Full package review for epichains v0.1.0 release

DESCRIPTION

@@ -1,7 +1,7 @@
 Package: epichains
 Title: Simulating and Analysing Transmission Chain Statistics Using Branching Process
     Models
-Version: 0.1.0
+Version: 0.0.0.9999
 Authors@R: c(
     person("James M.", "Azam", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "https://orcid.org/0000-0001-5782-7330")),
@@ -26,24 +26,19 @@ Depends:
 Imports: 
     checkmate,
     stats,
+    truncdist,
     utils
 Suggests:
     bookdown,
-    covr,
     dplyr,
-    epiparameter,
     ggplot2,
     knitr,
     lubridate,
     rmarkdown,
     spelling,
-    testthat,
-    truncdist,
-    usethis
+    testthat
 VignetteBuilder:
     knitr
-Remotes:
-    github::epiverse-trace/epiparameter
 Config/Needs/website:epiverse-trace/epiversetheme
 Config/testthat/edition: 3
 Encoding: UTF-8

NEWS.md

@@ -1,48 +1,31 @@
-# epichains 0.1.9999
+# epichains 0.0.9999
 
-## Documentation
-* A vignette outlining how to simulate interventions has been added
+* `epichains` is a re-implementation of `bpmodels` with a focus on providing
+a dedicated class of data structures for easy manipulation and interoperability
+with other new tools in the Epiverse and existing ecosystem.
 
-# epichains 0.1.0
+## Documentation
 
-## Package name change
+* A vignette outlining how to simulate interventions has been added.
 
-* `epichains` is a re-implementation of `bpmodels` with a focus on providing
-  a dedicated class of data structures for easy manipulation and interoperability
-  with other new tools in the pipeline.
+## Functions
 
-### Functions
-
-* `simulate_tree()`: simulate transmission trees from a given number of chains.
+* `simulate_tree()`: simulate transmission trees from a given number of initial
+cases.
 * `simulate_tree_from_pop()`: simulate transmission trees from a given 
-  population size and initial immunity.
+population size and initial immunity.
 * `simulate_summary()`: simulate a vector of observed transmission chains 
-  sizes/lengths from a given number of chains.
+sizes/lengths from a given number of chains.
 * `likelihood()`: estimate the likelihood/loglikelihood of observing
-  chains of given sizes/lengths.
-
-### Classes
-
-* An `epichains` class, which inherits from `data.frame` with attributes for
-  tracking:
-  - `chains`: number of chains simulated
-  - `chain_type`:
-    - `chains_tree`, if returned from `simulate_tree()` or 
-      `simulate_tree_from_pop()`
-    - `chains_summary`, if returned from `simulate_summary()`.
-  - `track_pop`: whether the susceptible population is tracked or not.
-* An `epichains_aggregate_df` class, which inherits from `data.frame` with
-  attributes for tracking:
-  - `chain_type`: as defined above, and
-  - `aggregated_over`: the variable(s) over which aggregation was done: "time",
-  "generation" or "both". Useful for easy plotting with the `plot` method (see
-  methods section below).
-
-### Methods
-
-* `print()`
-* `summary()`
-* `aggregate()`
+chains of given sizes/lengths.
+
+## Methods
+
+* Use `print()` and `summary()` to obtain more insightful results compared to
+previously in {bpmodels}.
+* Use `aggregate()` to aggregate results from `simulate_tree()` and
+`simulate_tree_from_pop()` into cases by "generation" and "time" (if time is
+simulated)
 
 # bpmodels 0.2.1
 

R/borel.r

@@ -14,7 +14,6 @@ dborel <- function(x, mu, log = FALSE) {
     mu, lower = 0, finite = TRUE, na.ok = FALSE
   )
 
-  if (x < 1) stop("'x' must be greater than 0")
   ld <- -mu * x + (x - 1) * log(mu * x) - lgamma(x + 1)
   if (!log) ld <- exp(ld)
   return(ld)

R/checks.R

@@ -7,11 +7,10 @@
 #' @keywords internal
 check_offspring_valid <- function(offspring_dist) {
   if (!checkmate::test_string(offspring_dist)) {
-    stop(sprintf(
-      "%s %s",
+    stop(
       "'offspring_dist' must be specified as a character string.",
       "Did you forget to enclose it in quotes?"
-    ))
+    )
   }
 }
 
@@ -37,11 +36,10 @@ check_offspring_func_valid <- function(roffspring_name) {
 #' @keywords internal
 check_generation_time_valid <- function(generation_time) {
   if (!checkmate::test_function(generation_time, nargs = 1)) {
-    stop(sprintf(
-      "%s %s",
+    stop(
       "The `generation_time` argument must be a function",
       "(see details in ?simulate_tree)."
-    ))
+    )
   }
   x <- generation_time(10)
   if (!checkmate::test_numeric(x, len = 10)) {

R/epichains.R

@@ -181,7 +181,7 @@ print.epichains_tree <- function(x, ...) {
 #' Print an `<epichains_summary>` object
 #'
 #' @param x An `<epichains_summary>` object.
-#' @param ... Other parameters passed to `print()`.
+#' @param ... ignored.
 #' @return Invisibly returns an `<epichains_summary>`. Called for
 #' side-effects.
 #' @author James M. Azam
@@ -193,7 +193,7 @@ print.epichains_summary <- function(x, ...) {
 #' Format method for `<epichains_tree>` class
 #'
 #' @param x An `<epichains_tree>` object
-#' @param ... further arguments passed to or from other methods
+#' @param ... ignored
 #' @return Invisibly returns an `<epichains_tree>`.
 #' Called for printing side-effects.
 #' @author James M. Azam
@@ -246,7 +246,7 @@ format.epichains_tree <- function(x, ...) {
 #' Format method for `<epichains_summary>` class
 #'
 #' @param x An `<epichains_summary>` object
-#' @param ... further arguments passed to or from other methods
+#' @param ... ignored
 #' @return Invisibly returns an `<epichains_summary>`. Called for printing
 #' side-effects.
 #' @author James M. Azam
@@ -289,7 +289,7 @@ format.epichains_summary <- function(x, ...) {
 #' Summary method for `<epichains_tree>` class
 #'
 #' @param object An `<epichains_tree>` object
-#' @param ... further arguments passed to or from other methods
+#' @param ... ignored
 #'
 #' @return List of summaries
 #' @author James M. Azam
@@ -323,7 +323,7 @@ summary.epichains_tree <- function(object, ...) {
 #' Summary method for `<epichains_summary>` class
 #'
 #' @param object An `<epichains_summary>` object
-#' @param ... further arguments passed to or from other methods
+#' @param ... ignored
 #'
 #' @return List of summaries
 #' @author James M. Azam
@@ -458,7 +458,7 @@ tail.epichains_tree <- function(x, ...) {
 #' @param x An `<epichains_tree>` object.
 #' @param by The variable to aggregate by. Options include
 #' "time" and "generation".
-#' @param ... Other arguments passed to aggregate.
+#' @param ... ignored.
 #' @importFrom stats aggregate
 #' @return A `<data.frame>` object of cases by `by`.
 #' @author James M. Azam

R/likelihood.R

@@ -140,16 +140,17 @@ likelihood <- function(chains, statistic = c("size", "length"), offspring_dist,
   if (!missing(exclude)) {
     likelihoods <- likelihoods - log(-expm1(sum(likelihoods[exclude])))
     likelihoods[exclude] <- -Inf
-
     stat_rep_list <- lapply(stat_rep_list, function(y) {
       y[!(y %in% exclude)]
-    })
+    }
+    )
   }
 
   ## assign likelihoods
   chains_likelihood <- lapply(stat_rep_list, function(sx) {
     likelihoods[sx[!(sx %in% exclude)]]
-  })
+  }
+  )
 
   ## if individual == FALSE, return the joint log-likelihood
   ## (sum of the log-likelihoods)

R/simulate.r

@@ -45,9 +45,7 @@
 #'
 #' ## Specifying `generation_time`
 #'
-#' `generation_time` must be specified as a named or
-#' [anonymous/inline/unnamed function](https://en.wikipedia.org/wiki/Anonymous_function#R)
-#' with one argument.
+#' `generation_time` must be specified as a function with one argument.
 #'
 #' For example, assuming we want to specify the generation time
 #' as a random log-normally distributed variable with
@@ -118,6 +116,8 @@ simulate_tree <- function(ntrees, statistic = c("size", "length"),
 
   if (!missing(generation_time)) {
     check_generation_time_valid(generation_time)
+  } else if (!missing(tf)) {
+    stop("If `tf` is specified, `generation_time` must be specified too.")
   }
   checkmate::assert_numeric(
     t0, lower = 0, finite = TRUE
@@ -129,12 +129,6 @@ simulate_tree <- function(ntrees, statistic = c("size", "length"),
   # Gather offspring distribution parameters
   pars <- list(...)
 
-  if (!missing(generation_time)) {
-    check_generation_time_valid(generation_time)
-  } else if (!missing(tf)) {
-    stop("If `tf` is specified, `generation_time` must be specified too.")
-  }
-
   # Initialisations
   stat_track <- rep(1, ntrees) # track length or size (depending on `statistic`)
   n_offspring <- rep(1, ntrees) # current number of offspring
@@ -453,14 +447,13 @@ simulate_tree_from_pop <- function(pop,
     }
   } else if (offspring_dist == "nbinom") {
     if (is.null(pars$size)) {
-      stop(sprintf("%s", "'size' must be specified."))
+      stop("'size' must be specified.")
     } else if (pars$size <= 1) { ## dispersion coefficient
-      stop(sprintf(
-        "%s %s %s",
+      stop(
         "Offspring distribution 'nbinom' requires",
         "argument 'size' > 1.",
         "Use 'pois' if there is no overdispersion."
-      ))
+      )
     }
     ## get distribution params from mean and dispersion
     offspring_func <- function(n, susc) {

README.Rmd

@@ -22,11 +22,9 @@ knitr::opts_chunk$set(
 # _{{ packagename }}_: Methods for simulating and analysing the size and length of transmission chains from branching process models <img src="man/figures/logo.svg" align="right" height="130" />
 
 <!-- badges: start -->
-![GitHub R package version](https://img.shields.io/github/r-package/v/epiverse-trace/epichains)
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![R-CMD-check](https://github.com/epiverse-trace/epichains/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/epiverse-trace/epichains/actions/workflows/R-CMD-check.yaml)
 [![codecov](https://codecov.io/github/epiverse-trace/epichains/branch/main/graphs/badge.svg)](https://codecov.io/github/epiverse-trace/epichains)
-![GitHub contributors](https://img.shields.io/github/contributors/epiverse-trace/epichains)
-[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![Lifecycle:
 experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
 <!-- badges: end -->
@@ -41,9 +39,9 @@ models are often used in infectious disease epidemiology, where the chains repre
 transmission, and the offspring distribution represents the distribution of 
 secondary infections caused by an infected individual. 
 
-_{{ packagename }}_ re-implements [bpmodels]("https://github.com/epiverse-trace/bpmodels/")
+_{{ packagename }}_ re-implements [bpmodels](https://github.com/epiverse-trace/bpmodels/)
 by providing bespoke functions and data structures that allow easy
-manipulation and interoperability with other Epiverse-TRACE packages, for example, [superspreading]("https://github.com/epiverse-trace/superspreading/") and [epiparameter]("https://github.com/epiverse-trace/epiparameter/"), and potentially some existing packages for handling transmission chains, for example, [epicontacts](https://github.com/reconhub/epicontacts).
+manipulation and interoperability with other Epiverse-TRACE packages, for example, [superspreading](https://github.com/epiverse-trace/superspreading/) and [epiparameter](https://github.com/epiverse-trace/epiparameter/), and potentially some existing packages for handling transmission chains, for example, [epicontacts](https://github.com/reconhub/epicontacts).
 
 _{{ packagename }}_ is developed at the [Centre for the Mathematical Modelling of Infectious Diseases](https://www.lshtm.ac.uk/research/centres/centre-mathematical-modelling-infectious-diseases) at the London School of Hygiene and Tropical Medicine as part of the [Epiverse Initiative](https://data.org/initiatives/epiverse/).
 

README.md

@@ -9,14 +9,10 @@
 
 <!-- badges: start -->
 
-![GitHub R package
-version](https://img.shields.io/github/r-package/v/epiverse-trace/epichains)
-[![R-CMD-check](https://github.com/epiverse-trace/epichains/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/epiverse-trace/epichains/actions/workflows/R-CMD-check.yaml)
-[![codecov](https://codecov.io/github/epiverse-trace/epichains/branch/main/graphs/badge.svg)](https://codecov.io/github/epiverse-trace/epichains)
-![GitHub
-contributors](https://img.shields.io/github/contributors/epiverse-trace/epichains)
 [![License:
 MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+[![R-CMD-check](https://github.com/epiverse-trace/epichains/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/epiverse-trace/epichains/actions/workflows/R-CMD-check.yaml)
+[![codecov](https://codecov.io/github/epiverse-trace/epichains/branch/main/graphs/badge.svg)](https://codecov.io/github/epiverse-trace/epichains)
 [![Lifecycle:
 experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)
 <!-- badges: end -->
@@ -29,15 +25,13 @@ distribution represents the distribution of secondary infections caused
 by an infected individual.
 
 *epichains* re-implements
-[bpmodels](%22https://github.com/epiverse-trace/bpmodels/%22) by
-providing bespoke functions and data structures that allow easy
-manipulation and interoperability with other Epiverse-TRACE packages,
-for example,
-[superspreading](%22https://github.com/epiverse-trace/superspreading/%22)
-and
-[epiparameter](%22https://github.com/epiverse-trace/epiparameter/%22),
-and potentially some existing packages for handling transmission chains,
-for example, [epicontacts](https://github.com/reconhub/epicontacts).
+[bpmodels](https://github.com/epiverse-trace/bpmodels/) by providing
+bespoke functions and data structures that allow easy manipulation and
+interoperability with other Epiverse-TRACE packages, for example,
+[superspreading](https://github.com/epiverse-trace/superspreading/) and
+[epiparameter](https://github.com/epiverse-trace/epiparameter/), and
+potentially some existing packages for handling transmission chains, for
+example, [epicontacts](https://github.com/reconhub/epicontacts).
 
 *epichains* is developed at the [Centre for the Mathematical Modelling
 of Infectious
@@ -133,18 +127,23 @@ By contributing to this project, you agree to abide by its terms.
 
 ``` r
 citation("epichains")
-#> To cite package epichains in publications use:
+#> To cite package 'epichains' in publications use:
 #> 
-#>   Sebastian Funk, Flavio Finger, and James M. Azam (2023). epichains:
-#>   Analysing transmission chain statistics using branching process
-#>   models, website: https://github.com/epiverse-trace/epichains/
+#>   Azam J, Finger F, Funk S (2023). _epichains: Simulating and Analysing
+#>   Transmission Chain Statistics Using Branching Process Models_. R
+#>   package version 0.0.0.9999,
+#>   https://epiverse-trace.github.io/epichains/,
+#>   <https://github.com/epiverse-trace/epichains>.
 #> 
 #> A BibTeX entry for LaTeX users is
 #> 
 #>   @Manual{,
-#>     title = {epichains: Analysing transmission chain statistics using branching process models},
-#>     author = {{Sebastian Funk} and {Flavio Finger} and {James M. Azam}},
+#>     title = {epichains: Simulating and Analysing Transmission Chain Statistics Using
+#> Branching Process Models},
+#>     author = {James M. Azam and Flavio Finger and Sebastian Funk},
 #>     year = {2023},
-#>     url = {https://github.com/epiverse-trace/epichains/},
+#>     note = {R package version 0.0.0.9999, 
+#> https://epiverse-trace.github.io/epichains/},
+#>     url = {https://github.com/epiverse-trace/epichains},
 #>   }
 ```

data-raw/covid19_sa.R

@@ -15,8 +15,6 @@ covid19_sa <- covid19_sa %>%
   select(date) %>%
   mutate(date = lubridate::dmy(date)) %>%
   filter(date <= min(date) + lubridate::days(15)) %>%
-  group_by(date) %>%
-  summarise(cases = n()) %>%
-  ungroup()
+  count(date, name = "cases")
 
 use_data(covid19_sa, overwrite = TRUE)