limit line lengths to 80 char

styler package seemed to break the 80-character rule -- perhaps we should reach out to them. also note there is one lingering long line in test-print-and-summary that I'm not yet sure how to break up

R/data_analysis_functions.R

@@ -245,7 +245,8 @@ analyze_workloop <- function(x,
   x_by_cycle <- lapply(cycle_names, function(cycle) x[x$Cycle == cycle, ])
 
   # create a percent cycle index column
-  percent_of_cycle <- lapply(x_by_cycle, function(x) seq(0, 100, 100 / (nrow(x) - 1)))
+  percent_of_cycle <- lapply(x_by_cycle, function(x)
+    seq(0, 100, 100 / (nrow(x) - 1)))
 
   # work is calculated as the path integral of Force with respect to Position
   # (displacement)
@@ -285,7 +286,9 @@ analyze_workloop <- function(x,
   # and force. However since velocity is calculated between two time points,
   # corresponding pairs of force measurements are averaged first
   # the result is divided by 1000 to convert mW to W
-  instant_power <- mapply(function(x, v) x$Force * v / 1000, x_by_cycle, filt_velocity,
+  instant_power <- mapply(function(x, v) x$Force * v / 1000,
+                          x_by_cycle,
+                          filt_velocity,
     SIMPLIFY = FALSE
   )
 
@@ -421,7 +424,8 @@ time_correct <- function(x) {
       (utils::tail(x$mtime, 1) - utils::head(x$mtime, 1)) * (x$mtime -
         utils::head(x$mtime, 1))
   x$Time_Corrected_Power <-
-    x$Mean_Power - (utils::tail(x$Mean_Power, 1) - utils::head(x$Mean_Power, 1)) /
+    x$Mean_Power - (utils::tail(x$Mean_Power, 1) - utils::head(x$Mean_Power,
+                                                               1)) /
       (utils::tail(x$mtime, 1) - utils::head(x$mtime, 1)) * (x$mtime -
         utils::head(x$mtime, 1))
   attr(x, "power_difference") <-

R/data_import_functions.R

@@ -155,13 +155,16 @@ summary.muscle_stim <- function(object, ...) {
   print_muscle_stim_header(object, ...)
   cat(paste0("\nFile ID: ", attr(object, "file_id")))
   cat(paste0("\nMod Time (mtime): ", attr(object, "mtime")))
-  cat(paste0("\nSample Frequency: ", attr(object, "sample_frequency"), "Hz\n\n"))
+  cat(paste0("\nSample Frequency: ", attr(object, "sample_frequency"),
+             "Hz\n\n"))
   cat(paste0("data.frame Columns: \n"))
   for (i in 2:ncol(object)) {
-    cat(paste0("  ", colnames(object)[i], " (", attr(object, "units")[i], ")\n"))
+    cat(paste0("  ", colnames(object)[i], " (", attr(object, "units")[i],
+               ")\n"))
   }
   cat(paste0("\nStimulus Offset: ", attr(object, "stimulus_offset"), "s\n"))
-  cat(paste0("Stimulus Frequency: ", attr(object, "stimulus_frequency"), "Hz\n"))
+  cat(paste0("Stimulus Frequency: ", attr(object, "stimulus_frequency"),
+             "Hz\n"))
   cat(paste0("Stimulus Width: ", attr(object, "stimulus_width"), "ms\n"))
   cat(paste0("Stimulus Pulses: ", attr(object, "stimulus_pulses"), "\n"))
   cat(paste0("Gear Ratio: ", attr(object, "gear_ratio"), "\n"))
@@ -371,7 +374,8 @@ as_muscle_stim <- function(x,
   attr(x, "sample_frequency") <- sample_frequency
   if (is.na(attr(x, "gear_ratio"))) attr(x, "gear_ratio") <- 1
   if (type == "workloop") {
-    if (is.na(attr(x, "position_inverted"))) attr(x, "position_inverted") <- FALSE
+    if (is.na(attr(x, "position_inverted")))
+      attr(x, "position_inverted") <- FALSE
   }
 
   # Assign classes and return
@@ -647,7 +651,9 @@ read_ddf_dir <- function(file_path,
                          sort_by = "mtime",
                          ...) {
   # Generate list of file_names
-  file_name_list <- list.files(path = file_path, pattern = pattern, full.names = TRUE)
+  file_name_list <- list.files(path = file_path,
+                               pattern = pattern,
+                               full.names = TRUE)
   if (length(file_name_list) == 0) {
     stop("No files matching the pattern found at the given directory!")
   }
@@ -661,7 +667,8 @@ read_ddf_dir <- function(file_path,
             \nDefaulting to `mtime`.")
     sort_by <- "mtime"
   }
-  ms_list <- ms_list[order(unlist(lapply(ms_list, function(i) attr(i, sort_by))))]
+  ms_list <- ms_list[order(unlist(lapply(ms_list, function(i)
+    attr(i, sort_by))))]
 
   return(ms_list)
 }
@@ -715,13 +722,19 @@ read_wl_ddf <-
     # get info on experimental parameters
     stim_table <-
       utils::read.table(
-        text = protocol_table[grepl("Stim", protocol_table$Then.action), "Units"],
+        text = protocol_table[grepl("Stim", protocol_table$Then.action),
+                              "Units"],
         sep = ",",
-        col.names = c("offset", "frequency", "width", "pulses", "cycle_frequency")
+        col.names = c("offset",
+                      "frequency",
+                      "width",
+                      "pulses",
+                      "cycle_frequency")
       )
     cycle_table <-
       utils::read.table(
-        text = protocol_table[grepl("Sine", protocol_table$Then.action), "Units"],
+        text = protocol_table[grepl("Sine", protocol_table$Then.action),
+                              "Units"],
         sep = ",",
         col.names = c("frequency", "amplitude", "total_cycles")
       )
@@ -761,7 +774,8 @@ read_twitch_ddf <-
     # get info on experimental parameters
     stim_table <-
       utils::read.table(
-        text = protocol_table[grepl("Stim", protocol_table$Then.action), "Units"],
+        text = protocol_table[grepl("Stim", protocol_table$Then.action),
+                              "Units"],
         sep = ",",
         col.names = c("offset", "width")
       )
@@ -801,7 +815,8 @@ read_tetanus_ddf <-
     # get info on experimental parameters
     stim_table <-
       utils::read.table(
-        text = protocol_table[grepl("Stim", protocol_table$Then.action), "Units"],
+        text = protocol_table[grepl("Stim", protocol_table$Then.action),
+                              "Units"],
         sep = ",",
         col.names = c("offset", "frequency", "width", "length")
       )
@@ -1051,7 +1066,9 @@ read_analyze_wl_dir <- function(file_path,
                                 sort_by = "mtime",
                                 ...) {
   # Generate list of file_names
-  file_name_list <- list.files(path = file_path, pattern = pattern, full.names = TRUE)
+  file_name_list <- list.files(path = file_path,
+                               pattern = pattern,
+                               full.names = TRUE)
   if (length(file_name_list) == 0) {
     stop("No files matching the pattern found at the given directory!")
   }
@@ -1065,7 +1082,8 @@ read_analyze_wl_dir <- function(file_path,
             \nDefaulting to `mtime`.")
     sort_by <- "mtime"
   }
-  return(wl_list <- wl_list[order(unlist(lapply(wl_list, function(i) attr(i, sort_by))))])
+  return(wl_list <- wl_list[order(unlist(lapply(wl_list, function(i)
+    attr(i, sort_by))))])
 }
 
 ######################### summarize sequence of work loops #####################
@@ -1137,23 +1155,32 @@ summarize_wl_trials <- function(wl_list) {
   if (class(wl_list)[[1]] != "list") {
     stop("Please provide a list of analyzed workloop objects")
   }
-  if (!all(unlist(lapply(wl_list, function(x) "analyzed_workloop" %in% class(x))))) {
+  if (!all(unlist(lapply(wl_list,
+                         function(x) "analyzed_workloop" %in% class(x))))) {
     stop("The provided list includes elements that are
          not analyzed workloop objects")
   }
 
   summarized <- data.frame(
-    File_ID = vapply(wl_list, function(i) attr(i, "file_id"), character(1)),
-    Cycle_Frequency = vapply(wl_list, function(i) attr(i, "cycle_frequency"), numeric(1)),
-    Amplitude = vapply(wl_list, function(i) attr(i, "amplitude"), numeric(1)),
-    Phase = vapply(wl_list, function(i) attr(i, "phase"), numeric(1)),
-    Stimulus_Pulses = vapply(wl_list, function(i) attr(i, "stimulus_pulses"), numeric(1)),
+    File_ID = vapply(wl_list, function(i) attr(i, "file_id"),
+                     character(1)),
+    Cycle_Frequency = vapply(wl_list, function(i) attr(i, "cycle_frequency"),
+                             numeric(1)),
+    Amplitude = vapply(wl_list, function(i) attr(i, "amplitude"),
+                       numeric(1)),
+    Phase = vapply(wl_list, function(i) attr(i, "phase"),
+                   numeric(1)),
+    Stimulus_Pulses = vapply(wl_list, function(i) attr(i, "stimulus_pulses"),
+                             numeric(1)),
     Stimulus_Frequency = vapply(wl_list, function(i) {
       attr(i, "stimulus_frequency")
     }, numeric(1)),
-    mtime = vapply(wl_list, function(i) attr(i, "mtime"), numeric(1)),
-    Mean_Work = vapply(wl_list, function(i) mean(attr(i, "summary")$Work), numeric(1)),
-    Mean_Power = vapply(wl_list, function(i) mean(attr(i, "summary")$Net_Power), numeric(1))
+    mtime = vapply(wl_list, function(i) attr(i, "mtime"),
+                   numeric(1)),
+    Mean_Work = vapply(wl_list, function(i) mean(attr(i, "summary")$Work),
+                       numeric(1)),
+    Mean_Power = vapply(wl_list, function(i) mean(attr(i, "summary")$Net_Power),
+                        numeric(1))
   )
 
   return(summarized)

R/data_transformation_functions.R

@@ -155,7 +155,8 @@ select_cycles <- function(x,
   }
   x <- x[x$Cycle %in% keep_cycles, ]
   x$Cycle <- letters[as.factor(x$Cycle)]
-  if (!all(is.na(attr(x, "units")))) attr(x, "units") <- c(attr(x, "units"), "letters")
+  if (!all(is.na(attr(x, "units")))) attr(x, "units") <- c(attr(x, "units"),
+                                                           "letters")
   attr(x, "retained_cycles") <- keep_cycles
   return(x)
 }

R/workloopR.R

@@ -17,10 +17,10 @@
 #' loop experiment (\code{select_cycles()}).
 #'
 #' Core data analytical functions include \code{analyze_workloop()} for work
-#' loop files and \code{isometric_timing()} for twitches. \code{analyze_workloop()}
-#' computes instantaneous velocity, net work, instantaneous power, and net power
-#' for work loop experiments on a per-cycle basis. \code{isometric_timing()}
-#' provides summarization of twitch kinetics.
+#' loop files and \code{isometric_timing()} for twitches.
+#' \code{analyze_workloop()} computes instantaneous velocity, net work,
+#' instantaneous power, and net power for work loop experiments on a per-cycle
+#' basis. \code{isometric_timing()} provides summarization of twitch kinetics.
 #'
 #' Some functions are readily available for batch processing of files. The
 #' \code{read_analyze_wl_dir()} function allows for the batch import, cycle