Merge pull request #537 from USEPA/hrm_test

Hrm test

R/Maintenance.R

@@ -232,3 +232,67 @@ FindSynonyms <- function() {
 # # run to update spelling word list
 # spelling::get_wordlist()
 # spelling::update_wordlist()
+
+# # Find Broken Links if test-URLChecker.R fails
+# # Run the code below:
+# # extract urls function
+# extract_urls <- function(text) {
+#   stringr::str_extract_all(text, "http[s]?://[^\\s\\)\\]]+") %>% unlist()
+# }
+# 
+# # clean urls function
+# clean_url <- function(url) {
+#   stringr::str_remove_all(url, "[\\\\.,\\\")]+$|[{}].*") %>%
+#     stringr::str_remove_all("[<>]")
+# }
+# 
+# # create lists of files to check
+# other_files <- c(
+#   system.file("README.md", package = "EPATADA"),
+#   system.file("DESCRIPTION", package = "EPATADA"),
+#   system.file("NAMESPACE", package = "EPATADA")
+# )
+# 
+# vignettes <- list.files(system.file("vignettes", package = "EPATADA"), pattern = ".Rmd", full.names = TRUE)
+# 
+# articles <- list.files(system.file("vignettes/articles", package = "EPATADA"), pattern = ".Rmd", full.names = TRUE)
+# 
+# r_files <- list.files(system.file("R", package = "EPATADA"), pattern = ".R", full.names = TRUE)
+# 
+# # combine file lists
+# files <- append(other_files, vignettes) %>%
+#   append(articles) %>%
+#   append(r_files)
+# 
+# # create list of urls
+# urls <- purrr::map(files, ~ readLines(.x)) %>%
+#   unlist() %>%
+#   extract_urls() %>%
+#   clean_url() %>%
+#   unique() %>%
+#   # problematic URL I can't get a response from using multiple methods (itec) and CRAN because its response is inconsistent, likely due to redirecting to mirrors (HRM 10/28/2024)
+#   setdiff(c(
+#     "https://www.itecmembers.org/attains/"
+#   ))
+# 
+# # retrieve http response headers from url list
+# headers <- urls %>%
+#   purrr::map(~ tryCatch(curlGetHeaders(.x), error = function(e) NA))
+# 
+# # extract response code from first line of header response
+# response_code <- sapply(headers, "[[", 1)
+# 
+# # create data frame of urls and response codes
+# df <- data.frame(urls, response_code)
+# 
+# # filter for any response codes that are not successful or redirect responses
+# df_false <- df %>%
+#   dplyr::filter(!grepl("200", response_code) &
+#                   !grepl("301", response_code) &
+#                   !grepl("302", response_code))
+# 
+# # Review the output of df_false.
+# # More information about http response codes can be found here:
+# # [Mozilla Developer HTTP response status codes] (https://developer.mozilla.org/en-US/docs/Web/HTTP/Status)
+# # Replace the broken links with functional ones or remove if no acceptable substitute is available.
+# # Rerun code above to verify that df_false contains zero rows.

R/Utilities.R

@@ -1405,7 +1405,7 @@ TADA_addPoints <- function(map, layerfilepath, layergroup, layername, bbox = NUL
   if (is.na(lbbox[1])) {
     return(map)
   }
-  shapes <- c(2) # open triangle; for other options see http://www.statmethods.net/advgraphs/parameters.html
+  shapes <- c(2) # open triangle; for other options see https://www.geeksforgeeks.org/r-plot-pch-symbols-different-point-shapes-available-in-r/
   iconFiles <- pchIcons(shapes, width = 20, height = 20, col = c("#CC7722"), lwd = 2)
   map <- leaflet::addMarkers(
     map,

README.md

@@ -4,7 +4,7 @@
 
 [![](https://github.com/USEPA/EPATADA/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/USEPA/EPATADA/actions/workflows/R-CMD-check.yaml)
 
-Tools for Automated Data Analysis, or TADA, is being developed to help States, Tribes (i.e., Tribal Nations, Pueblos, Bands, Rancherias, Communities, Colonies, Towns, Indians, Villages), federal partners, and any other [Water Quality Portal (WQP)](https://www.waterqualitydata.us/) users (e.g. researchers) efficiently compile and evaluate WQP data collected from water quality monitoring sites. TADA is both a stand-alone R package, and a building block to support development of the [TADA R Shiny application](https://github.com/USEPA/EPATADAShiny). We encourage you to read this package's [LICENSE](https://usepa.github.io/EPATADA/LICENSE.html) and [README](https://usepa.github.io/EPATADA/index.html) files (you are here).
+Tools for Automated Data Analysis, or TADA, is being developed to help States, Tribes (i.e., Tribal Nations, Pueblos, Bands, Rancherias, Communities, Colonies, Towns, Indians, Villages), federal partners, and any other [Water Quality Portal (WQP)](https://www.waterqualitydata.us/) users (e.g. researchers) efficiently compile and evaluate WQP data collected from water quality monitoring sites. TADA is both a stand-alone R package, and a building block to support development of the [TADA R Shiny application](https://github.com/USEPA/TADAShiny). We encourage you to read this package's [LICENSE](https://usepa.github.io/EPATADA/LICENSE.html) and [README](https://usepa.github.io/EPATADA/index.html) files (you are here).
 
 -   How to use TADA:
 
@@ -34,7 +34,7 @@ install.packages("remotes")
 remotes::install_github("USEPA/EPATADA", ref = "develop", dependencies = TRUE, force = TRUE)
 ```
 
-The TADA R Shiny application can be run [on the web](https://owshiny-dev.app.cloud.gov/tada-dev/) (R and R Studio install not required), or within R Studio. Run the following code within R Studio to install or update and run the most recent version of the [TADA R Shiny](https://github.com/USEPA/EPATADAShiny) application:
+The TADA R Shiny application can be run [on the web](https://rconnect-public.epa.gov/TADAShiny/) (R and R Studio install not required), or within R Studio. Run the following code within R Studio to install or update and run the most recent version of the [TADA R Shiny](https://github.com/USEPA/TADAShiny) application:
 
 ```{r}
 if(!"remotes"%in%installed.packages()){
@@ -73,7 +73,7 @@ Effective August 8, 2016, the [OMB Mandate: M-16-21; Federal Source Code Policy:
 
 The EPA specific implementation of OMB Mandate M-16-21 is addressed in the [System Life Cycle Management Procedure](https://www.epa.gov/irmpoli8/policy-procedures-and-guidance-system-life-cycle-management-slcm). EPA has chosen to use GitHub as its version control system as well as its inventory of open-source code projects. EPA uses GitHub to inventory its custom-developed, open-source code and generate the necessary metadata file that is then posted to code.gov for broad reuse in compliance with OMB Mandate M-16-21.
 
-If you have any questions or want to read more, check out the [EPA Open Source Project Repo](https://github.com/USEPA/open-source-projects) and [EPA's Interim Open Source Code Guidance](https://www.epa.gov/developers/open-source-software-and-epa-code-repository-requirements).
+If you have any questions or want to read more, check out the [EPA Open Source Project Repo](https://www.epa.gov/developers/open-source-software-and-code-repositories) and [EPA's Interim Open Source Software Policy](https://www.epa.gov/sites/default/files/2018-02/documents/interim_oss_policy_final.pdf).
 
 ## License
 

tests/testthat/test-URLChecker.R

@@ -0,0 +1,68 @@
+test_that("URLs are not broken", {
+  # extract urls function
+  extract_urls <- function(text) {
+    stringr::str_extract_all(text, "http[s]?://[^\\s\\)\\]]+") %>% unlist()
+  }
+
+  # clean urls function
+  clean_url <- function(url) {
+    stringr::str_remove_all(url, "[\\\\.,\\\")]+$|[{}].*") %>%
+      stringr::str_remove_all("[<>]")
+  }
+
+  # create lists of files to check
+  other_files <- c(
+    system.file("README.md", package = "EPATADA"),
+    system.file("DESCRIPTION", package = "EPATADA"),
+    system.file("NAMESPACE", package = "EPATADA")
+  )
+
+  vignettes <- list.files(system.file("vignettes", package = "EPATADA"), pattern = ".Rmd", full.names = TRUE)
+
+  articles <- list.files(system.file("vignettes/articles", package = "EPATADA"), pattern = ".Rmd", full.names = TRUE)
+
+  r_files <- list.files(system.file("R", package = "EPATADA"), pattern = ".R", full.names = TRUE)
+
+  # combine file lists
+  files <- append(other_files, vignettes) %>%
+    append(articles) %>%
+    append(r_files)
+
+  # create list of urls
+  urls <- purrr::map(files, ~ readLines(.x)) %>%
+    unlist() %>%
+    extract_urls() %>%
+    clean_url() %>%
+    unique() %>%
+    # problematic URL I can't get a response from using multiple methods (itec) and CRAN because its response is inconsistent, likely due to redirecting to mirrors (HRM 10/28/2024)
+    setdiff(c(
+      "https://www.itecmembers.org/attains/"
+    ))
+
+  # retrieve http response headers from url list
+  headers <- urls %>%
+    purrr::map(~ tryCatch(curlGetHeaders(.x), error = function(e) NA))
+
+  # extract response code from first line of header response
+  response_code <- sapply(headers, "[[", 1)
+
+  # create data frame of urls and response codes
+  df <- data.frame(urls, response_code)
+
+  # filter for any response codes that are not successful or redirect responses
+  df_false <- df %>%
+    dplyr::filter(!grepl("200", response_code) &
+                    !grepl("301", response_code) &
+                    !grepl("302", response_code))
+
+  # count number of failed responses
+  n <- nrow(df_false)
+
+  # print url and response code for failures
+  print(df_false)
+
+  # verify that there are zero urls with failing response codes
+  testthat::expect_equal(n, 0)
+})
+
+

vignettes/CONTRIBUTING.Rmd

@@ -82,9 +82,9 @@ There are multiple ways to interact with GitHub using Git.
 -   Option 2: Interact with GitHub using the command line or a web
     browser
 
-    -   [Setting Up Git](https://docs.github.com/articles/set-up-git/)
+    -   [Setting Up Git](https://docs.github.com/en/get-started/getting-started-with-git/set-up-git)
 
-    -   [Git Basics](https://git-scm.com/book/ch1-3.html)
+    -   [Git Basics](https://git-scm.com/book/en/v2/Git-Basics-Getting-a-Git-Repository)
 
     -   [Comprehensive Guide: Happy Git and GitHub for the
         useR](https://happygitwithr.com/ "Great and comprehensive guide for Git with an R flair")
@@ -107,7 +107,7 @@ might be needed for Mac or Linux OS:
 
 -   Download both:
 
-    -   [GitHub Desktop](https://desktop.github.com/)
+    -   [GitHub Desktop](https://github.com/apps/desktop)
 
     -   [Git](https://git-scm.com/downloads)
 
@@ -149,7 +149,7 @@ install.packages(c("devtools", "rmarkdown"))
     might be good first pickings for your first contribution to this
     open-source project.
 -   Pull requests can be directly
-    [linked](https://docs.github.com/en/issues/tracking-your-work-with-issues/linking-a-pull-request-to-an-issue)
+    [linked](https://docs.github.com/en/issues/tracking-your-work-with-issues/using-issues/linking-a-pull-request-to-an-issue)
     to a specific issue. If linked, the Repository Administrators can
     more easily review the pull request and issue at the same time once
     a contributor submits the pull request. The issue can then be closed

vignettes/TADAModule1.Rmd

@@ -165,7 +165,7 @@ Additional resources:
     the console: ?TADA_DataRetrieval
 
 -   [Introduction to the dataRetrieval
-    package](https://CRAN.R-project.org/package=dataRetrieval)
+    package](https://cran.r-project.org/web/packages/dataRetrieval/index.html)
 
 -   [General Data Import from Water Quality
     Portal](https://rdrr.io/cran/dataRetrieval/man/readWQPdata.html)
@@ -1308,7 +1308,7 @@ interface. The shiny application queries the WQP, contains maps and data
 visualizations, flags suspect data results, handles censored data, and
 more. You can launch it using the code below.
 
-DRAFT [Module 1](https://owshiny-dev.app.cloud.gov/tada-dev/) is also
+DRAFT [Module 1](https://rconnect-public.epa.gov/TADAShiny/) is also
 currently hosted on the web with minimal server memory/storage
 allocated.
 

vignettes/TADAModule1_AdvancedTraining.Rmd

@@ -781,6 +781,6 @@ remotes::install_github("USEPA/TADAShiny", ref = "develop", dependencies = TRUE)
 TADAShiny::run_app()
 ```
 
-DRAFT [Module 1](https://owshiny-dev.app.cloud.gov/tada-dev/) is also
+DRAFT [Module 1](https://rconnect-public.epa.gov/TADAShiny/) is also
 currently hosted on the web with minimal server memory/storage
 allocated.

vignettes/TADAModule1_BeginnerTraining.Rmd

@@ -1147,7 +1147,7 @@ interface. The shiny application queries the WQP, contains maps and data
 visualizations, flags suspect data results, handles censored data, and
 more. You can launch it using the code below.
 
-DRAFT [Module 1](https://owshiny-dev.app.cloud.gov/tada-dev/) is also
+DRAFT [Module 1](https://rconnect-public.epa.gov/TADAShiny/) is also
 currently hosted on the web with minimal server memory/storage
 allocated.
 

vignettes/WQXValidationService.Rmd

@@ -100,7 +100,7 @@ interquartile range) and a [probability density
 function](https://en.wikipedia.org/wiki/Probability_density_function
 "Probability density function") (pdf) of a Normal N(0,σ2) Population.
 Attribution: Jhguch at en.wikipedia, [CC BY-SA
-2.5](https://creativecommons.org/licenses/by-sa/2.5), via Wikimedia
+2.5](https://creativecommons.org/licenses/by-sa/2.5/), via Wikimedia
 Commons.](images/IQR.png)](https://commons.wikimedia.org/wiki/File:Boxplot_vs_PDF.svg)
 
 Additional tests only available in WQX Web and Node Submissions (for