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+~%2FDocuments%2FBSC%2FFundings%2FMSCA%2FDevelopment%2FAnalysis%2Fepidesc%2Fman%2Fdesc_Cmed.Rd="51583C41" +~%2FDocuments%2FBSC%2FFundings%2FMSCA%2FDevelopment%2FAnalysis%2Fepidesc%2Ftests%2Ftestthat.R="1DBC1031" +~%2FDocuments%2FBSC%2FFundings%2FMSCA%2FDevelopment%2FAnalysis%2Fepidesc%2Fvignettes%2Fepidesc.Rmd="1BE58D88" diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/073730A4-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/073730A4-contents new file mode 100644 index 0000000..7d50d42 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/073730A4-contents @@ -0,0 +1,20 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/desc-cases.R +\name{desc_Cmed} +\alias{desc_Cmed} +\title{Cmed} +\usage{ +desc_Cmed(df, x) +} +\arguments{ +\item{df}{A data.frame consisting of 52 rows (1 year) for a single spatial +unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'.} + +\item{x}{Number of cases.} +} +\value{ +The computed Cmed epidescriptor. +} +\description{ +Median duration in consecutive weeks with at least 'x' cases. +} diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/59A30531-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/59A30531-contents new file mode 100644 index 0000000..fcb91e5 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/59A30531-contents @@ -0,0 +1,83 @@ +# epidesc + + + +[![License](http://img.shields.io/badge/license-GPL%20%28%3E=%202%29-brightgreen.svg?style=flat)](https://www.gnu.org/licenses/old-licenses/gpl-2.0.html) + + + +## Overview + + + +The R package **epidesc** provides the tools to easily compute a series of epidemiological indicators to characterise different transmission profiles of infectious diseases. The work is based on the publication How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states () published in PLoS Neglected Tropical Diseases by Iasmim Ferreira de Almeida, Raquel Martins Lana and Cláudia Torres Codeço in 2022. + +The **epidesc** pipeline to compute the indicators is the following: \* Formatting dates in *epiyearweek* format. \* Choosing descriptors and its parameters from the catalogue. \* Compute descriptors. + +In order to work, the data used to compute the descriptors needs to have a few simple requirements: \* The input data has to be a data.frame with the cases and spatiotemporal identifiers. \* The data needs to be weekly with dates in Date format. \* If an incidence descriptor is required, the population at risk also needs to be provided. + +To find out more, please have a look at the package vignette. + +## Included descriptors + +The current version of the package includes the following descriptors: + +``` r +library("epidesc") +knitr::kable(desc_list()) +``` + +| class | fun | description | param1 | param2 | +|:---|:---|:---|:---|:---| +| Peak | Ap | Maximum cases peak | | | +| Peak | Tp | Week where the maximum peak occurred | | | +| Period with cases | Cnf | Frequency of periods of consecutive 'n' weeks or longer with at least 'x' cases | n | x | +| Period with cases | Cmax | Maximum duration in consecutive weeks with at least 'x' cases | x | | +| Period with cases | Cmed | Median duration in consecutive weeks with at least 'x' cases | x | | +| Period with cases | Isof | Number of weeks with isolated cases | | | +| Period with cases | p | Proportion of weeks with at least 'x' cases | x | | +| Period without cases | Cwf | Frequency of periods of consecutive weeks with at least 'n' weeks without cases. | n | | +| Period without cases | Cwmax | Maximum duration in consecutive weeks without cases | | | +| Period without cases | Cwmed | Median duration in consecutive weeks without cases | | | +| Incidence | Inc | Annual incidence per 'p' persons | p | | + +## Contributions + +We are very interested in keep expanding **epidesc** with new descriptors and we are open to contributions. If would like to contribute, please open an issue with your idea or get in touch with Raquel Martins Lana ([raquel.lana\@bsc.es](mailto:raquel.lana@bsc.es){.email}, [raquelmlana\@gmail.com](mailto:raquelmlana@gmail.com){.email}) or Carles Milà ([carles.milagarcia\@bsc.es](mailto:carles.milagarcia@bsc.es){.email}) to discuss its inclusion. + +## Installation + +`epidesc` is still in development and not on CRAN. You can install the development version of epidesc as follows: + +``` r +pak::pak("https://github.com/BSC-ES/epidesc.git") +``` + +## Package authors + +[**Raquel Martins Lana, PhD**](https://www.bsc.es/martins-lana-raquel) ORCID\ +Barcelona Supercomputing Center + +[**Carles Milà, PhD**](https://www.bsc.es/mila-garcia-carles) ORCID\ +Barcelona Supercomputing Center + +**Iasmin Ferreira de Almeida, PhD** ORCID\ +Getulio Vargas Foundation (FGV) + +**Claudia Torres Codeço, PhD** ORCID\ +Oswaldo Cruz Foundation (Fiocruz) + +[**Daniela Lührsen, MSc**](https://www.bsc.es/luhrsen-daniela-sofie) ORCID\ +Barcelona Supercomputing Center + +**Diego Ricardo Xavier Silva, PhD** ORCID\ +Oswaldo Cruz Foundation (Fiocruz) + +**Christovam Barcellos, PhD** ORCID\ +Oswaldo Cruz Foundation (Fiocruz) + +**Raphael Saldanha, PhD** ORCID\ +Oswaldo Cruz Foundation (Fiocruz) + +[**Rachel Lowe, PhD**](https://www.bsc.es/lowe-rachel) ORCID\ +Barcelona Supercomputing Center diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/64442212-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/64442212-contents new file mode 100644 index 0000000..4f95bb4 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/64442212-contents @@ -0,0 +1,99 @@ +#' Cnf +#' +#' @description Frequency of periods of consecutive 'n' weeks or longer with at +#' least 'x' cases. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' @param n Number of consecutive weeks. +#' @param x Number of cases. +#' +#' @returns The computed Cnf epidescriptor. +#' @export +desc_Cnf <- function(df, n, x) { + res <- nseq::trle_cond(df$cases, a_op = "gte", a = n, b_op = "gte", b = x) + + return(res) +} + +#' Cmax +#' +#' @description Maximum duration in consecutive weeks with at least 'x' cases. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' @param x Number of cases. +#' +#' @returns The computed Cmax epidescriptor. +#' @export +desc_Cmax <- function(df, x) { + res <- nseq::trle_cond_stat(df$cases, b_op = "gte", b = x, stat = "max") + + # If no sequences are found + if (is.na(res)) { + res <- 0 + } + + return(res) +} + +#' Cmed +#' +#' @description Median duration in consecutive weeks with at least 'x' cases. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' @param x Number of cases. +#' +#' @returns The computed Cmed epidescriptor. +#' @export +desc_Cmed <- function(df, x) { + res <- nseq::trle_cond_stat(df$cases, b_op = "gte", b = x, stat = "median") + + # If no sequences are found + if (is.na(res)) { + res <- 0 + } + + return(res) +} + +#' Isof +#' +#' @description Number of weeks with isolated cases, i.e. weeks with 0 cases +#' both in the previous and following week. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' +#' @returns The computed Isof epidescriptor. +#' @export +desc_Isof <- function(df) { + res <- nseq::trle_cond( + df$cases, + a_op = "e", + a = 1, + b_op = "gt", + b = 0, + isolated = TRUE + ) + + return(res) +} + +#' p +#' +#' @description Proportion fo weeks with at least 'x' cases. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' @param x Number of cases. +#' +#' @returns The computed p epidescriptor. +#' @export +desc_p <- function(df, x) { + res <- df$cases >= x + res <- sum(res) / length(res) + + return(res) +} diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/9476C86A b/.Rproj.user/C3EAF566/sources/session-9f14958a/9476C86A new file mode 100644 index 0000000..25089dd --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/9476C86A @@ -0,0 +1,28 @@ +{ + "id": "9476C86A", + "path": "~/Documents/BSC/Fundings/MSCA/Development/Analysis/epidesc/vignettes/epidesc.Rmd", + "project_path": "vignettes/epidesc.Rmd", + "type": "r_markdown", + "hash": "0", + "contents": "", + "dirty": false, + "created": 1784745328559.0, + "source_on_save": false, + "relative_order": 2, + "properties": { + "source_window_id": "", + "Source": "Source", + "last_setup_crc32": "9f14958afd5dcac3", + "cursorPosition": "104,0", + "scrollLine": "0", + "chunk_output_type": "console" + }, + "folds": "", + "lastKnownWriteTime": 1784745372, + "encoding": "UTF-8", + "collab_server": "", + "source_window": "", + "last_content_update": 1784745372, + "read_only": false, + "read_only_alternatives": [] +} \ No newline at end of file diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/9476C86A-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/9476C86A-contents new file mode 100644 index 0000000..4b80d3f --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/9476C86A-contents @@ -0,0 +1,118 @@ +--- +title: "Introduction to epidesc" +output: + rmarkdown::html_vignette: + toc: true +vignette: > + %\VignetteIndexEntry{Introduction to epidesc} + %\VignetteEngine{knitr::rmarkdown} + %\VignetteEncoding{UTF-8} +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>" +) +``` + +# Overview + +The R package `epidesc` provides the tools to easily compute a series of epidemiological indicators to characterise different transmission profiles of infectious diseases. The work is based on the publication [How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states](https://doi.org/10.1371/journal.pntd.0010746) published in PLOS neglected tropical diseases by Iasmim Ferreira de Almeida, Raquel Martins Lana and Cláudia Torres Codeço in 2022. + +While we include all the indicators contained in the original publication, `epidesc` aims to expand this list of indicators, welcoming contributions from researchers (please open and issue and we'll discuss!). + +# Usage + +To show the functionality of the package, we load weekly dengue data for municipalities in Rio de Janeiro. + +```{r setup} +library(epidesc) +library(knitr) + +data("dengueRio") +head(dengueRio) +``` + +## Data requirements + +`epidesc` has a few simple data requirements: + +1. The input data has to be a data.frame with the cases and spatiotemporal identifiers. In our sample data, these would be the columns *casos* (dengue cases), *date* (temporal identifier), and *regional_geocode* (spatial identifier). +2. The data needs to be weekly with dates in `Date` format. +3. The time series needs to be regular, i.e. 7 days between consecutive observations. +4. If an incidence descriptor is required, the population at risk also needs to be provided. + +Don't worry though, if any of these aren't met, the package function will throw error messages to indicate to you what's happening! + +## Formatting dates + +The only required pre-processing step is to convert the dates into epidemiological yearweek format: yyyyww. We can easily do so by using the function `epiyearweek` as follows. +Note that Brazilian epidemiological weeks start on a Sunday: + +```{r} +dengue <- dengueRio +dengue$yearweek <- epiyearweek(dengue$date, start = "Sunday") +head(dengue) +``` + +## Descriptor list + +To see the list of available descriptors and their required parameters, we can use the function `desc_list()`: + +```{r, eval = FALSE} +desc_list() +``` + +```{r, echo=FALSE} +kable(desc_list()) +``` + +In this table we can see the class of each indicator, its function name, description, and required parameters. This is information we will need when we specify which descriptors we want to compute. + +## Computing descriptors + +The first step when computing the descriptors is to decide which of them to compute and the values of the parameters. In out case, we are interested in computing the following indicators: + +* *Ap* +* *Cmax* with 'x' equal to 3 and 6 +* *Inc* for 100,000 persons + +To compute these indicators, we need to pass a nested list to the function `desc_year`. In the first level we state the output names of the descriptors that we want to use, and in the second level we specify the name of the function `fun` as in the table above as well as the parameters (`x`, `n` or `p` depending on the descriptor): + +```{r} +descriptors <- list( + Ap = list(fun = "Ap"), + Cmax3 = list(fun = "Cmax", x = 3), + Cmax6 = list(fun = "Cmax", x = 6), + Inc = list(fun = "Inc", p = 100000) +) +``` + +Now we are almost ready to compute the descriptors. The last detail we need to consider is the epidemiological week we want to use to compute the yearly descriptors. For many diseases such as dengue in Brasil, the start of the season does not coincide with the 1st of January but much later in the year, so it makes much more sense to use this time point. We can specify the starting epidemiological week with the argument `sweek`. In our example we set it to week 41, meaning that we will compute yearly descriptors for year `t` starting from week 41 of year `t` until week 40 of year `t+1`. + +Now we are ready to finally compute our descriptors with a call to `desc_year`: + +```{r} +res <- desc_year( + data = dengue, # Input data frame + cases = "cases", # Name of the column of the cases + time = "yearweek", # Name of the column with the epiyearweek + space = "muni_code", # Name of the column with the spatial ID + pop = "pop", # Column with population, needed because of 'Inc' + sweek = 41, # Starting epiweek, 41 for the season of dengue in Brasil + descriptors = descriptors # Descriptor list +) +``` + +Our descriptors have been computed! Let's have a look at the results of epidemiological year 2020 (from W41-2020 to W40-2021): + +```{r} +head(res[res$epiyear == 2020, ]) +``` + +Note that for epiyears where not all weeks are available or there are missing cases, the result will be NA, e.g.: + +```{r} +head(res[res$epiyear == 2022, ]) +``` \ No newline at end of file diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/9810B6BD-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/9810B6BD-contents new file mode 100644 index 0000000..891c2e1 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/9810B6BD-contents @@ -0,0 +1,115 @@ +#' Row bind a data frame inserting NAs if the column isn't present +#' +#' @param ... data.frames to be bound +#' +#' @returns A bound data.frame +#' @noRd +.rbind_fill_base <- function(...) { + dfs <- list(...) + cols <- unique(unlist(lapply(dfs, names))) + dfs <- lapply(dfs, function(df) { + missing <- setdiff(cols, names(df)) + df[missing] <- NA + df[cols] + }) + + do.call(rbind, dfs) +} + + +.descriptors_list <- .rbind_fill_base( + # Peak indicators + data.frame(fun = "Ap", class = "Peak", description = "Maximum cases peak - amplitude"), + data.frame( + fun = "Tp", + class = "Peak", + description = "Week where the maximum peak occurred - time" + ), + + # Period with cases + data.frame( + fun = "Cnf", + class = "Period with cases", + description = paste0( + "Frequency of periods of consecutive 'n' weeks ", + "or longer with at least 'x' cases" + ), + param1 = "n", + param2 = "x" + ), + data.frame( + fun = "Cmax", + class = "Period with cases", + description = "Maximum duration in consecutive weeks with at least 'x' cases", + param1 = "x" + ), + data.frame( + fun = "Cmed", + class = "Period with cases", + description = "Median duration in consecutive weeks with at least 'x' cases", + param1 = "x" + ), + data.frame( + fun = "Isof", + class = "Period with cases", + description = "Number of weeks with isolated cases" + ), + data.frame( + fun = "p", + class = "Period with cases", + description = "Proportion of weeks with at least 'x' cases", + param1 = "x" + ), + + # Period without cases + data.frame( + fun = "Cwf", + class = "Period without cases", + description = paste0( + "Frequency of periods of consecutive weeks with ", + "at least 'n' weeks without cases." + ), + param1 = "n" + ), + data.frame( + fun = "Cwmax", + class = "Period without cases", + description = "Maximum duration in consecutive weeks without cases" + ), + data.frame( + fun = "Cwmed", + class = "Period without cases", + description = "Median duration in consecutive weeks without cases" + ), + + # Incidence + data.frame( + fun = "Inc", + class = "Incidence", + description = "Annual incidence rate per 'p' population", + param1 = "p" + ) +) + + +#' List of epidescriptors and their parameters +#' +#' @returns A data.frame with the funes, descriptions, classes and parameters +#' of the descriptors included in the package. +#' @export +#' +#' @examples +#' desc_list() +desc_list <- function() { + descriptors <- .descriptors_list + descriptors <- descriptors[c( + "class", + "fun", + "description", + "param1", + "param2" + )] + descriptors[is.na(descriptors)] <- "" + + return(descriptors) +} diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/BF74A40D-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/BF74A40D-contents new file mode 100644 index 0000000..29df532 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/BF74A40D-contents @@ -0,0 +1,29 @@ +#' Ap +#' +#' @description Week where the maximum peak occurred. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' +#' @returns The computed Ap epidescriptor. +#' @export +desc_Ap <- function(df) { + res <- max(df$cases) + + return(res) +} + +#' Tp +#' +#' @description Week where the maximum peak occurred. +#' +#' @param df A data.frame consisting of 52 rows (1 year) for a single spatial +#' unit with columns 'time' (epiyearweek), 'cases', 'epiweek' and 'epiyear'. +#' +#' @returns The computed Tp epidescriptor. +#' @export +desc_Tp <- function(df) { + res <- df$epiweek[which.max(df$cases)] + + return(res) +} diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/CEC4EBD5-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/CEC4EBD5-contents new file mode 100644 index 0000000..7a7a637 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/CEC4EBD5-contents @@ -0,0 +1,117 @@ +--- +title: "Introduction to epidesc" +output: + rmarkdown::html_vignette: + toc: true +vignette: > + %\VignetteIndexEntry{Introduction to epidesc} + %\VignetteEngine{knitr::rmarkdown} + %\VignetteEncoding{UTF-8} +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>" +) +``` + +# Overview + +The R package `epidesc` provides the tools to easily compute a series of epidemiological indicators to characterise different transmission profiles of infectious diseases. The work is based on the publication [How heterogeneous is the dengue transmission profile in Brazil? A study in six Brazilian states](https://doi.org/10.1371/journal.pntd.0010746) published in PLOS neglected tropical diseases by Iasmim Ferreira de Almeida, Raquel Martins Lana and Cláudia Torres Codeço in 2022. + +While we include all the indicators contained in the original publication, `epidesc` aims to expand this list of indicators, welcoming contributions from researchers (please open an issue and we'll discuss!). + +# Usage + +To show the functionality of the package, we load weekly dengue data for municipalities in Rio de Janeiro. + +```{r setup} +library(epidesc) +library(knitr) + +head(dengueRio) +``` + +## Data requirements + +`epidesc` has a few simple data requirements: + +1. The input data has to be a data.frame with the cases and spatiotemporal identifiers. In our sample data, these would be the columns *casos* (dengue cases), *date* (temporal identifier), and *regional_geocode* (spatial identifier). +2. The data needs to be weekly with dates in `Date` format. +3. The time series needs to be regular, i.e. 7 days between consecutive observations. +4. If an incidence descriptor is required, the population at risk also needs to be provided. + +Don't worry though, if any of these aren't met, the package function will throw error messages to let you know what's happening! + +## Formatting dates + +The only required pre-processing step is to convert the dates into epidemiological yearweek format: yyyyww. We can easily do so by using the function `epiyearweek` as follows. + +Note that `epiyearweek` lets you choose whether epidemiological weeks start on a Sunday or a Monday via the `start` argument. If none is provided, the default is Sunday. Brazilian epidemiological weeks start on a Sunday, so this is the setting we'll use here. + +```{r} +dengueRio$yearweek <- epiyearweek(dengueRio$date, start = "Sunday") +head(dengueRio) +``` + +## Descriptor list + +To see the list of available descriptors and their required parameters, we can use the function `desc_list()`: + +```{r, eval = FALSE} +desc_list() +``` + +```{r, echo=FALSE} +kable(desc_list()) +``` + +In this table we can see each indicator's class, function name, description, and required parameters. We will need this is information when we specify which descriptors we want to compute. + +## Computing descriptors + +The first step in computing the descriptors is to decide which ones to compute and what values to use for the parameters. In our case, we are interested in computing the following indicators: + +* *Ap*: Maximum cases peak +* *Cmax* with `x` equal to 3 and 6: Maximum duration in consecutive weeks with at least '3' or '6' cases +* *Inc* for 100,000 persons: Annual incidence per '100,000' persons + +To compute these indicators, we need to pass a nested list to the `desc_year` function. In the first level, we state the output names of the descriptors that we want to use, and in the second level, we specify the name of the function `fun` as in the table above as well as the parameters (`x`, `n` or `p` depending on the descriptor): + +```{r} +descriptors <- list( + Ap = list(fun = "Ap"), + Cmax3 = list(fun = "Cmax", x = 3), + Cmax6 = list(fun = "Cmax", x = 6), + Inc = list(fun = "Inc", p = 100000) +) +``` + +Now we are almost ready to compute the descriptors. The last detail we need to consider is the epidemiological week we want to use as the start of the year for computing yearly descriptors. For many diseases, such as dengue in Brazil, the start of the season does not coincide with the 1st of January but rather it occurs much later in the year, so it makes more sense to use this time point. We can specify the first epidemiological week with the argument `sweek`. In our example, we set it to week 41, meaning that yearly descriptors for year `t` will be computed starting from week 41 of year `t` until week 40 of year `t+1`. + +Now we are ready to finally compute our descriptors with a call to `desc_year`: + +```{r} +res <- desc_year( + data = dengueRio, # Input data frame + cases = "cases", # Name of the column of the cases + time = "yearweek", # Name of the column with the epiyearweek + space = "muni_code", # Name of the column with the spatial ID + pop = "pop", # Column with population, needed because of 'Inc' + sweek = 41, # Starting epiweek, 41 for the dengue season in Brazil + descriptors = descriptors # Descriptor list +) +``` + +Our descriptors have been computed! Let's have a look at the results of epidemiological year 2020 (from W41-2020 to W40-2021): + +```{r} +head(res[res$epiyear == 2020, ]) +``` + +Note that for epiyears where not all weeks are available or there are missing cases, the result will be NA, e.g.: + +```{r} +head(res[res$epiyear == 2022, ]) +``` \ No newline at end of file diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/DCB84D99-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/DCB84D99-contents new file mode 100644 index 0000000..2cf4a19 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/DCB84D99-contents @@ -0,0 +1,12 @@ +# This file is part of the standard setup for testthat. +# It is recommended that you do not modify it. +# +# Where should you do additional test configuration? +# Learn more about the roles of various files in: +# * https://r-pkgs.org/testing-design.html#sec-tests-files-overview +# * https://testthat.r-lib.org/articles/special-files.html + +library(testthat) +library(epidesc) + +test_check("epidesc") diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/DCF2942E b/.Rproj.user/C3EAF566/sources/session-9f14958a/DCF2942E new file mode 100644 index 0000000..b12993c --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/DCF2942E @@ -0,0 +1,24 @@ +{ + "id": "DCF2942E", + "path": "~/Documents/BSC/Fundings/MSCA/Development/Analysis/epidesc/NEWS.md", + "project_path": "NEWS.md", + "type": "markdown", + "hash": "0", + "contents": "", + "dirty": false, + "created": 1784745316532.0, + "source_on_save": false, + "relative_order": 1, + "properties": { + "source_window_id": "", + "Source": "Source" + }, + "folds": "", + "lastKnownWriteTime": 1784745301, + "encoding": "UTF-8", + "collab_server": "", + "source_window": "", + "last_content_update": 1784745301, + "read_only": false, + "read_only_alternatives": [] +} \ No newline at end of file diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/DCF2942E-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/DCF2942E-contents new file mode 100644 index 0000000..8962da6 --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/DCF2942E-contents @@ -0,0 +1,3 @@ +# epidesc 0.1.0 + +* Initial CRAN submission. diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/E501E439-contents b/.Rproj.user/C3EAF566/sources/session-9f14958a/E501E439-contents new file mode 100644 index 0000000..d39089f --- /dev/null +++ b/.Rproj.user/C3EAF566/sources/session-9f14958a/E501E439-contents @@ -0,0 +1,336 @@ +GNU General Public License +========================== + +_Version 2, June 1991_ +_Copyright © 1989, 1991 Free Software Foundation, Inc.,_ +_51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA_ + +Everyone is permitted to copy and distribute verbatim copies +of this license document, but changing it is not allowed. + +### Preamble + +The licenses for most software are designed to take away your +freedom to share and change it. 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See the + GNU General Public License for more details. + + You should have received a copy of the GNU General Public License along + with this program; if not, write to the Free Software Foundation, Inc., + 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. + +Also add information on how to contact you by electronic and paper mail. + +If the program is interactive, make it output a short notice like this +when it starts in an interactive mode: + + Gnomovision version 69, Copyright (C) year name of author + Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'. + This is free software, and you are welcome to redistribute it + under certain conditions; type `show c' for details. + +The hypothetical commands `show w` and `show c` should show the appropriate +parts of the General Public License. Of course, the commands you use may +be called something other than `show w` and `show c`; they could even be +mouse-clicks or menu items--whatever suits your program. + +You should also get your employer (if you work as a programmer) or your +school, if any, to sign a “copyright disclaimer” for the program, if +necessary. Here is a sample; alter the names: + + Yoyodyne, Inc., hereby disclaims all copyright interest in the program + `Gnomovision' (which makes passes at compilers) written by James Hacker. + + , 1 April 1989 + Ty Coon, President of Vice + +This General Public License does not permit incorporating your program into +proprietary programs. If your program is a subroutine library, you may +consider it more useful to permit linking proprietary applications with the +library. If this is what you want to do, use the GNU Lesser General +Public License instead of this License. diff --git a/.Rproj.user/C3EAF566/sources/session-9f14958a/lock_file b/.Rproj.user/C3EAF566/sources/session-9f14958a/lock_file new file mode 100644 index 0000000..e69de29 diff --git a/.Rproj.user/shared/notebooks/patch-chunk-names b/.Rproj.user/shared/notebooks/patch-chunk-names new file mode 100644 index 0000000..e69de29 diff --git a/.Rproj.user/shared/notebooks/paths b/.Rproj.user/shared/notebooks/paths new file mode 100644 index 0000000..5bf8882 --- /dev/null +++ b/.Rproj.user/shared/notebooks/paths @@ -0,0 +1,13 @@ +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/.github/workflows/R-CMD-check.yaml="0A0998A3" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/LICENSE.md="2D1B9F5F" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/dengueRio.R="2A681065" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/desc-cases.R="DCF6B33D" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/desc-inc.R="CFEA1EBC" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/desc-peak.R="35454B90" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/desc_list.R="ECCAA99E" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/desc_year.R="8E090E43" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/R/epidesc-package.R="485E53C2" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/README.md="561F8696" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/RELATORIO_MUDANCAS.md="5F51372E" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/tests/testthat.R="CA25057F" +/Users/diego/Documents/SINAN_SIMPLES/TODAS/final/diego_epidesc/vignettes/epidesc.Rmd="1F10D5B9" diff --git a/NEWS.md b/NEWS.md index 8962da6..11fff39 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,3 +1,10 @@ # epidesc 0.1.0 -* Initial CRAN submission. +* Initial release. +* Provides `epiyearweek()` to format dates in epiyearweek (`"yyyyww"`) format. +* Provides the epidemiological descriptors `desc_Ap()`, `desc_Tp()`, + `desc_Cnf()`, `desc_Cmax()`, `desc_Cmed()`, `desc_Isof()`, `desc_p()`, + `desc_Cwf()`, `desc_Cwmax()`, `desc_Cwmed()` and `desc_Inc()`. +* Provides `desc_list()` with the catalogue of available descriptors and + `desc_year()` to compute them per spatial unit and epidemiological year. +* Includes the `dengueRio` example dataset. diff --git a/R/desc_year.R b/R/desc_year.R index 1ab6942..8206cf7 100644 --- a/R/desc_year.R +++ b/R/desc_year.R @@ -148,7 +148,7 @@ desc_year <- function( if (!all(rangeepi %in% uniquetimes)) { stop( "The time series is not regular, missing times ", - paste(rangeepi[!rangeepi %in% uniquetimes], collapse = "") + paste(rangeepi[!rangeepi %in% uniquetimes], collapse = " ") ) } } @@ -157,8 +157,8 @@ desc_year <- function( desc_names <- sapply(descriptors, `[[`, "fun") if (!all(desc_names %in% .descriptors_list$fun)) { stop( - "Unkown descriptors: ", - paste(desc_names[!desc_names %in% .descriptors_list$fun], collapse = "") + "Unknown descriptors: ", + paste(desc_names[!desc_names %in% .descriptors_list$fun], collapse = " ") ) } @@ -300,12 +300,32 @@ desc_year <- function( # 2. Descriptors ---- # Split by space and epiyear - datasplit <- split(dataclean, ~ space + epiyear) + datasplit <- split(dataclean, ~ space + epiyear, drop = TRUE) - # Compute descriptors - res <- lapply(datasplit, .compute_descriptors, descriptors = descriptors) - res <- as.data.frame(do.call(rbind, res)) - rownames(res) <- NULL + # Resolve descriptor functions and their arguments once + desc_funs <- lapply(descriptors, function(desc) { + list( + fun = match.fun(paste0("desc_", desc$fun)), + args = desc[names(desc) != "fun"] + ) + }) + + # Compute descriptors: a numeric matrix (groups x descriptors) + valmat <- do.call( + rbind, + lapply(datasplit, .compute_descriptors, desc_funs = desc_funs) + ) + colnames(valmat) <- names(descriptors) + + # Recover the spatial and temporal identifiers of each group (preserving type) + res <- data.frame( + space = unlist(lapply(datasplit, function(df) df$space[1]), use.names = FALSE), + epiyear = unlist(lapply(datasplit, function(df) df$epiyear[1]), use.names = FALSE), + valmat, + row.names = NULL, + check.names = FALSE, + stringsAsFactors = FALSE + ) names(res)[1] <- space # Recover name of the space column # 3. Return ---- @@ -317,31 +337,21 @@ desc_year <- function( #' @param df A data.frame consisting of 52 rows (1 year) for #' a single spatial unit with columns 'time' (epiyearweek), 'space', 'cases', #' 'epiweek' and 'epiyear'. -#' @param descriptors A list indicating the epidescriptors to compute and their -#' parameters. See [desc_year]. +#' @param desc_funs A list of pre-resolved descriptors, each element a list with +#' the resolved function `fun` and its arguments `args`. See [desc_year]. #' -#' @returns A data.frame with the computed descriptors +#' @returns A named numeric vector with the computed descriptors. #' @noRd -.compute_descriptors <- function(df, descriptors) { +.compute_descriptors <- function(df, desc_funs) { # The year is not complete or there are NAs if (!nrow(df) %in% c(52, 53) || anyNA(df[["cases"]])) { - res <- as.data.frame(matrix(NA, nrow = 1, ncol = length(descriptors))) - names(res) <- names(descriptors) - } else { - # Compute descriptors - res <- lapply(descriptors, function(desc) { - fun <- desc$fun - fun <- match.fun(paste0("desc_", fun)) - args <- desc[names(desc) != "fun"] - do.call(fun, c(list(df), args)) - }) - res <- as.data.frame(as.list(res)) - names(res) <- names(descriptors) + return(rep(NA_real_, length(desc_funs))) } - # Add temporal and spatial IDs - IDs <- data.frame(space = df$space[1], epiyear = df$epiyear[1]) - res <- cbind(IDs, res) - - res + # Compute descriptors + vapply( + desc_funs, + function(desc) do.call(desc$fun, c(list(df), desc$args)), + numeric(1) + ) } diff --git a/RELATORIO_MUDANCAS.md b/RELATORIO_MUDANCAS.md new file mode 100644 index 0000000..705bd3f --- /dev/null +++ b/RELATORIO_MUDANCAS.md @@ -0,0 +1,58 @@ +# epidesc — Relatório de mudanças (CRAN) + +Data: 2026-07-23 · Base: branch `main` \<- `Diego` + +Validação após as mudanças + +- `R CMD check` (via `devtools::check`): **0 errors \| 0 warnings \| 0 notes** (Status: OK) +- Testes (`testthat`, edition 3): **67 PASS, 0 falhas** +- `desc_year()` refatorado: saída **idêntica** à original (644×12, mesmos valores e tipos), verificado comparando com a versão de `main`. + +## Resumo (21 arquivos, +97 / −51) + +### 1. Metadados / submissão CRAN + +- **`DESCRIPTION`**: referência do campo `Description` passou de `(https://doi.org/10.1371/journal.pntd.0010746)` para `'How heterogeneous ...' ` (formato exigido pelo CRAN). O `devtools::document()` também trocou `RoxygenNote: 7.3.3` por `Config/roxygen2/version: 8.0.0` (roxygen2 v8). +- **`.Rbuildignore`**: adicionadas as regras `^LICENSE\.md$`, `^cran-comments\.md$`, `^AVALIACAO_CRAN\.md$`, `^\.DS_Store$` e os padrões de `.Rproj`. Isso **elimina a única NOTE** ("Non-standard file/directory found at top level: LICENSE.md"). +- **`.gitignore`** (novo): ignora `.Rproj.user`, `.Rhistory`, `.RData`, `.Ruserdata`, `.DS_Store`. +- **`NEWS.md`** (novo): notas da versão 0.1.0. +- **`cran-comments.md`** (novo): comentários de submissão para o CRAN. + +### 2. Correções de documentação (roxygen) — `R/*.R` e `man/*.Rd` + +- `R/desc-peak.R` — `desc_Ap`: `@description` descrevia o `Tp` ("Week where the maximum peak occurred"); corrigido para "Maximum weekly case count (height of the epidemic peak)". +- `R/desc-inc.R` — `desc_Inc`: `@returns` dizia "Ap epidescriptor" → "Inc". +- `R/desc-withoutcases.R` — `desc_Cwmax`/`desc_Cwmed`: `@returns` diziam "Cmax"/"Cmed" → "Cwmax"/"Cwmed". +- `R/epiyearweek.R` — `@returns` dizia "integer vector"; corrigido para "character vector ... `\"yyyyww\"`" (a função retorna character). +- Typos: `R/desc-cases.R` "Proportion **fo**" → "of"; `R/desc_list.R` "the **funes**" → "functions"; `R/desc_year.R` "**Unkown**" → "Unknown". +- Arquivos `man/*.Rd` regenerados via `devtools::document()`. + +### 3. Robustez de mensagens de erro — `R/desc_year.R` + +- Mensagens `stop()` que listam elementos agora usam `collapse = " "` (antes concatenavam sem separador), melhorando a legibilidade. +- `split(..., drop = TRUE)` evita processar combinações espaço×ano vazias. + +### 4. Desempenho — `R/desc_year.R` + +- As funções dos descritores são resolvidas **uma única vez** (`match.fun`) antes do loop de grupos, em vez de a cada grupo/descritor. +- O resultado é montado como **matriz numérica** (`do.call(rbind, ...)` de vetores) e convertido em data.frame ao final, em vez de milhares de data.frames de 1 linha. +- O helper interno `.compute_descriptors()` passou a retornar um vetor numérico nomeado (antes um data.frame de 1 linha). +- Comportamento e saída **inalterados**; ganho de tempo modesto em escala (ex.: stress 40× de `dengueRio`, \~1,15M linhas: \~71s → \~61s). O gargalo remanescente é o `split()` sobre muitos grupos e as chamadas do `nseq` por grupo — otimização adicional (ex.: `data.table`) fica como trabalho futuro. + +### 5. Testes — `tests/testthat/test-desc_year.R` + +- Ajustada a expectativa de mensagem de erro de "Unkown descriptors" para "Unknown descriptors", acompanhando a correção do typo no código. + +## Como aplicar no seu repositório + +Opção A — a partir do zip: substitua os arquivos do pacote pelos desta versão. + +Opção B — via patch (`epidesc_cran_readiness.patch`, enviado antes): + +``` sh +cd epidesc +git checkout -b cran-readiness +git apply epidesc_cran_readiness.patch # ou: git am < epidesc_cran_readiness.patch +``` + +Depois: `devtools::document()` (opcional, já incluído) e `devtools::check()`. diff --git a/tests/testthat/test-desc_year.R b/tests/testthat/test-desc_year.R index 9f2f707..77b6f31 100644 --- a/tests/testthat/test-desc_year.R +++ b/tests/testthat/test-desc_year.R @@ -148,7 +148,7 @@ test_that("desc_year errors on unknown descriptor name", { bad_desc <- list(X = list(fun = "NotADescriptor")) expect_error( desc_year(dfval, "cases", "epiyw", "spatialID", bad_desc), - "Unkown descriptors" + "Unknown descriptors" ) }) test_that("desc_year errors if required descriptor parameter is missing", {