Complete CRAN checks for submission

.Rbuildignore

@@ -12,4 +12,5 @@
 ^docs$
 ^pkgdown$
 ^touchstone$
+^cran-comments\.md$
 ^paper$

DESCRIPTION

@@ -1,10 +1,10 @@
 Package: conmat
-Title: Builds contact matrices using GAMs and population data
+Title: Builds Contact Matrices using GAMs and Population Data
 Version: 0.0.2.9000
 Authors@R: c(
       person(given = "Nicholas",
              family = "Tierney",
-             role = c("aut", "cre"),
+             role = c("aut", "cre", "cph"),
              email = "[email protected]",
              comment = c(ORCID = "https://orcid.org/0000-0003-1460-8722")),
       person(given = "Nick",
@@ -17,6 +17,11 @@ Authors@R: c(
              role = c("aut"),
              email = "[email protected]",
              comment = c(ORCID = "https://orcid.org/0000-0002-6982-5989")),
+     person(given = "Chitra",
+             family = "Saraswati",
+             role = c("aut"),
+             email = "[email protected]",
+             comment = c(ORCID = "https://orcid.org/0000-0002-8159-0414")),
       person(given = "Michael",
              family = "Lydeamore",
              role = "aut",
@@ -71,3 +76,5 @@ Imports:
     english,
     waldo,
     stringr
+URL: https://github.com/idem-lab/conmat
+BugReports: https://github.com/idem-lab/conmat/issues

NAMESPACE

@@ -34,6 +34,8 @@ S3method(get_age_population_function,data.frame)
 S3method(population_label,conmat_population)
 S3method(population_label,default)
 S3method(predictions_to_matrix,predicted_contacts)
+S3method(prepare_population_for_modelling,conmat_population)
+S3method(prepare_population_for_modelling,data.frame)
 S3method(print,conmat_age_matrix)
 S3method(print,conmat_population)
 S3method(print,conmat_setting_prediction_matrix)

NEWS.md

@@ -9,9 +9,9 @@
   * `transmission_probability_matrix()` for creating new transmission probability
   matrices
 
-* there is now a print method for age group information in setting matrices - [#139](https://github.com/njtierney/conmat/issues/139)
+* there is now a print method for age group information in setting matrices - [#139](https://github.com/idem-lab/conmat/issues/139)
 
-* improved age break checking [#138](https://github.com/njtierney/conmat/issues/138)
+* improved age break checking [#138](https://github.com/idem-lab/conmat/issues/138)
 
 * extended `add_school_work_participation()`, `add_modelling_features()`, `fit_single_contact_model()`, `fit_setting_contacts()`, `estimate_setting_contacts()` to use different school and work demographics arguments. (#82 and #15, resolved by #153).
 
@@ -53,14 +53,14 @@
 
 * Added a `NEWS.md` file to track changes to the package.
 * Decouple prediction and estimation of models with `fit_setting_contacts` to 
-  fit models, and `predict_setting_contacts` to predict. Fixes [#7](https://github.com/njtierney/conmat/issues/7)
-* Implement parallelisation with `furrr`. Resolves [#31](https://github.com/njtierney/conmat/issues/31)
+  fit models, and `predict_setting_contacts` to predict. Fixes [#7](https://github.com/idem-lab/conmat/issues/7)
+* Implement parallelisation with `furrr`. Resolves [#31](https://github.com/idem-lab/conmat/issues/31)
 * Change argument of `fit_setting_contacts` from `survey_population` to just `population`
-* Reduce vignette size, closes [#28](https://github.com/njtierney/conmat/issues/28)
-* Add transmission probability data from Eyre et al., closes [#39](https://github.com/njtierney/conmat/issues/39)
-* Add household adjustment - [#41](https://github.com/njtierney/conmat/issues/41)
+* Reduce vignette size, closes [#28](https://github.com/idem-lab/conmat/issues/28)
+* Add transmission probability data from Eyre et al., closes [#39](https://github.com/idem-lab/conmat/issues/39)
+* Add household adjustment - [#41](https://github.com/idem-lab/conmat/issues/41)
 * Added setting weights, related to #44 (but no longer Eyre weights)
-* Added `apply_vaccination` to take in vaccination rates of ages and apply to contact matrices [#40](https://github.com/njtierney/conmat/issues/40)
+* Added `apply_vaccination` to take in vaccination rates of ages and apply to contact matrices [#40](https://github.com/idem-lab/conmat/issues/40)
 * Data from `get_polymod_population` has been revised as a result of the [socialmixr package](https://github.com/epiforecasts/socialmixr/blob/main/NEWS.md) being updated to version 0.2.0, where the world population data has been updated to 2017 by switching from the wpp2015 to wpp2017 package. We have explored the new data and found it to be very similar and should not introduce any errant errors. See the exploration [here](https://gist.github.com/njtierney/4862fa73abab97093d779fa7f2904d11).
 * Added new print methods for: `conmat_setting_prediction_matrix`, `conmat_prediction_matrix`, `ngm_setting_matrix`, `setting_contact_model`, `setting_vaccination_matrix`, and `setting_data`, see #116. Main change is that list objects don't return the entire list and output but a summary of the list contents and details on what that object contains.
 * Added a new S3 method for `conmat_population` to avoid fragile use of the `lower.age.limit` variable name. This resolves #77.

R/add_population_age_to.R

@@ -16,7 +16,8 @@
 #'  `conmat_population` object, which specifies the `age` and `population`
 #'  columns. But it can optionally be any data frame with columns,
 #'  `lower.age.limit`, and `population`.
-#' @return data frame
+#' @return data frame of `contact_data` with the number of intergenerational
+#' mixing contacts added.
 #' @examples
 #' age_min <- 10
 #' age_max <- 15

R/data_abs_employ_age_lga.R

@@ -16,7 +16,7 @@
 #'   \item{total}{sum of these totals...or thereabouts??}
 #' }
 #' @note still need to finalise these columns
-#' @source ABS.stat \url{https://stat.data.abs.gov.au/Index.aspx?} LABOUR >
-#'   Employment and Unemployment > Labour force status >
+#' @source ABS.stat \url{https://www.abs.gov.au/statistics} LABOUR >
+#'   Employment and Unemployment > Labour force, Australia >
 #'   Census 2016, G43 labour status by age and sex (LGA)
 "abs_employ_age_lga"

R/data_abs_household_lga.R

@@ -16,6 +16,6 @@
 #'   \item{n_households}{number of households with that number of people}
 #' }
 #' @note still need to clean this
-#' @source  \url{https://stat.data.abs.gov.au/Index.aspx?Datasetcode=ABS_FAMILY_PROJ}
+#' @source  \url{https://www.abs.gov.au/statistics}
 #' (downloaded the CSV) PEOPLE > People and Communities > Household Composition > Census 2016, T23 Household Composition By Number Of Persons Usually Resident (LGA)
 "abs_household_lga"

R/generate-ngm.R

@@ -44,6 +44,7 @@
 #'   for more detail.
 #' @param ... extra arguments, currently not used
 #' @name generate_ngm
+#' @return A next generation matrix, containing the rates of contact between two age groups.
 #' @examples
 #' \dontrun{
 #' perth <- abs_age_lga("Perth (C)")

R/get-age-population-function-internals.R

@@ -8,12 +8,16 @@
 #' @author njtierney
 #' @keywords internal
 #' @name prepare_population_for_modelling
+#' @examples
+#' prepare_population_for_modelling(get_polymod_population())
+#' 
 #' @export
 prepare_population_for_modelling <- function(data, ...) {
   UseMethod("prepare_population_for_modelling")
 }
 
 #' @rdname prepare_population_for_modelling
+#' @export
 prepare_population_for_modelling.conmat_population <- function(data, ...) {
   age_col <- age(data)
   pop_col <- population(data)
@@ -58,6 +62,7 @@ prepare_population_for_modelling.conmat_population <- function(data, ...) {
 #' @param age_col column of ages
 #' @param pop_col column of population,
 #' @param ... extra arguments
+#' @export
 prepare_population_for_modelling.data.frame <- function(data = data,
                                                         age_col = age_col,
                                                         pop_col = pop_col,

R/get_polymod_per_capita_household_size.R

@@ -5,6 +5,8 @@
 #'
 #' @return number, 3.248971
 #' @author Nicholas Tierney
+#' @examples
+#' get_polymod_per_capita_household_size()
 #' @export
 get_polymod_per_capita_household_size <- function() {
   mean(socialmixr::polymod$participants$hh_size)

R/utils.R

@@ -226,25 +226,6 @@ ungroup_age_breaks <- function(x) {
     unique() %>%
     sort()
 }
-#
-# group_age_breaks(1:10, pad_inf = FALSE)
-# group_age_breaks(1:10, pad_inf = FALSE) %>% ungroup_age_breaks()
-# group_age_breaks(1:10, pad_inf = TRUE)
-# group_age_breaks(1:10, pad_inf = TRUE) %>% ungroup_age_breaks()
-#
-# group_age_breaks(c(1:10, Inf), pad_inf = TRUE)
-# group_age_breaks(c(1:10, Inf), pad_inf = TRUE) %>% ungroup_age_breaks()
-#
-# group_age_breaks(c(1:10, Inf), pad_inf = FALSE)
-# group_age_breaks(c(1:10, Inf), pad_inf = FALSE) %>% ungroup_age_breaks()
-#
-# group_age_breaks(age_breaks_0_80_plus)
-# group_age_breaks(1:10, pad_inf = FALSE)
-# group_age_breaks(1:9, pad_inf = FALSE)
-# group_age_breaks(1:8, pad_inf = FALSE)
-# group_age_breaks(1:10)
-# group_age_breaks(1:9)
-# group_age_breaks(1:8)
 
 all_matrix <- function(x) {
   all(vapply(
@@ -300,8 +281,6 @@ set_age_breaks_matrices <- function(list_matrix, age_breaks) {
   )
 }
 
-# age_breaks(perth_contact_0_75)
-
 remove_inf <- function(x) {
   x_inf <- is.infinite(x)
   if (!any(x_inf)) {

README.Rmd

@@ -17,7 +17,7 @@ knitr::opts_chunk$set(
 
 <!-- badges: start -->
 [![R-CMD-check](https://github.com/idem-lab/conmat/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/idem-lab/conmat/actions/workflows/R-CMD-check.yaml)
-[![Codecov test coverage](https://codecov.io/gh/idem-lab/conmat/branch/master/graph/badge.svg)](https://codecov.io/gh/idem-lab/conmat?branch=master)
+[![Codecov test coverage](https://codecov.io/gh/idem-lab/conmat/branch/master/graph/badge.svg)](https://app.codecov.io/gh/idem-lab/conmat?branch=master)
 <!-- badges: end -->
 
 The goal of conmat is to make it easy to generate synthetic contact matrices for a given age population.
@@ -71,6 +71,12 @@ We need methods that allow for flexibly creating synthetic contact matrices for
 
 ## Installation
 
+You can install the stable version from CRAN with:
+
+```r
+install.packages("conmat")
+```
+
 You can install the development version with:
 
 ```r

README.md

@@ -7,7 +7,7 @@
 
 [![R-CMD-check](https://github.com/idem-lab/conmat/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/idem-lab/conmat/actions/workflows/R-CMD-check.yaml)
 [![Codecov test
-coverage](https://codecov.io/gh/idem-lab/conmat/branch/master/graph/badge.svg)](https://codecov.io/gh/idem-lab/conmat?branch=master)
+coverage](https://codecov.io/gh/idem-lab/conmat/branch/master/graph/badge.svg)](https://app.codecov.io/gh/idem-lab/conmat?branch=master)
 <!-- badges: end -->
 
 The goal of conmat is to make it easy to generate synthetic contact
@@ -59,6 +59,12 @@ representation of community infection in many regions.
 
 ## Installation
 
+You can install the stable version from CRAN with:
+
+``` r
+install.packages("conmat")
+```
+
 You can install the development version with:
 
 ``` r
@@ -127,6 +133,8 @@ contact_model <- fit_single_contact_model(
   contact_data = polymod_contact_data,
   population = polymod_survey_data
 )
+#> Warning in bgam.fit(G, mf, chunk.size, gp, scale, gamma, method = method, :
+#> fitted rates numerically 0 occurred
 ```
 
 This fits a generalised additive model (GAM), predicting the contact
@@ -145,9 +153,9 @@ contact_model
 #>     school_probability + work_probability + offset(log_contactable_population)
 #> 
 #> Estimated degrees of freedom:
-#> 1.85 3.95 3.82 7.10 7.59 4.77  total = 32.09 
+#> 1.01 4.33 4.24 7.03 7.58 4.75  total = 31.94 
 #> 
-#> fREML score: 24429.55     rank: 55/57
+#> fREML score: 24021.47     rank: 55/57
 ```
 
 We can use this contact model to then predict the contact rate in a new
@@ -201,16 +209,16 @@ synthetic_contact_fairfield
 #> # A tibble: 324 × 3
 #>    age_group_from age_group_to contacts
 #>    <fct>          <fct>           <dbl>
-#>  1 [0,5)          [0,5)         0.00281
-#>  2 [0,5)          [5,10)        0.00318
-#>  3 [0,5)          [10,15)       0.00345
-#>  4 [0,5)          [15,20)       0.00571
-#>  5 [0,5)          [20,25)       0.0133 
-#>  6 [0,5)          [25,30)       0.0261 
-#>  7 [0,5)          [30,35)       0.0356 
-#>  8 [0,5)          [35,40)       0.0372 
-#>  9 [0,5)          [40,45)       0.0349 
-#> 10 [0,5)          [45,50)       0.0317 
+#>  1 [0,5)          [0,5)         0.00286
+#>  2 [0,5)          [5,10)        0.00309
+#>  3 [0,5)          [10,15)       0.00330
+#>  4 [0,5)          [15,20)       0.00562
+#>  5 [0,5)          [20,25)       0.0135 
+#>  6 [0,5)          [25,30)       0.0266 
+#>  7 [0,5)          [30,35)       0.0358 
+#>  8 [0,5)          [35,40)       0.0370 
+#>  9 [0,5)          [40,45)       0.0348 
+#> 10 [0,5)          [45,50)       0.0318 
 #> # ℹ 314 more rows
 ```
 

cran-comments.md

@@ -0,0 +1,5 @@
+## R CMD check results
+
+0 errors | 0 warnings | 1 note
+
+* This is a new release.