HzaCode · HzaCode · Feb 13, 2026 · Feb 13, 2026
diff --git a/.Rbuildignore b/.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$
diff --git a/CITATION.cff b/CITATION.cff
diff --git a/DESCRIPTION b/DESCRIPTION
@@ -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
diff --git a/NAMESPACE b/NAMESPACE
@@ -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,"%||%")

diff --git a/R/calculate_ef.R b/R/calculate_ef.R
@@ -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,

diff --git a/R/cohort_reference.R b/R/cohort_reference.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
     )
   }
 

diff --git a/R/color_palettes.R b/R/color_palettes.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(

diff --git a/R/flag_quality.R b/R/flag_quality.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().")

diff --git a/R/load_local_activities.R b/R/load_local_activities.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

diff --git a/R/parse_activity_file.R b/R/parse_activity_file.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

diff --git a/R/plot_exposure.R b/R/plot_exposure.R
@@ -29,7 +29,6 @@
 #'   Optional risk zones (based on ACWR thresholds ~0.8, 1.3, 1.5) can be shaded.
 #'   **Best practice: Use `calculate_exposure()` first, then pass the result to this function.**
 #'
-#' @import ggplot2
 #' @export
 #'
 #' @examples

diff --git a/R/plot_pbs.R b/R/plot_pbs.R
@@ -22,7 +22,6 @@
 #'   solid points mark new PBs. Y-axis is MM:SS.
 #'   **Best practice: Use `calculate_pbs()` first, then pass the result to this function.**
 #'
-#' @import ggplot2
 #' @export
 #'
 #' @examples
@@ -181,7 +180,7 @@ plot_pbs <- function(data,
     # Use linear model (lm) instead of loess to avoid errors with sparse data
     # and to better represent the overall improvement trend
     p <- p + ggplot2::geom_smooth(
-      method = "lm", se = TRUE, aes(group = .data$distance_label),
+      method = "lm", se = TRUE, ggplot2::aes(group = .data$distance_label),
       linewidth = 1.0, alpha = 0.15, linetype = "dashed"
     )
   }

diff --git a/inst/extdata/activities.csv b/inst/extdata/activities.csv
@@ -0,0 +1,76 @@
+"Activity ID","Activity Date","Activity Name","Activity Type","Elapsed Time","Moving Time","Distance","Filename","Elevation Gain","Elevation Loss","Average Heart Rate","Max Heart Rate","Average Speed","Max Speed","Average Watts","Max Watts","Calories","Relative Effort"
+4,"Oct 01, 2024, 11:35:00 AM","Afternoon Ride","Ride",5486,5268,33892,"",246,237,132,163,6.43,7.9,178,307,863,46
+5,"Oct 02, 2024, 8:35:00 AM","Tempo Run","Run",2641,2364,7925,"",59,55,165,176,3.35,4.4,,,471,59
+6,"Oct 04, 2024, 6:41:00 AM","Morning Run","Run",2785,2632,6976,"",61,52,148,174,2.65,3.6,,,352,53
+7,"Oct 05, 2024, 7:44:00 AM","Long Run","Run",5649,5485,18440,"",93,81,142,166,3.36,4.7,,,1056,49
+8,"Oct 07, 2024, 6:25:00 AM","Morning Run","Run",2453,2230,6834,"",36,31,147,173,3.06,4.1,,,336,49
+9,"Oct 08, 2024, 10:39:00 AM","Afternoon Ride","Ride",4560,4490,31874,"",191,187,140,154,7.1,8.9,192,305,663,46
+10,"Oct 09, 2024, 6:42:00 AM","Tempo Run","Run",2171,2025,7016,"",62,53,160,175,3.46,4.3,,,375,54
+11,"Oct 10, 2024, 7:17:00 AM","Morning Run","Run",2697,2461,6763,"",68,62,144,169,2.75,3.8,,,413,50
+12,"Oct 11, 2024, 6:35:00 AM","Morning Run","Run",2372,2136,6543,"",69,61,147,175,3.06,4.1,,,285,50
+13,"Oct 12, 2024, 7:59:00 AM","Long Run","Run",5584,5325,15716,"",115,109,143,162,2.95,3.9,,,856,48
+14,"Oct 14, 2024, 6:54:00 AM","Morning Run","Run",2847,2642,6987,"",60,51,152,170,2.64,3.6,,,517,54
+15,"Oct 15, 2024, 9:58:00 AM","Afternoon Ride","Ride",3899,3612,30107,"",267,261,129,158,8.34,10.3,188,311,517,45
+16,"Oct 16, 2024, 7:55:00 AM","Tempo Run","Run",2549,2265,8357,"",49,41,157,175,3.69,4.9,,,393,49
+17,"Oct 18, 2024, 8:33:00 AM","Morning Run","Run",2367,2208,7130,"",61,54,145,169,3.23,4.1,,,357,45
+18,"Oct 19, 2024, 11:59:00 AM","Hard Ride","Ride",6926,6646,50888,"",363,353,149,170,7.66,10.3,216,367,945,48
+19,"Oct 21, 2024, 6:27:00 AM","Morning Run","Run",2311,2073,6322,"",54,44,145,168,3.05,3.7,,,399,49
+20,"Oct 22, 2024, 10:36:00 AM","Afternoon Ride","Ride",4370,4229,24052,"",188,184,142,158,5.69,7.6,167,297,691,51
+21,"Oct 23, 2024, 6:34:00 AM","Tempo Run","Run",2351,2094,8785,"",74,68,157,180,4.2,5.3,,,305,48
+22,"Oct 24, 2024, 8:26:00 AM","Morning Run","Run",2468,2199,6398,"",63,55,144,175,2.91,3.5,,,355,44
+23,"Oct 25, 2024, 8:59:00 AM","Morning Run","Run",2662,2376,6528,"",40,34,148,169,2.75,3.6,,,347,47
+24,"Oct 26, 2024, 11:36:00 AM","Hard Ride","Ride",6276,6096,37207,"",443,439,145,167,6.1,8.5,207,346,1166,45
+25,"Oct 28, 2024, 7:54:00 AM","Morning Run","Run",2463,2306,7963,"",47,40,145,174,3.45,4.4,,,364,48
+26,"Oct 29, 2024, 11:28:00 AM","Afternoon Ride","Ride",4225,3989,34775,"",153,147,130,158,8.72,12,170,271,635,42
+27,"Oct 30, 2024, 6:21:00 AM","Tempo Run","Run",2091,1820,7291,"",47,36,160,179,4.01,5.1,,,290,50
+28,"Nov 01, 2024, 8:14:00 AM","Morning Run","Run",2816,2685,6270,"",42,33,148,169,2.34,3.2,,,519,54
+29,"Nov 02, 2024, 7:54:00 AM","Long Run","Run",5021,4788,13851,"",115,105,144,171,2.89,4,,,933,43
+30,"Nov 04, 2024, 7:04:00 AM","Morning Run","Run",2484,2326,7688,"",64,60,148,170,3.31,4.2,,,434,48
+31,"Nov 05, 2024, 10:50:00 AM","Afternoon Ride","Ride",4322,4084,34408,"",216,209,139,164,8.43,10.4,181,274,731,51
+32,"Nov 06, 2024, 8:48:00 AM","Tempo Run","Run",2400,2192,8120,"",64,53,158,185,3.7,4.9,,,349,51
+33,"Nov 07, 2024, 7:54:00 AM","Morning Run","Run",2128,2055,7896,"",42,32,150,175,3.84,4.7,,,354,50
+34,"Nov 08, 2024, 8:33:00 AM","Morning Run","Run",2836,2569,7499,"",41,33,145,175,2.92,3.6,,,455,46
+35,"Nov 09, 2024, 6:19:00 AM","Long Run","Run",6316,6105,18792,"",92,85,144,163,3.08,4,,,1172,44
+36,"Nov 11, 2024, 7:21:00 AM","Morning Run","Run",2167,2070,6965,"",60,55,149,170,3.36,4.1,,,383,49
+37,"Nov 12, 2024, 10:53:00 AM","Afternoon Ride","Ride",5188,5004,34729,"",220,212,136,153,6.94,9,170,304,816,41
+38,"Nov 13, 2024, 7:06:00 AM","Tempo Run","Run",2083,1936,7828,"",65,54,156,180,4.04,5.6,,,297,52
+39,"Nov 15, 2024, 8:02:00 AM","Morning Run","Run",2183,2025,7665,"",59,53,147,171,3.79,5,,,304,51
+40,"Nov 16, 2024, 6:29:00 AM","Long Run","Run",4503,4366,15357,"",98,93,146,163,3.52,4.7,,,697,52
+41,"Nov 18, 2024, 6:25:00 AM","Morning Run","Run",2767,2665,8278,"",56,46,148,171,3.11,4.3,,,397,50
+42,"Nov 19, 2024, 10:41:00 AM","Afternoon Ride","Ride",5338,5178,27852,"",157,150,131,153,5.38,7.4,199,294,754,46
+43,"Nov 20, 2024, 6:13:00 AM","Tempo Run","Run",2156,1882,7066,"",69,61,157,180,3.75,4.6,,,269,56
+44,"Nov 21, 2024, 8:56:00 AM","Morning Run","Run",2270,2146,7921,"",47,41,146,172,3.69,4.5,,,369,52
+45,"Nov 22, 2024, 7:22:00 AM","Morning Run","Run",2572,2448,6318,"",67,56,150,168,2.58,3.3,,,364,53
+46,"Nov 23, 2024, 8:17:00 AM","Long Run","Run",5499,5315,13021,"",140,135,143,164,2.45,3.4,,,908,50
+47,"Nov 25, 2024, 8:08:00 AM","Morning Run","Run",2296,2210,6865,"",59,55,151,169,3.11,3.8,,,430,48
+48,"Nov 26, 2024, 11:33:00 AM","Afternoon Ride","Ride",3643,3401,24674,"",202,193,129,156,7.25,9.5,188,283,500,48
+49,"Nov 27, 2024, 7:12:00 AM","Tempo Run","Run",2091,1810,8268,"",62,53,155,181,4.57,5.7,,,319,49
+50,"Nov 29, 2024, 8:16:00 AM","Morning Run","Run",2604,2305,8483,"",64,54,150,170,3.68,4.7,,,382,50
+51,"Nov 30, 2024, 11:02:00 AM","Hard Ride","Ride",6095,5996,44174,"",361,354,141,169,7.37,10,231,354,1009,47
+52,"Dec 02, 2024, 6:44:00 AM","Morning Run","Run",2243,2129,6266,"",52,42,148,170,2.94,3.9,,,305,51
+53,"Dec 03, 2024, 10:38:00 AM","Afternoon Ride","Ride",4382,4296,31377,"",182,174,133,155,7.3,9.8,166,298,817,46
+54,"Dec 04, 2024, 7:05:00 AM","Tempo Run","Run",2591,2299,8150,"",60,49,160,182,3.55,4.5,,,338,58
+55,"Dec 05, 2024, 6:32:00 AM","Morning Run","Run",2571,2326,7281,"",52,41,146,169,3.13,4,,,362,52
+56,"Dec 06, 2024, 6:15:00 AM","Morning Run","Run",2365,2285,7402,"",51,44,151,170,3.24,4.4,,,319,47
+57,"Dec 07, 2024, 10:30:00 AM","Hard Ride","Ride",6069,5979,42496,"",491,481,149,169,7.11,8.7,220,371,1016,51
+58,"Dec 09, 2024, 8:32:00 AM","Morning Run","Run",2182,2013,8106,"",68,58,150,172,4.03,5.6,,,336,47
+59,"Dec 10, 2024, 11:55:00 AM","Afternoon Ride","Ride",3939,3702,31183,"",236,226,132,156,8.42,10.8,195,314,672,43
+60,"Dec 11, 2024, 8:20:00 AM","Tempo Run","Run",2323,2175,7396,"",54,47,156,179,3.4,4.6,,,354,53
+61,"Dec 13, 2024, 8:49:00 AM","Morning Run","Run",2851,2638,8427,"",47,36,145,171,3.19,4.3,,,519,49
+62,"Dec 14, 2024, 7:33:00 AM","Long Run","Run",4386,4305,15462,"",116,109,146,171,3.59,4.5,,,626,45
+63,"Dec 16, 2024, 8:36:00 AM","Morning Run","Run",2735,2673,6370,"",60,51,152,175,2.38,2.9,,,478,55
+64,"Dec 17, 2024, 9:33:00 AM","Afternoon Ride","Ride",4445,4169,28985,"",180,170,129,157,6.95,9.6,188,271,820,44
+65,"Dec 18, 2024, 7:32:00 AM","Tempo Run","Run",2292,2215,7131,"",64,53,156,178,3.22,4.1,,,352,54
+66,"Dec 19, 2024, 8:57:00 AM","Morning Run","Run",2543,2267,6691,"",40,35,145,174,2.95,4.1,,,383,49
+67,"Dec 20, 2024, 8:33:00 AM","Morning Run","Run",2582,2343,6704,"",52,43,145,174,2.86,3.8,,,458,44
+68,"Dec 21, 2024, 7:28:00 AM","Long Run","Run",5668,5554,14447,"",93,90,142,162,2.6,3.6,,,821,43
+69,"Dec 23, 2024, 6:18:00 AM","Morning Run","Run",2665,2416,7461,"",68,58,146,173,3.09,3.7,,,334,49
+70,"Dec 24, 2024, 11:00:00 AM","Afternoon Ride","Ride",3855,3660,32566,"",193,182,135,162,8.9,10.7,175,303,594,49
+71,"Dec 25, 2024, 8:57:00 AM","Tempo Run","Run",2101,1925,7597,"",47,41,158,184,3.95,4.9,,,361,56
+72,"Dec 27, 2024, 8:32:00 AM","Morning Run","Run",2306,2065,7680,"",55,46,148,174,3.72,5.1,,,385,54
+73,"Dec 28, 2024, 8:31:00 AM","Long Run","Run",6090,5941,13586,"",121,115,146,165,2.29,3,,,1154,48
+74,"Dec 30, 2024, 7:58:00 AM","Morning Run","Run",2336,2049,7732,"",35,29,144,171,3.77,5,,,307,48
+75,"Dec 31, 2024, 10:07:00 AM","Afternoon Ride","Ride",5381,5289,26258,"",264,254,141,162,4.96,6.2,200,299,1051,52
+1,"Jan 01, 2025, 12:00:00 PM","Example Run","Run",3600,3600,5000,"activities/example.tcx",50,30,145,170,3.5,4,,,100,50
+2,"Jan 02, 2025, 12:00:00 PM","Example Ride","Ride",3600,3600,10000,"activities/example.gpx",100,80,140,165,5.5,6,200,250,200,80
+3,"Jan 03, 2025, 12:00:00 PM","Example FIT","Run",2400,2400,3000,"activities/example.fit",30,20,150,175,3.3,3.8,,,80,40
diff --git a/inst/extdata/example.fit → inst/extdata/activities/example.fit b/inst/extdata/example.fit → inst/extdata/activities/example.fit
diff --git a/inst/extdata/example.gpx → inst/extdata/activities/example.gpx b/inst/extdata/example.gpx → inst/extdata/activities/example.gpx
diff --git a/inst/extdata/example.tcx → inst/extdata/activities/example.tcx b/inst/extdata/example.tcx → inst/extdata/activities/example.tcx