1fd65 + da6282b commit 72aa8c5
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1 change: 1 addition & 0 deletions .Rbuildignore
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^docs$
^pkgdown$
^CRAN-RELEASE$
^CRAN-SUBMISSION$
2 changes: 1 addition & 1 deletion .github/workflows/R-CMD-check.yaml
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Expand Up @@ -41,7 +41,7 @@ jobs:

- uses: r-lib/actions/setup-r-dependencies@v2
with:
extra-packages: any::rcmdcheck
extra-packages: local::., any::rcmdcheck
needs: check

- uses: r-lib/actions/check-r-package@v2
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3 changes: 3 additions & 0 deletions CRAN-SUBMISSION
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Version: 0.1.6
Date: 2024-01-22 23:59:23 UTC
SHA: 07478e47d4472f6943691aaa254a28c1365b6e4a
12 changes: 6 additions & 6 deletions DESCRIPTION
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Package: epikit
Title: Miscellaneous helper tools for epidemiologists
Version: 0.1.4
Title: Miscellaneous Helper Tools for Epidemiologists
Version: 0.1.6
Authors@R:
c(person(given = "Alexander",
family = "Spina",
email = "[email protected]",
comment = c(ORCID = "0000-0001-8425-1867"),
role = c("aut", "cre")),
role = c("aut")),
person(given = "Zhian N.",
family = "Kamvar",
role = "aut",
role = c("aut", "cre"),
email = "[email protected]",
comment = c(ORCID = "0000-0003-1458-7108")),
person(given = "Dirk",
Expand All @@ -23,7 +23,7 @@ Description: Contains tools for formatting inline code, renaming redundant
columns, aggregating age categories, adding survey weights, finding the earliest
date of an event, plotting z-curves, generating population counts and
calculating proportions with confidence intervals. This is part of the
'R4Epis' project <https://r4epis.netlify.com>.
'R4Epis' project <https://r4epis.netlify.app/>.
License: GPL-3
Encoding: UTF-8
LazyData: true
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rmarkdown
Additional_repositories: https://r4epi.github.io/drat
URL: https://github.com/R4EPI/epikit,
https://r4epis.netlify.com,
https://r4epis.netlify.app,
https://r4epi.github.io/epikit/
BugReports: https://github.com/R4EPI/epikit/issues
VignetteBuilder: knitr
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1 change: 1 addition & 0 deletions NAMESPACE
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Expand Up @@ -42,5 +42,6 @@ importFrom(sf,st_make_grid)
importFrom(sf,st_polygon)
importFrom(sf,st_set_crs)
importFrom(sf,st_sf)
importFrom(stats,setNames)
importFrom(tibble,as_tibble)
importFrom(utils,read.csv)
14 changes: 14 additions & 0 deletions NEWS.md
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# epikit 0.1.6

* internal documentation fix. No user-visible changes.

# epikit 0.1.5

* removed tidyr::unite() in favour of paste-ing two columns together
* added `separator` argument to `_ci()` functions which now defaults to `-`
(@aspina7, #31)

# epikit 0.1.4

* unecessary bump because {pkgdown}

# epikit 0.1.3

(non-cran release)

* migrated functions and tests from {sitrep} including: `add_weights_cluster()`,
`add_weights_strata()`, `find_date_cause()`, `find_end_date()`,
`find_start_date()`, `gen_polygon()`, `gen_population()` and `zcurve()` (@aspina7, #22)
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1 change: 1 addition & 0 deletions R/epikit-package.R
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# roxygen namespace tags. Modify with care!
## usethis namespace: start
#' @importFrom rlang .data :=
#' @importFrom stats setNames
#' @importFrom ggplot2 ggplot
#' @importFrom ggplot2 aes
#' @importFrom ggplot2 stat_density
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5 changes: 2 additions & 3 deletions R/relabel_proportions.R
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Expand Up @@ -58,9 +58,8 @@ augment_redundant <- function(x, ...) {
#' calls for the express purpose of renaming functions. This function is
#' intended for internal use to be passed to other MSF packages.
#'
#' @param call a language object reflecting the current call.
#' @param ... passed from the calling function
#'
#' @param parent the level of the parent function. Defaults to 1, which
#' selects the dots from the immediate parent.
#'
#' @return a list of character vectors
#' @export
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4 changes: 2 additions & 2 deletions README.Rmd
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<!-- badges: start -->
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
[![Lifecycle: experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![CRAN status](https://www.r-pkg.org/badges/version/epikit)](https://CRAN.R-project.org/package=epikit)
[![Codecov test coverage](https://codecov.io/gh/R4EPI/epikit/branch/master/graph/badge.svg)](https://codecov.io/gh/R4EPI/epikit?branch=master)
[![Codecov test coverage](https://app.codecov.io/gh/R4EPI/epikit/branch/master/graph/badge.svg)](https://app.codecov.io/gh/R4EPI/epikit?branch=master)
[![R-CMD-check](https://github.com/R4EPI/epikit/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/R4EPI/epikit/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

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90 changes: 70 additions & 20 deletions README.md
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Expand Up @@ -5,17 +5,17 @@ epikit
<!-- badges: start -->

[![Lifecycle:
experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://www.tidyverse.org/lifecycle/#experimental)
experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
[![CRAN
status](https://www.r-pkg.org/badges/version/epikit)](https://CRAN.R-project.org/package=epikit)
[![Codecov test
coverage](https://codecov.io/gh/R4EPI/epikit/branch/master/graph/badge.svg)](https://codecov.io/gh/R4EPI/epikit?branch=master)
coverage](https://app.codecov.io/gh/R4EPI/epikit/branch/master/graph/badge.svg)](https://app.codecov.io/gh/R4EPI/epikit?branch=master)
[![R-CMD-check](https://github.com/R4EPI/epikit/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/R4EPI/epikit/actions/workflows/R-CMD-check.yaml)
<!-- badges: end -->

The goal of {epikit} is to provide miscellaneous functions for applied
epidemiologists. This is a product of the R4EPIs project; learn more at
<https://r4epis.netlify.com>.
<https://r4epis.netlify.app/>.

## Installation

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#> 20 30-39 <NA> 30-39 years
```

## Quick proportions with conficence intervals

There are three functions that will provide quick statistics for
different rates based on binomial estimates of proportions from
`binom::binom.wilson()`

- `attack_rate()`
- `case_fatality_rate()`
- `mortality_rate()`

``` r
attack_rate(10, 50)
#> cases population ar lower upper
#> 1 10 50 20 11.24375 33.03711
case_fatality_rate(2, 50)
#> deaths population cfr lower upper
#> 1 2 50 4 1.103888 13.46009
mortality_rate(40, 50000)
#> deaths population mortality per 10 000 lower upper
#> 1 40 50000 8 5.87591 10.89109
```

In addition, it’s possible to rapidly calculate Case fatality rate from
a linelist, stratified by different groups (e.g. gender):

``` r
library("outbreaks")
case_fatality_rate_df(ebola_sim_clean$linelist,
outcome == "Death",
group = gender,
add_total = TRUE,
mergeCI = TRUE
)
#> Warning: There was 1 warning in `dplyr::mutate()`.
#> ℹ In argument: `gender = forcats::fct_explicit_na(gender, "(Missing)")`.
#> Caused by warning:
#> ! `fct_explicit_na()` was deprecated in forcats 1.0.0.
#> ℹ Please use `fct_na_value_to_level()` instead.
#> ℹ The deprecated feature was likely used in the epikit package.
#> Please report the issue at <https://github.com/R4EPI/epikit/issues>.
#> # A tibble: 3 × 5
#> gender deaths population cfr ci
#> <fct> <int> <int> <dbl> <chr>
#> 1 f 1291 2280 56.6 (54.58-58.64)
#> 2 m 1273 2247 56.7 (54.59-58.69)
#> 3 Total 2564 4527 56.6 (55.19-58.08)
```

## Inline functions

The inline functions make it easier to print estimates with confidence
intervals in reports with the correct number of digits.

- `fmt_ci()` formats confidence intervals from three numbers.
(e.g. `fmt_ci(50, 10, 80)` produces 50.00% (CI 10.00-80.00)
- `fmt_pci()` formats confidence intervals from three fractions,
multiplying by 100 beforehand.

<!--
The `_df` suffixes (`fmt_ci_df()`, `fmt_pci_df()`) will print the confidence
intervals for data stored in data frames. These are designed to work with the
outputs of the rates functions. For example, `fmt_ci_df(attack_rate(10, 50))`
will produce . All of these suffixes will have
three options `e`, `l`, and `u`. These refer to `estimate`, `lower`, and `upper`
column positions or names.
- `fmt_count()` will count a condition in a data frame and present the number
and percent of `TRUE` values. For example, if you wanted to count the number
of women patients from Rokupa hospital, you would write: `fmt_count(ebola_sim_clean$linelist, gender == "f", hospital == "Rokupa Hospital")` and it would produce:
-->

- `fmt_ci()` formats confidence intervals from three numbers.
(e.g. `fmt_ci(50, 10, 80)` produces 50.00% (CI 10.00-80.00)
- `fmt_pci()` formats confidence intervals from three fractions,
multiplying by 100 beforehand.

The `_df` suffixes (`fmt_ci_df()`, `fmt_pci_df()`) will print the
confidence intervals for data stored in data frames. These are designed
to work with the outputs of the rates functions. For example,
`fmt_ci_df(attack_rate(10, 50))` will produce 20.00% (CI 11.24-33.04).
All of these suffixes will have three options `e`, `l`, and `u`. These
refer to `estimate`, `lower`, and `upper` column positions or names.

- `fmt_count()` will count a condition in a data frame and present the
number and percent of `TRUE` values. For example, if you wanted to
count the number of women patients from Rokupa hospital, you would
write:
`fmt_count(ebola_sim_clean$linelist, gender == "f", hospital == "Rokupa Hospital")`
and it would produce: 210 (3.6%)

## Confidence interval manipulation

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5 changes: 2 additions & 3 deletions man/dots_to_charlist.Rd

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10 changes: 5 additions & 5 deletions man/epikit-package.Rd

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2 changes: 1 addition & 1 deletion man/rmdhunks/introduction.Rmd
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The goal of {epikit} is to provide miscellaneous functions for applied epidemiologists.
This is a product of the R4EPIs project; learn more at <https://r4epis.netlify.com>.
This is a product of the R4EPIs project; learn more at <https://r4epis.netlify.app/>.

## Installation

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