Fill out treatment level nas, closes #309

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: portalr
 Title: Create Useful Summaries of the Portal Data
-Version: 0.4.3
+Version: 0.4.4
 Authors@R: 
     c(person(given = c("Glenda", "M."),
              family = "Yenni",

NEWS.md

@@ -1,11 +1,19 @@
 # portalr
+
+Version numbers follow [Semantic Versioning](https://semver.org/).
+
+# portalr 0.4.4
+
+* Fix bug in `na_drop = FALSE` that failed to complete missing rows to the treatment level when `time = "newmoon"`.
+
+# [portalr 0.4.3](https://github.com/weecology/portalr/releases/tag/v0.4.3)
+*2024-09-23*
+
 * `load_rodent_data()` now returns an object with an S3 class, and provides a useful message on `print`.
 * Users can now pass arguments to `download_observations()` from `load_rodent_data()` and other calling functions.
 * Fix bug in `na_drop = FALSE` that failed to complete missing rows to the species level when `time = "newmoon"`.
 * Fix bug in `ndvi()` that filtered by sensor only for higher levels.
 
-Version numbers follow [Semantic Versioning](https://semver.org/).
-
 # [portalr 0.4.2](https://github.com/weecology/portalr/releases/tag/v0.4.2)
 *2024-08-08*
 

R/process_data_utils.R

@@ -100,18 +100,20 @@ add_time <- function(summary_table, newmoons_table, time = "period") {
   {
     join_summary_newmoon <- dplyr::right_join(newmoons_table, summary_table,
                                               by = c("period" = "period")) %>%
-      dplyr::filter(.data$period <= max(.data$period, na.rm = TRUE))
+      dplyr::filter(.data$period <= max(.data$period, na.rm = TRUE))  %>%
+        tidyr::drop_na(tidyselect::any_of(c("species","plot","treatment")))
   } else {
     newmoons_table$censusdate[is.na(newmoons_table$censusdate)] <-
       newmoons_table$newmoondate[is.na(newmoons_table$censusdate)]
-    vars_to_complete <- names(dplyr::select(summary_table,tidyselect::any_of(c("species","plot"))))
+    vars_to_complete <-
+        names(dplyr::select(summary_table,tidyselect::any_of(c("species","plot","treatment"))))
     join_summary_newmoon <- dplyr::left_join(newmoons_table, summary_table,
                                              by = "period") %>%
                             tidyr::complete(tidyr::nesting(!!!rlang::syms(c("newmoonnumber",
                                                            "newmoondate",
                                                            "censusdate"))),
                                             !!!rlang::syms(vars_to_complete)) %>%
-                            tidyr::drop_na(tidyselect::any_of(c("species","plot")))
+                            tidyr::drop_na(tidyselect::any_of(c("species","plot","treatment")))
   }
   date_vars <- c("newmoondate", "newmoonnumber", "period", "censusdate")
   vars_to_keep <- switch(tolower(time),

R/process_rodent_data.R

@@ -167,6 +167,10 @@ prep_rodent_output <- function(level_data, effort, na_drop,
     level_data <- dplyr::select(level_data, -"nplots")
   }
 
+  if (level == "treatment" && "newmoonnumber" %in% names(level_data)) {
+    level_data <- dplyr::filter(level_data, !(treatment == 'spectabs' & newmoonnumber > 340))
+  }
+
   if (output == "rates") {
     grouping <- switch(level,
                        "plot" = c("species", "plot"),

R/summarize_rodents.R

@@ -87,6 +87,8 @@ summarize_rodent_data <- function(path = get_default_data_path(),
   time <- tolower(time)
   output <- tolower(output)
 
+  if (! (level %in% c("plot", "treatment", "site"))) {level = "site"}
+
   if (!missing("length"))
   {
     warning("The `length` argument is deprecated; please use `plots` instead.")

tests/testthat/test-03-summarize-rodents.R

@@ -131,7 +131,7 @@ test_that("abundance filters at the plot level correctly", {
                                 min_plots = 1, min_traps = 1, effort = TRUE,
                                 na_drop = FALSE) %>%
     dplyr::filter(ntraps < 1, period <= 463)
-  expect_equal(NROW(incomplete_plots), 238)
+  expect_equal(NROW(incomplete_plots), 213)
 
   incomplete_plots <- abundance(path = portal_data_path, level = "plot",
                                 min_plots = 1, min_traps = 1, effort = TRUE) %>%