From 6d11709d30acdcf43138731d0bc08f6c85e032be Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 17:38:14 +0100 Subject: [PATCH 01/11] Subsetting incubation period directly using parameter_type column instead of grepl --- vignettes/articles/data_from_epireview.Rmd | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index 8cf14a52e..3f223abec 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -43,16 +43,12 @@ We will start by just using the epidemiological parameter table to convert infor marburg_params <- marburg_data$params ``` -Given that currently only delay distributions are supported for the conversion (this feature is still under active development) we will filter to only include these. +Out of these parameters, subset the data to only keep those rows that contain incubation periods for Marburg. ```{r, subset-marburg-params} -delay_dist_rows <- grepl( - pattern = "Human delay", - x = marburg_params$parameter_type, - fixed = TRUE -) -marburg_params <- marburg_params[delay_dist_rows, ] -marburg_params +marburg_incubation_period <- marburg_params[ + marburg_params$parameter_type_short=="incubation_period",] +marburg_incubation_period ``` We will select the second entry, which is an incubation period, to use as the first example: From 4247447b0dd2f6455dab05e108d1cd98065a8cd4 Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 17:39:24 +0100 Subject: [PATCH 02/11] Renaming marburg entry to match previous direct selection of incubation periods --- vignettes/articles/data_from_epireview.Rmd | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index 3f223abec..ead800942 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -51,10 +51,10 @@ marburg_incubation_period <- marburg_params[ marburg_incubation_period ``` -We will select the second entry, which is an incubation period, to use as the first example: +We will select the second entry to use as the first example: ```{r, select-marburg-entry} -marburg_incub <- marburg_params[2, ] +marburg_incub <- marburg_incubation_period[2, ] marburg_incub ``` From ccc0e67e9c9ac936e20d08a827d0563bb28847c5 Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 17:50:56 +0100 Subject: [PATCH 03/11] Adding step to visualise multi row entries --- vignettes/articles/data_from_epireview.Rmd | 1 + 1 file changed, 1 insertion(+) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index ead800942..caa1303a5 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -137,6 +137,7 @@ multi_row_ids <- marburg_params$id[multi_row_entries] ```{r, subset-multi-row-entries} multi_row_marburg_params <- marburg_params[marburg_params$id %in% multi_row_ids, ] +multi_row_marburg_params ``` In this case there are two studies for Marburg with more than one entry (row) in the {epireview} database. Out of these studies, we select the first two rows, which contain the mean and standard deviation. From b996d551e3d52e8cebb04db3c4589efe21753d5f Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 17:51:58 +0100 Subject: [PATCH 04/11] Adding text about checking entries manually and explanation from epireview team --- vignettes/articles/data_from_epireview.Rmd | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index caa1303a5..3ea2d865e 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -146,7 +146,10 @@ In this case there are two studies for Marburg with more than one entry (row) in multi_row_marburg_params$parameter_value_type ``` -We use the first two rows of this subset table, which are the mean and standard deviation for the generation time of Marburg disease. This step should be verified manually to ensure that the entries that have been selected are indeed multiple rows for the same reported epidemiological parameter. +We select the first two rows of this subset table, which are the mean and standard deviation for the generation time of Marburg disease. This step should be verified manually to ensure that the entries that have been selected are indeed multiple rows for the same reported epidemiological parameter. + +In this case, we know that the mean and standard deviation from the chosen rows correspond to the same estimation process by having read the corresponding article. However, there is currently no identifiers on the {epireview} `params` database for Marburg, Ebola or Lassa to directly identify which of the two rows with mean values correspond to the standard deviation. The {epireview} team are currently working on rectifying this issue. **Therefore, we encourage readers to manually verify their data subsets, to ensure that the entries that have been selected are indeed multiple rows for the same reported epidemiological parameter.** +* For future {epireview} pathogens (excluding SARS) mean and standard deviation estimates that match will form one row in the params database. Current software development at {epireview} is working on ensuring compatibility between these formats. ```{r, subset-multi-row-marburg-entry} marburg_gt <- multi_row_marburg_params[1:2, ] From 10fed1bb462f7760042e40ea07e29ead630b7685 Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 18:03:59 +0100 Subject: [PATCH 05/11] Filtering generation time entries using their ids instead of row numbers --- vignettes/articles/data_from_epireview.Rmd | 5 ++++- 1 file changed, 4 insertions(+), 1 deletion(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index 3ea2d865e..dd015ff55 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -152,7 +152,10 @@ In this case, we know that the mean and standard deviation from the chosen rows * For future {epireview} pathogens (excluding SARS) mean and standard deviation estimates that match will form one row in the params database. Current software development at {epireview} is working on ensuring compatibility between these formats. ```{r, subset-multi-row-marburg-entry} -marburg_gt <- multi_row_marburg_params[1:2, ] +marburg_gt <- multi_row_marburg_params[ + multi_row_marburg_params$parameter_data_id %in% + c("056a8d6b5f9aee3622d3bd8b715d4296" , "ce3976e2e15df3f6fb92f6deb2db2a29"),] +marburg_gt ``` We can now convert this to an ``. From d290c3939fa12dedb984ab6ba867686ebf98cc48 Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 18:05:34 +0100 Subject: [PATCH 06/11] Subsetting parameter table directly to include only serial intervals --- vignettes/articles/data_from_epireview.Rmd | 12 ++++-------- 1 file changed, 4 insertions(+), 8 deletions(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index dd015ff55..7a380a26f 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -174,20 +174,16 @@ For this example we will load the Ebola epidemiological parameters from the {epi ebola_data <- load_epidata("ebola") ``` -We will again subset the data to just use the epidemiological parameter table, and subset that table to just the delay distributions. +We will again subset the data to just use the epidemiological parameter table, and select those rows containing a serial interval. ```{r, ebola-params} ebola_params <- ebola_data$params ``` ```{r, subset-ebola-params} -delay_dist_rows <- grepl( - pattern = "Human delay", - x = ebola_params$parameter_type, - fixed = TRUE -) -ebola_delays <- ebola_params[delay_dist_rows, ] -ebola_delays +ebola_si_rows <- ebola_params[ + ebola_params$parameter_type_short=="serial_interval",] +ebola_si_rows ``` We will select the 358th entry, which is a serial interval, as this entry has estimated and reported a Weibull distribution: From ec6a8c7fa837b59efd1bef3c1d7ac207bb84110f Mon Sep 17 00:00:00 2001 From: CarmenTamayo Date: Tue, 20 Aug 2024 18:06:48 +0100 Subject: [PATCH 07/11] Selecting correct row using parameter id instead of row number --- vignettes/articles/data_from_epireview.Rmd | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index 7a380a26f..7dc673be4 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -186,10 +186,11 @@ ebola_si_rows <- ebola_params[ ebola_si_rows ``` -We will select the 358th entry, which is a serial interval, as this entry has estimated and reported a Weibull distribution: +We will select the 17th entry, as this entry has estimated and reported a Weibull distribution: ```{r, select-ebola-entry} -ebola_si <- ebola_delays[358, ] +ebola_si <- ebola_si_rows[ + ebola_si_rows$parameter_data_id=="0c3e02f80addfccc1017fa619fba76c5",] ebola_si ``` From 5c07f4712fdebf15b7f5cba7156c020a90ee1320 Mon Sep 17 00:00:00 2001 From: GitHub Action Date: Mon, 7 Oct 2024 16:37:57 +0000 Subject: [PATCH 08/11] Automatic readme update --- README.md | 26 +++++++++++++------------- 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/README.md b/README.md index 033cab84d..e01bd3a49 100644 --- a/README.md +++ b/README.md @@ -55,15 +55,15 @@ To load the library of epidemiological parameters into `R`: ``` r epiparameters <- epiparameter_db() -#> Returning 122 results that match the criteria (99 are parameterised). +#> Returning 125 results that match the criteria (100 are parameterised). #> Use subset to filter by entry variables or single_epiparameter to return a single entry. #> To retrieve the citation for each use the 'get_citation' function epiparameters -#> # List of 122 objects +#> # List of 125 objects #> Number of diseases: 23 #> ❯ Adenovirus ❯ Chikungunya ❯ COVID-19 ❯ Dengue ❯ Ebola Virus Disease ❯ Hantavirus Pulmonary Syndrome ❯ Human Coronavirus ❯ Influenza ❯ Japanese Encephalitis ❯ Marburg Virus Disease ❯ Measles ❯ MERS ❯ Mpox ❯ Parainfluenza ❯ Pneumonic Plague ❯ Rhinovirus ❯ Rift Valley Fever ❯ RSV ❯ SARS ❯ Smallpox ❯ West Nile Fever ❯ Yellow Fever ❯ Zika Virus Disease -#> Number of epi distributions: 12 -#> ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval +#> Number of epi distributions: 13 +#> ❯ case fatality risk ❯ generation time ❯ hospitalisation to death ❯ hospitalisation to discharge ❯ incubation period ❯ notification to death ❯ notification to discharge ❯ offspring distribution ❯ onset to death ❯ onset to discharge ❯ onset to hospitalisation ❯ onset to ventilation ❯ serial interval #> [[1]] #> Disease: Adenovirus #> Pathogen: Adenovirus @@ -75,8 +75,8 @@ epiparameters #> . #> Distribution: lnorm #> Parameters: -#> meanlog: 1.247 -#> sdlog: 0.975 +#> meanlog: 1.723 +#> sdlog: 0.231 #> #> [[2]] #> Disease: Human Coronavirus @@ -89,8 +89,8 @@ epiparameters #> . #> Distribution: lnorm #> Parameters: -#> meanlog: 0.742 -#> sdlog: 0.918 +#> meanlog: 1.163 +#> sdlog: 0.140 #> #> [[3]] #> Disease: SARS @@ -103,10 +103,10 @@ epiparameters #> . #> Distribution: lnorm #> Parameters: -#> meanlog: 0.660 -#> sdlog: 1.205 +#> meanlog: 1.386 +#> sdlog: 0.593 #> -#> # ℹ 119 more elements +#> # ℹ 122 more elements #> # ℹ Use `print(n = ...)` to see more elements. #> # ℹ Use `parameter_tbl()` to see a summary table of the parameters. #> # ℹ Explore database online at: https://epiverse-trace.github.io/epiparameter/articles/database.html @@ -161,7 +161,7 @@ the data, and offers the ability to subset you data by `disease`, ``` r parameter_tbl(epiparameters) #> # Parameter table: -#> # A data frame: 122 × 7 +#> # A data frame: 125 × 7 #> disease pathogen epi_distribution prob_distribution author year sample_size #> #> 1 Adenovi… Adenovi… incubation peri… lnorm Lessl… 2009 14 @@ -174,7 +174,7 @@ parameter_tbl(epiparameters) #> 8 Parainf… Parainf… incubation peri… lnorm Lessl… 2009 11 #> 9 RSV RSV incubation peri… lnorm Lessl… 2009 24 #> 10 Rhinovi… Rhinovi… incubation peri… lnorm Lessl… 2009 28 -#> # ℹ 112 more rows +#> # ℹ 115 more rows parameter_tbl( epiparameters, epi_dist = "onset to hospitalisation" From d07674ec44d594b785e50c45285ed9f00496721e Mon Sep 17 00:00:00 2001 From: Joshua Lambert Date: Tue, 8 Oct 2024 12:09:55 +0100 Subject: [PATCH 09/11] linting data_from_epireview vignette --- vignettes/articles/data_from_epireview.Rmd | 35 ++++++++++++---------- 1 file changed, 20 insertions(+), 15 deletions(-) diff --git a/vignettes/articles/data_from_epireview.Rmd b/vignettes/articles/data_from_epireview.Rmd index 7dc673be4..761a1ef1b 100644 --- a/vignettes/articles/data_from_epireview.Rmd +++ b/vignettes/articles/data_from_epireview.Rmd @@ -47,14 +47,15 @@ Out of these parameters, subset the data to only keep those rows that contain in ```{r, subset-marburg-params} marburg_incubation_period <- marburg_params[ - marburg_params$parameter_type_short=="incubation_period",] + marburg_params$parameter_type_short == "incubation_period", +] marburg_incubation_period ``` -We will select the second entry to use as the first example: +We will select the first entry to use as the first example: ```{r, select-marburg-entry} -marburg_incub <- marburg_incubation_period[2, ] +marburg_incub <- marburg_incubation_period[1, ] marburg_incub ``` @@ -104,7 +105,7 @@ marburg_incub_article <- marburg_articles[article_row, ] marburg_incub_article ``` -Now we can repeat the example of converting to `` as shown above, but this time pass the bibliographic information as well as the epidemiological parameter information to create a full citation. The bibliographic information needs to be passed with the `articles` argument. +Now we can repeat the example of converting to `` as shown above, but this time pass the bibliographic information as well as the epidemiological parameter information to create a full citation. The bibliographic information needs to be passed with the `article` argument. ```{r, convert-to-epiparameter-full-citation} marburg_incub_epiparameter <- as_epiparameter( @@ -119,14 +120,14 @@ marburg_incub_epiparameter$citation ``` ::: {.alert .alert-info} -The `as_epiparameter()` function is an S3 generic. If you are not familiar with S3 object-oriented programming in R, then this detail is not important, however, it does mean that the `articles` argument is not explicitly in the function definition of `as_epiparameter()` (i.e. it will not show up on autocomplete when typing out the function and will not be shown if you read the function help page `?as_epiparameter()`). Instead, the argument is specified as part of the `...` argument. This is because the `articles` argument is only required when converting data from {epireview} into ``, and other data that can be converted to `` objects do not require this argument. +The `as_epiparameter()` function is an S3 generic. If you are not familiar with S3 object-oriented programming in R, then this detail is not important, however, it does mean that the `article` argument is not explicitly in the function definition of `as_epiparameter()` (i.e. it will not show up on autocomplete when typing out the function and will not be shown if you read the function help page `?as_epiparameter()`). Instead, the argument is specified as part of the `...` argument. This is because the `article` argument is only required when converting data from {epireview} into ``, and other data that can be converted to `` objects do not require this argument. ::: ## Multi-row {epireview} entries The way the {epireview} data is stored means that some epidemiological parameter entries require multiple rows. This can be, for example, because they contain two summary statistics (e.g. mean and standard deviation) that are kept on separate rows. In order to create `` objects that contains the full information for each entry multiple rows of the epidemiological parameters table from {epireview} can be given to `as_epiparameter()` to create a single `` object. -We can search which entries in the data have multiple rows by checking if there are duplicated parameter types and IDs. Remember that it is only possible to convert delay distributions into epiparameter objects (i.e. known as _Human delay_ parameter types in {epireview}), which we previously subset in this vignette. +We can search which entries in the data have multiple rows by checking if there are duplicated parameter types and IDs. Remember that it is only possible to convert delay distributions into epiparameter objects (i.e. known as _Human delay_ parameter types in {epireview}). ```{r, check-multi-row-entries} multi_row_entries <- duplicated(marburg_params$parameter_type) & @@ -140,21 +141,23 @@ multi_row_marburg_params <- multi_row_marburg_params ``` -In this case there are two studies for Marburg with more than one entry (row) in the {epireview} database. Out of these studies, we select the first two rows, which contain the mean and standard deviation. +In this case there are two studies for Marburg with more than one entry (row) in the {epireview} database. Out of these studies we select the mean and standard deviation. ```{r, check-multi-row-param-value-type} multi_row_marburg_params$parameter_value_type ``` -We select the first two rows of this subset table, which are the mean and standard deviation for the generation time of Marburg disease. This step should be verified manually to ensure that the entries that have been selected are indeed multiple rows for the same reported epidemiological parameter. +In this case, we know that the mean and standard deviation from the chosen rows correspond to the same estimation process by having read the corresponding article. However, there is currently no identifiers on the {epireview} `params` database for Marburg, Ebola or Lassa to directly identify which of the two rows with mean values correspond to the standard deviation. The {epireview} team are currently working on rectifying this issue. + +***Therefore, we encourage readers to manually verify their data subsets, to ensure that the entries that have been selected are indeed multiple rows for the same reported epidemiological parameter.*** -In this case, we know that the mean and standard deviation from the chosen rows correspond to the same estimation process by having read the corresponding article. However, there is currently no identifiers on the {epireview} `params` database for Marburg, Ebola or Lassa to directly identify which of the two rows with mean values correspond to the standard deviation. The {epireview} team are currently working on rectifying this issue. **Therefore, we encourage readers to manually verify their data subsets, to ensure that the entries that have been selected are indeed multiple rows for the same reported epidemiological parameter.** -* For future {epireview} pathogens (excluding SARS) mean and standard deviation estimates that match will form one row in the params database. Current software development at {epireview} is working on ensuring compatibility between these formats. +* For future {epireview} pathogens (excluding SARS) mean and standard deviation estimates that match will form one row in the `$params` database. Current software development at {epireview} is working on ensuring compatibility between these formats. ```{r, subset-multi-row-marburg-entry} marburg_gt <- multi_row_marburg_params[ multi_row_marburg_params$parameter_data_id %in% - c("056a8d6b5f9aee3622d3bd8b715d4296" , "ce3976e2e15df3f6fb92f6deb2db2a29"),] + c("056a8d6b5f9aee3622d3bd8b715d4296", "ce3976e2e15df3f6fb92f6deb2db2a29"), +] marburg_gt ``` @@ -182,15 +185,17 @@ ebola_params <- ebola_data$params ```{r, subset-ebola-params} ebola_si_rows <- ebola_params[ - ebola_params$parameter_type_short=="serial_interval",] + ebola_params$parameter_type_short == "serial_interval", +] ebola_si_rows ``` -We will select the 17th entry, as this entry has estimated and reported a Weibull distribution: +We will select an entry that has estimated and reported a Weibull distribution: ```{r, select-ebola-entry} ebola_si <- ebola_si_rows[ - ebola_si_rows$parameter_data_id=="0c3e02f80addfccc1017fa619fba76c5",] + ebola_si_rows$parameter_data_id == "0c3e02f80addfccc1017fa619fba76c5", +] ebola_si ``` @@ -254,7 +259,7 @@ is_parameterised(ebola_si_epiparameter) Given that we can convert the mean and standard deviation into parameters of a probability distribution if we assume a distribution form, we can supply this data to `as_epiparameter()`. This uses the parameter conversion functions in {epiparameter} (see `vignette("extract_convert", package = "epiparameter")`). ```{r, convert-to-epiparameter-assumed-prob-dist} -ebola_si_epiparameter <- as_epiparameter(ebola_si, prob_dist = "gamma") +ebola_si_epiparameter <- as_epiparameter(ebola_si, prob_distribution = "gamma") ebola_si_epiparameter is_parameterised(ebola_si_epiparameter) ``` From cc63a752983b5aba76e09a3d2fcaf1e7ef4324a1 Mon Sep 17 00:00:00 2001 From: Joshua Lambert Date: Tue, 8 Oct 2024 12:10:20 +0100 Subject: [PATCH 10/11] update as_epiparameter to use prob_distribution --- R/coercion.R | 8 ++++---- man/as_epiparameter.Rd | 6 +++--- tests/testthat/test-coercion.R | 8 ++++---- 3 files changed, 11 insertions(+), 11 deletions(-) diff --git a/R/coercion.R b/R/coercion.R index 769b92093..47b264e0e 100644 --- a/R/coercion.R +++ b/R/coercion.R @@ -99,9 +99,9 @@ as.data.frame.multi_epiparameter <- function(x, ...) { #' as it will be matched by name by `$`. #' #' To specify a probability distribution pass a `character` string to the -#' function via the `...` argument. The argument should be called `prob_dist`. -#' For example, to specify a gamma distribution: -#' `as_epiparameter(x, prob_dist = "gamma")`. +#' function via the `...` argument. The argument should be called +#' `prob_distribution`. For example, to specify a gamma distribution: +#' `as_epiparameter(x, prob_distribution = "gamma")`. #' #' ***Warning***: distributions specified via the `prob_dist` argument will #' overwrite the probability distribution specified in the `x` argument. For @@ -247,7 +247,7 @@ is_epiparameter_df <- function(x) { # capture dots and extract article info if supplied dots <- list(...) article <- dots$article - prob_dist_in <- dots$prob_dist + prob_dist_in <- dots$prob_distribution # validate multi-row entries if (nrow(x) > 1) { stopifnot( diff --git a/man/as_epiparameter.Rd b/man/as_epiparameter.Rd index e028b4eaa..0194f5b00 100644 --- a/man/as_epiparameter.Rd +++ b/man/as_epiparameter.Rd @@ -25,9 +25,9 @@ to function via the \code{...} argument. The argument should be called \code{art as it will be matched by name by \code{$}. To specify a probability distribution pass a \code{character} string to the -function via the \code{...} argument. The argument should be called \code{prob_dist}. -For example, to specify a gamma distribution: -\code{as_epiparameter(x, prob_dist = "gamma")}. +function via the \code{...} argument. The argument should be called +\code{prob_distribution}. For example, to specify a gamma distribution: +\code{as_epiparameter(x, prob_distribution = "gamma")}. \emph{\strong{Warning}}: distributions specified via the \code{prob_dist} argument will overwrite the probability distribution specified in the \code{x} argument. For diff --git a/tests/testthat/test-coercion.R b/tests/testthat/test-coercion.R index 247104bbe..598e1390d 100644 --- a/tests/testthat/test-coercion.R +++ b/tests/testthat/test-coercion.R @@ -97,7 +97,7 @@ test_that("as_epiparameter works for ebola SI assumed prob_dist (issue #310)", { # suppress warning and message about citation ebola_serial_epiparameter <- suppressWarnings( suppressMessages( - as_epiparameter(ebola_serial, prob_dist = "gamma") + as_epiparameter(ebola_serial, prob_distribution = "gamma") ) ) expect_s3_class(ebola_serial_epiparameter, class = "epiparameter") @@ -122,7 +122,7 @@ test_that("as_epiparameter works for lassa incubation overwritten prob_dist", { # suppress warning and message about citation lassa_incub_epiparameter <- suppressWarnings( suppressMessages( - as_epiparameter(lassa_incub, prob_dist = "lnorm") + as_epiparameter(lassa_incub, prob_distribution = "lnorm") ) ) expect_s3_class(lassa_incub_epiparameter, class = "epiparameter") @@ -155,7 +155,7 @@ test_that("as_epiparameter works for overwritten prob_dist with same parameters" ) ebola_si_weibull <- suppressWarnings( suppressMessages( - as_epiparameter(ebola_si, prob_dist = "weibull") + as_epiparameter(ebola_si, prob_distribution = "weibull") ) ) expect_s3_class(ebola_si_gamma, class = "epiparameter") @@ -179,7 +179,7 @@ test_that("as_epiparameter fails as expected with overwritten prob_dist", { expect_error( suppressWarnings( suppressMessages( - as_epiparameter(ebola_si, prob_dist = "lnorm") + as_epiparameter(ebola_si, prob_distribution = "lnorm") ) ), regexp = "Incorrect parameters provided for probability distribution." From 35b8b1e9e28f2142d2403fbbf4134b858a5c2350 Mon Sep 17 00:00:00 2001 From: Joshua Lambert Date: Tue, 8 Oct 2024 12:10:31 +0100 Subject: [PATCH 11/11] update WORDLIST --- inst/WORDLIST | 1 + 1 file changed, 1 insertion(+) diff --git a/inst/WORDLIST b/inst/WORDLIST index 443423c5c..52837b509 100644 --- a/inst/WORDLIST +++ b/inst/WORDLIST @@ -22,6 +22,7 @@ etc EVD facetted jsonlite +Lassa Lifecycle Marburg md