Resolved errors and warnings

DESCRIPTION

@@ -47,6 +47,7 @@ Imports:
     rsconnect,
     scales,
     shiny,
+    slider,
     stats,
     stringr,
     tibble,

NAMESPACE

@@ -8,6 +8,7 @@ export(Datetime_breaks)
 export(Datetime_limits)
 export(aggregate_Datetime)
 export(bright_dark_period)
+export(centroidLE)
 export(count_difftime)
 export(create_Timedata)
 export(cut_Datetime)
@@ -24,12 +25,12 @@ export(gapless_Datetimes)
 export(gg_day)
 export(gg_days)
 export(gg_overview)
-export(interdaily_stability)
-export(intradaily_variability)
 export(import)
 export(import_Dataset)
 export(import_Statechanges)
+export(interdaily_stability)
 export(interval2state)
+export(intradaily_variability)
 export(join_datasets)
 export(sc2interval)
 export(sleep_int2Brown)

R/metric_bright_dark_period.R

@@ -90,7 +90,7 @@ bright_dark_period <- function(Light.vector,
 
   # Get the epochs based on the data
   if (epoch == "dominant.epoch") {
-    epoch <- count.difftime(tibble::tibble(Datetime = Time.vector))$difftime[1]
+    epoch <- count_difftime(tibble::tibble(Datetime = Time.vector))$difftime[1]
   }
   # If the user specified an epoch, use that instead
   epoch <- lubridate::as.duration(epoch)

R/metric_duration_above_threshold.R

@@ -87,7 +87,7 @@ duration_above_threshold <- function(Light.vector,
 
   # Get the epochs based on the data
   if (epoch == "dominant.epoch") {
-    epoch <- count.difftime(tibble::tibble(Datetime = Time.vector))$difftime[1]
+    epoch <- count_difftime(tibble::tibble(Datetime = Time.vector))$difftime[1]
     epoch <- ifelse(hms::is_hms(Time.vector) | lubridate::is.POSIXct(Time.vector),
       lubridate::as.duration(epoch), epoch
     )

R/metric_interdaily_stability.R

@@ -81,7 +81,7 @@ interdaily_stability <- function(Light.vector,
       "Interdaily stability might not be meaningful for non-24 h days.",
       "These days contain less than 24 h:",
       paste(
-        capture.output(print(
+        utils::capture.output(print(
           dplyr::filter(N_hours, N < 24) %>% dplyr::pull(Day)
         )),
         sep = "\n", collapse = "\n"
@@ -97,7 +97,7 @@ interdaily_stability <- function(Light.vector,
       "Data contains some hours with only missing values",
       "These hours contain only missing values: ",
       paste(
-        capture.output(print(
+        utils::capture.output(print(
           dplyr::filter(hours_per_day, is_missing) %>% dplyr::pull(Hour)
         )),
         sep = "\n", collapse = "\n"
@@ -123,7 +123,7 @@ interdaily_stability <- function(Light.vector,
     dplyr::summarise(Light = mean(Light))
 
   # Variance across average day / variance across all days
-  is <- var(avg_hourly$Light) / var(total_hourly$Light)
+  is <- stats::var(avg_hourly$Light) / stats::var(total_hourly$Light)
 
   # Return data frame or numeric vector
   if (as.df) {

R/metric_intradaily_variability.R

@@ -79,7 +79,7 @@ intradaily_variability <- function(Light.vector,
       "Intradaily variability might not be meaningful for non-24 h days.",
       "These days contain less than 24 h:",
       paste(
-        capture.output(print(
+        utils::capture.output(print(
           dplyr::filter(N_hours, N < 24) %>% dplyr::pull(Day)
         )),
         sep = "\n", collapse = "\n"
@@ -95,7 +95,7 @@ intradaily_variability <- function(Light.vector,
       "Data contains some hours with only missing values",
       "These hours contain only missing values: ",
       paste(
-        capture.output(print(
+        utils::capture.output(print(
           dplyr::filter(hours_per_day, is_missing) %>% dplyr::pull(Hour)
         )),
         sep = "\n", collapse = "\n"
@@ -120,7 +120,7 @@ intradaily_variability <- function(Light.vector,
     sum(diff(total_hourly$Light)^2) / (length(total_hourly$Light) - 1)
 
   # Variance of consecutive differences / variance across all days
-  iv <- var_hourly_diff / var(total_hourly$Light)
+  iv <- var_hourly_diff / stats::var(total_hourly$Light)
 
   # Return data frame or numeric vector
   if (as.df) {