address smnnlt follow-up: streamline test suite and drop purrr

- rewrote test suite from ~600 to 373 focused assertions (0 fail / 0 warn / 0 skip on local devtools::test())

- replaced expect_true(is.data.frame()) with expect_s3_class(), expect_equal(length()) with expect_length()

- removed redundant gg-class checks now covered by vdiffr snapshots

- deleted test-smoke-and-errors.R, test-uncovered-branches.R and other fragmented test files

- replaced mock helpers with inst/extdata/ example data where possible

- removed purrr from dependencies entirely

- removed CITATION.cff (flagged by R CMD check)

- cleaned up NAMESPACE, DESCRIPTION, and .Rbuildignore

- R CMD check: 0 errors, 0 warnings

Author: HzaCode

.Rbuildignore

@@ -97,7 +97,7 @@
 ^package\.json$
 ^package-lock\.json$
 ^strava_api.*\.md$
-^提交指南.*\.md$
+^submission_guide.*\.md$
 ^export_data$
 ^athlytics_downloads_raw_data\.csv$
 ^Athlytics_.*\.tar\.gz$
@@ -108,7 +108,7 @@
 ^analysis_output$
 ^Athlytics$
 ^\.lang$
-^.*调试.*$
+^.*debug.*$
 ^create_multi_athlete_sample_data\.R$
 ^regenerate_figures\.R$
 ^.*coverage.*\.R$
@@ -154,3 +154,8 @@
 ^\.pytest_cache$
 ^review.*\.md$
 ^document_output\.log$
+^PACKAGES$
+^PACKAGES\.gz$
+^PACKAGES\.rds$
+^coverage_output\.txt$
+^test-ef-adv\.Rout$

CITATION.cff

@@ -34,7 +34,7 @@ Suggests:
     R.utils,
     readr,
     rmarkdown,
-    testthat (>= 3.0.0),
+    testthat (>= 3.1.5),
     vdiffr,
     xml2
 Remotes:
@@ -43,4 +43,5 @@ Additional_repositories: https://grimbough.r-universe.dev
 VignetteBuilder: knitr
 RoxygenNote: 7.3.3
 Roxygen: list(markdown = TRUE)
+Config/testthat/edition: 3
 NeedsCompilation: no

DESCRIPTION

@@ -26,7 +26,6 @@ export(plot_with_reference)
 export(quality_summary)
 export(summarize_quality)
 export(theme_athlytics)
-import(ggplot2)
 importFrom(dplyr,"%>%")
 importFrom(dplyr,first)
 importFrom(rlang,"%||%")

NAMESPACE

@@ -433,20 +433,26 @@ calculate_ef <- function(activities_data,
 #' @return Data frame with EF calculation results
 #'
 #' @examples
-#' \dontrun{
-#' # Parse activity file and calculate EF from streams
-#' streams <- parse_activity_file("activity_12345.fit")
-#' ef_result <- calculate_ef_from_stream(
-#'   stream_data = streams,
+#' # Example with synthetic stream data
+#' set.seed(42)
+#' n <- 3600
+#' stream <- data.frame(
+#'   time = 0:(n - 1),
+#'   heartrate = round(150 + rnorm(n, 0, 2)),
+#'   velocity_smooth = 3.0 + rnorm(n, 0, 0.05),
+#'   distance = cumsum(rep(3.0, n))
+#' )
+#' result <- calculate_ef_from_stream(
+#'   stream_data = stream,
 #'   activity_date = as.Date("2025-01-15"),
 #'   act_type = "Run",
 #'   ef_metric = "speed_hr",
-#'   min_steady_minutes = 20,
-#'   steady_cv_threshold = 0.08,
-#'   min_hr_coverage = 0.9,
-#'   quality_control = "filter"
+#'   min_steady_minutes = 10,
+#'   steady_cv_threshold = 0.1,
+#'   min_hr_coverage = 0.8,
+#'   quality_control = "off"
 #' )
-#' }
+#' print(result)
 #'
 #' @export
 calculate_ef_from_stream <- function(stream_data, activity_date, act_type, ef_metric,

R/calculate_ef.R

@@ -218,21 +218,28 @@ cohort_reference <- function(data,
 #'   "p25_p75" (inner quartiles), "p05_p95" (outer 5-95 range), "p50" (median).
 #'   Default c("p25_p75", "p05_p95", "p50").
 #' @param alpha Transparency for reference bands (0-1). Default 0.15.
-#' @param colors Named list of colors for bands. Default uses viridis colors.
+#' @param colors Named list of colors for bands. Default uses Nature-inspired palette colors.
 #'
 #' @return A ggplot object with added reference bands.
 #'
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' # Create base plot
-#' p <- plot_acwr(acwr_df = individual_acwr)
+#' # Example: add reference bands to an ACWR plot
+#' data("sample_acwr", package = "Athlytics")
+#' set.seed(42)
+#' cohort <- dplyr::bind_rows(
+#'   dplyr::mutate(sample_acwr, athlete_id = "A1"),
+#'   dplyr::mutate(sample_acwr, athlete_id = "A2",
+#'     acwr_smooth = acwr_smooth * runif(nrow(sample_acwr), 0.9, 1.1))
+#' )
+#' ref <- suppressWarnings(
+#'   calculate_cohort_reference(cohort, metric = "acwr_smooth", min_athletes = 2)
+#' )
+#' p <- suppressMessages(plot_acwr(sample_acwr, highlight_zones = FALSE))
+#' p_ref <- add_reference_bands(p, reference_data = ref)
+#' print(p_ref)
 #'
-#' # Add reference bands
-#' p_with_ref <- add_reference_bands(p, reference_data = cohort_ref)
-#' print(p_with_ref)
-#' }
 add_reference_bands <- function(p,
                                 reference_data,
                                 bands = c("p25_p75", "p05_p95", "p50"),
@@ -261,7 +268,8 @@ add_reference_bands <- function(p,
       data = ref_wide,
       ggplot2::aes(x = .data$date, ymin = .data$p05, ymax = .data$p95),
       fill = colors$p05_p95,
-      alpha = alpha
+      alpha = alpha,
+      inherit.aes = FALSE
     )
   }
 
@@ -270,7 +278,8 @@ add_reference_bands <- function(p,
       data = ref_wide,
       ggplot2::aes(x = .data$date, ymin = .data$p25, ymax = .data$p75),
       fill = colors$p25_p75,
-      alpha = alpha * 1.5
+      alpha = alpha * 1.5,
+      inherit.aes = FALSE
     )
   }
 
@@ -280,7 +289,8 @@ add_reference_bands <- function(p,
       ggplot2::aes(x = .data$date, y = .data$p50),
       color = colors$p50,
       linetype = "dashed",
-      linewidth = 0.8
+      linewidth = 0.8,
+      inherit.aes = FALSE
     )
   }
 

R/cohort_reference.R

@@ -73,7 +73,6 @@ athlytics_palette_vibrant <- function() {
 #'   theme_athlytics()
 #'
 #' @export
-#' @import ggplot2
 theme_athlytics <- function(base_size = 13, base_family = "") {
   ggplot2::theme_minimal(base_size = base_size, base_family = base_family) +
     ggplot2::theme(

R/color_palettes.R

@@ -239,10 +239,17 @@ flag_quality <- function(streams,
 #' @export
 #'
 #' @examples
-#' \dontrun{
-#' flagged_data <- flag_quality(stream_data)
+#' # Create sample stream and summarize quality
+#' set.seed(42)
+#' stream_data <- data.frame(
+#'   time = seq(0, 3600, by = 1),
+#'   heartrate = pmax(60, pmin(200, rnorm(3601, mean = 150, sd = 10))),
+#'   watts = pmax(0, rnorm(3601, mean = 200, sd = 20)),
+#'   velocity_smooth = pmax(0, rnorm(3601, mean = 3.5, sd = 0.3))
+#' )
+#' flagged_data <- flag_quality(stream_data, sport = "Run")
 #' summarize_quality(flagged_data)
-#' }
+#'
 summarize_quality <- function(flagged_streams) {
   if (!is.data.frame(flagged_streams)) {
     stop("`flagged_streams` must be a data frame from flag_quality().")

R/flag_quality.R

@@ -52,28 +52,24 @@
 #' follow applicable privacy regulations when using this data for research purposes.
 #'
 #' @examples
-#' \dontrun{
-#' # Load all activities from local CSV
-#' activities <- load_local_activities("strava_export_data/activities.csv")
+#' # Example using built-in sample CSV
+#' csv_path <- system.file("extdata", "activities.csv", package = "Athlytics")
+#' if (nzchar(csv_path)) {
+#'   activities <- load_local_activities(csv_path)
+#'   head(activities)
+#' }
 #'
-#' # Load directly from ZIP archive (no need to extract manually!)
+#' \dontrun{
+#' # Load from a local Strava export ZIP archive
 #' activities <- load_local_activities("export_12345678.zip")
 #'
-#' # Load only running activities from 2023
+#' # Filter by date and activity type
 #' activities <- load_local_activities(
 #'   path = "export_12345678.zip",
 #'   start_date = "2023-01-01",
 #'   end_date = "2023-12-31",
 #'   activity_types = "Run"
 #' )
-#'
-#' # Use with Athlytics functions
-#' acwr_data <- calculate_acwr(activities, load_metric = "distance_km")
-#' plot_acwr(acwr_data, highlight_zones = TRUE)
-#'
-#' # Multi-metric analysis
-#' ef_data <- calculate_ef(activities, ef_metric = "speed_hr")
-#' plot_ef(ef_data, add_trend_line = TRUE)
 #' }
 #'
 #' @export

R/load_local_activities.R

@@ -13,12 +13,16 @@
 #'   Returns NULL if file cannot be parsed or does not exist.
 #'
 #' @examples
+#' # Parse a built-in example TCX file
+#' tcx_path <- system.file("extdata", "activities", "example.tcx", package = "Athlytics")
+#' if (nzchar(tcx_path)) {
+#'   streams <- parse_activity_file(tcx_path)
+#'   if (!is.null(streams)) head(streams)
+#' }
+#'
 #' \dontrun{
-#' # Parse a FIT file
+#' # Parse a FIT file from a Strava export
 #' streams <- parse_activity_file("activity_12345.fit", export_dir = "strava_export/")
-#'
-#' # Parse a compressed GPX file
-#' streams <- parse_activity_file("activity_12345.gpx.gz")
 #' }
 #'
 #' @export