R/g.report.part4.R
In wadpac/GGIR: Raw Accelerometer Data Analysis
Defines functions
g.report.part4
Documented in
g.report.part4
g.report.part4 = function(datadir = c(), metadatadir = c(), f0 = c(), f1 = c(),
data_cleaning_file = c(), params_sleep, params_output,
verbose = TRUE) {
# description: function to merge generate report from milestone data generated by g.part4 (if store.ms was
# set to TRUE)
output = NULL
ms4.out = "/meta/ms4.out"
if (file.exists(paste(metadatadir, ms4.out, sep = ""))) {
if (length(dir(paste(metadatadir, ms4.out, sep = ""))) == 0) {
try.generate.report = FALSE
} else {
try.generate.report = TRUE
}
} else {
try.generate.report = FALSE
}
if (try.generate.report == TRUE) {
resultfolder = metadatadir #resultfolder = 'Q:/studies/sleep/output_pi_sleep_wrist'
meta.sleep.folder = paste(metadatadir, "/meta/ms3.out", sep = "")
if (length(params_sleep[["loglocation"]]) > 0) {
only.use.sleeplog = TRUE
} else {
only.use.sleeplog = FALSE
}
# ============================================================================ Go through
# accelerometer datafiles and merge with sleep log data
fnames = dir(meta.sleep.folder)
if (f1 > length(fnames)) {
if (verbose == TRUE) cat(paste0("\nf1 changed from, ", f1, " to ", length(fnames)))
f1 = length(fnames)
}
if (length(f1) == 0 | f1 > length(fnames))
f1 = length(fnames)
#-----------------------------------------------------
colnames_nightsummary2 = c("ID", "night", "sleeponset", "wakeup", "SptDuration", "sleepparam", "guider_onset",
"guider_wakeup", "guider_SptDuration", "error_onset", "error_wake", "error_dur", "fraction_night_invalid",
"SleepDurationInSpt", "WASO", "duration_sib_wakinghours", "number_sib_sleepperiod", "number_of_awakenings",
"number_sib_wakinghours", "duration_sib_wakinghours_atleast15min", "sleeponset_ts", "wakeup_ts", "guider_onset_ts",
"guider_wakeup_ts", "sleeplatency", "sleepefficiency", "page", "daysleeper", "weekday", "calendar_date",
"filename", "cleaningcode", "sleeplog_used", "sleeplog_ID", "acc_available", "guider", "SleepRegularityIndex", "SriFractionValid",
"longitudinal_axis")
nightsummary2 = as.data.frame(matrix(0, 0, length(colnames_nightsummary2)))
if (params_sleep[["sleepwindowType"]] == "TimeInBed") {
colnames(nightsummary2) = gsub(replacement = "guider_inbedStart", pattern = "guider_onset", x = colnames(nightsummary2))
colnames(nightsummary2) = gsub(replacement = "guider_inbedEnd", pattern = "guider_wakeup", x = colnames(nightsummary2))
colnames(nightsummary2) = gsub(replacement = "guider_inbedDuration", pattern = "guider_SptDuration",
x = colnames(nightsummary2))
}
sumi = 1
sleeplog_used = rep(" ", ((f1 - f0) + 1))
fnames.ms4 = list.files(paste0(metadatadir, ms4.out), full.names = TRUE)
if (length(fnames.ms4) < f1)
f1 = length(fnames.ms4)
if (verbose == TRUE) cat(" loading all the milestone data from part 4 this can take a few minutes\n")
myfun = function(x) {
tail_expansion_log = NULL
load(file = x)
cut = which(nightsummary[, 1] == "")
if (length(cut) > 0 & length(cut) < nrow(nightsummary)) {
nightsummary = nightsummary[-cut, ]
}
if (length(tail_expansion_log) != 0) {
nightsummary = nightsummary[-which(nightsummary$night == max(nightsummary$night)),] # remove last row because it may not be trustworthy
}
if ("GGIRversion" %in% colnames(nightsummary) == FALSE) {
if (nrow(nightsummary) > 0) {
nightsummary$GGIRversion = "" #before 3.0-10 this column did not exist
} else {
nightsummary[1, ] = NA
nightsummary$GGIRversion = NA
nightsummary = nightsummary[0, ]
}
}
out = as.matrix(nightsummary)
}
nightsummary2 = as.data.frame(do.call(rbind, lapply(fnames.ms4, myfun)), stringsAsFactors = FALSE)
nightsummary2$night = as.numeric(gsub(" ", "", nightsummary2$night))
nightsummary2$calendar_date = as.Date(nightsummary2$calendar_date, format = "%d/%m/%Y")
nightsummary2$calendar_date = format(nightsummary2$calendar_date, format = "%Y-%m-%d")
nightsummary2$filename = gsub(".RData$", "", nightsummary2$filename)
# ====================================== Add non-wearing during SPT from part 5, if it is availabe:
ms5.out = "/meta/ms5.out"
if (file.exists(paste(metadatadir, ms5.out, sep = ""))) {
if (length(dir(paste(metadatadir, ms5.out, sep = ""))) == 0) {
try.add.part5.variable = FALSE #do not run this function if there is no milestone data from g.part5
} else {
# check WW windows are calculated in the first file
load(dir(paste(metadatadir, ms5.out, sep = ""), full.names = T)[1]) # this loads object output
if ("WW" %in% output$window) {
try.add.part5.variable = TRUE
} else {
try.add.part5.variable = FALSE #do not run this function if WW windows are not calculated
}
}
} else {
try.add.part5.variable = FALSE #do not run this function if there is no milestone data from g.part5
}
if (try.add.part5.variable == TRUE) {
# ====================================================================== loop through meta-files
fnames.ms5 = list.files(paste0(metadatadir, ms5.out), full.names = TRUE)
if (f1 > length(fnames.ms5))
f1 = length(fnames.ms5)
# cat(' loading all the milestone data from part 5 this can take a few minutes\n')
myfun5 = function(x) {
load(file = x) # this loads the content of a RData file that has object output
cut = which(output[, 1] == "")
if (length(cut) > 0 & length(cut) < nrow(output)) {
output = output[-cut, which(colnames(output) != "")]
}
WW = which(output[, "window"] == "WW")
out = as.matrix(output[WW, which(colnames(output) %in% c("ID", "nonwear_perc_spt", "ACC_spt_mg", "night_number", "window"))])
}
outputp5 = as.data.frame(do.call(rbind, lapply(fnames.ms5[f0:f1], myfun5)), stringsAsFactors = FALSE)
dupl = which(duplicated(outputp5[, c("ID", "night_number")]) == TRUE)
# Note: another approach to removing duplicates could be to take the average...
if (length(dupl) > 0) {
# some days in part 5 can have two SPTs, remove first and keep second SPT
outputp5 = outputp5[-dupl, ] #-dupl2[1]
}
colnames(outputp5)[which(colnames(outputp5) == "night_number")] = "night"
# merge should now work, but if ID is numeric and stored as character with a leading zero then
# part 5 ID will not have this leading zero, so, we need fix this now:
remove_oldID = FALSE
if (is.character(nightsummary2$ID) & is.character(outputp5$ID)) {
options(warn = -1)
# next line could generate warning about NA creation when content is not numeric this is why
# we turn of warnings
testnumeric = !is.na(as.numeric(nightsummary2$ID))
options(warn = 0)
if (length(which(testnumeric == TRUE)) > (nrow(nightsummary2) * (2/3))) {
nightsummary2$ID_old = nightsummary2$ID
nightsummary2$ID = as.character(as.numeric(nightsummary2$ID))
remove_oldID = TRUE
}
}
# merge in variable
outputp5$night = as.numeric(outputp5$night)
nightsummary2 = base::merge(nightsummary2, outputp5, by = c("ID", "night"), all.x = TRUE)
if (remove_oldID == TRUE) {
nightsummary2$ID = nightsummary2$ID_old
nightsummary2 = nightsummary2[, -which(names(nightsummary2) == "ID_old")]
}
nightsummary2 = nightsummary2[order(nightsummary2$ID, nightsummary2$night), ]
nightsummary2$nonwear_perc_spt = as.numeric(nightsummary2$nonwear_perc_spt)
nightsummary2$ACC_spt_mg = as.numeric(nightsummary2$ACC_spt_mg)
}
# =============
skip = FALSE
if (length(nightsummary2) != 0) {
NumberNotNA = length(which(is.na(nightsummary2[, 3:25]) == FALSE))
if (NumberNotNA == 0) {
skip = TRUE
warning("\nCannot create report part 4 report, because no sleep estimates present in milestone data.", call. = FALSE)
}
} else {
skip = TRUE
warning("\nCannot create report part 4 report, because no milestone data found for part4.", call. = FALSE)
}
if (skip == FALSE) {
# skip if no data was loaded or if it all rows were NA values
#----------------
nightsummary = nightsummary2
pko = which(nightsummary$sleeponset == 0 & nightsummary$wakeup == 0 & nightsummary$SptDuration == 0)
if (length(pko) > 0) {
nightsummary = nightsummary[-pko, ]
}
##################################################### COLLAPSING nightsummary TO A ONELINE
##################################################### personsummary PER PARTICIPANT
if (nrow(nightsummary) == 0) {
if (verbose == TRUE) cat("report not stored, because no results available")
} else {
nightsummary_clean = tidyup_df(nightsummary)
data.table::fwrite(nightsummary_clean, file = paste(resultfolder, "/results/QC/part4_nightsummary_sleep_full.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
nightsummary_bu = nightsummary
}
####
summarynames_backup = c()
for (dotwice in 1:2) {
# store data twice, once full and once cleaned
if (dotwice == 2) {
# ignore nights that were derived without sleep log?
if (only.use.sleeplog == TRUE) {
del = which(nightsummary$cleaningcode > 0 | nightsummary$sleeplog_used == "FALSE" |
nightsummary$guider == "NotWorn" | nightsummary$guider == "NotWorn+invalid")
} else {
# only delete nights with no or no valid accelerometer data or when accelerometer not worn, but consider nights with
# missing sleep log data
del = which(nightsummary$cleaningcode > 1 | nightsummary$guider == "NotWorn" |
nightsummary$guider == "NotWorn+invalid")
}
if (length(del) > 0) {
nightsummary = nightsummary_bu[-del, ]
}
# Ignore nights based on data_cleaning_file if this is provided include_window = rep(TRUE,
# nrow(x)) allow for forced relying on guider based on external data_cleaning_file
if (length(data_cleaning_file) > 0) {
DaCleanFile = data.table::fread(data_cleaning_file, data.table = FALSE)
if ("night_part4" %in% colnames(DaCleanFile)) {
days2exclude = which(paste(nightsummary$ID, nightsummary$night) %in% paste(DaCleanFile$ID, DaCleanFile$night_part4))
if (length(days2exclude) > 0) {
nightsummary = nightsummary[-days2exclude, ]
}
}
}
# ignore also all columns related to error (difference between guider and final estimate,
# which were mainly used for methodological research
coldel = which(colnames(nightsummary) %in% c("error_onset", "error_wake", "error_dur") == TRUE)
if (length(coldel) > 0)
nightsummary = nightsummary[, -coldel]
}
NIDS = max(c(length(unique(nightsummary$filename)), length(unique(nightsummary$ID))))
NDEF = length(unique(nightsummary$sleepparam))
uuu = unique(nightsummary$sleepparam)
rem = which(uuu == 0 | uuu == "0" | is.na(uuu) == TRUE)
if (length(rem) > 0) {
uuu = uuu[-rem]
NDEF = length(uuu)
}
if (params_output[["storefolderstructure"]] == TRUE) {
personSummary = matrix(0, NIDS, ((NDEF * 3 * 22) + 15 + (6 * 3)))
} else {
personSummary = matrix(0, NIDS, ((NDEF * 3 * 22) + 13 + (6 * 3)))
}
# unique filenames, previously we used unique IDs, but that would not allow
# for repeated measurements of the same ID to be summarised separately
uniquefn = unique(nightsummary$filename)
if (nrow(nightsummary) > 0) {
for (i in 1:length(uniquefn)) {
personSummarynames = c() #moved here on 3/12/2014
# fully cleaned from nights that need to be deleted
this_file = which(nightsummary$filename == uniquefn[i])
nightsummary.tmp = nightsummary[this_file, ] #back up
udef = as.character(unique(nightsummary.tmp$sleepparam))
if (length(which(as.character(udef) == "0") > 0))
udef = udef[-c(which(as.character(udef) == "0"))]
udefn = udef
#-------------------------------------------
# general info about file
personSummary[i, 1] = nightsummary.tmp$ID[1] #id
personSummarynames = c(personSummarynames, "ID")
personSummary[i, 2] = uniquefn[i] #as.character(nightsummary$filename[which(nightsummary$ID == uid[i])][1]) #filename
if (length(unlist(strsplit(as.character(personSummary[i, 2]), ".RDa"))) > 1)
personSummary[i, 2] = unlist(strsplit(personSummary[i, 2], ".RDa"))[1]
personSummarynames = c(personSummarynames, "filename")
cntt = 2
personSummary[i, cntt + 1] = as.character(nightsummary$calendar_date[this_file[1]]) #date
personSummarynames = c(personSummarynames, "calendar_date")
personSummary[i, cntt + 2] = nightsummary$weekday[this_file[1]] #date
personSummarynames = c(personSummarynames, "weekday")
# sleep log used
personSummary[i, cntt + 3] = as.character(nightsummary.tmp$sleeplog_used[1])
personSummarynames = c(personSummarynames, paste("sleeplog_used", sep = ""))
this_sleepparam = which(nightsummary.tmp$sleepparam == udef[1])
# sleep log ID
personSummary[i, cntt + 4] = as.character(nightsummary.tmp$sleeplog_ID[1])
personSummarynames = c(personSummarynames, paste("sleeplog_ID", sep = ""))
# total number of nights with acceleration and accelerometer worn
personSummary[i, cntt + 5] = length(which((nightsummary.tmp$acc_available[this_sleepparam] == "TRUE" |
nightsummary.tmp$acc_available[this_sleepparam] == "1") &
nightsummary.tmp$cleaningcode[this_sleepparam] != 2))
personSummarynames = c(personSummarynames, paste("n_nights_acc", sep = ""))
# total number of nights with sleep log
n_nights_sleeplog = length(nightsummary.tmp$night[which(nightsummary.tmp$sleepparam == udef[1] &
nightsummary.tmp$guider == "sleeplog")]) # number of nights with sleeplog
personSummary[i, cntt + 6] = n_nights_sleeplog
personSummarynames = c(personSummarynames, paste("n_nights_sleeplog", sep = ""))
# total number of complete weekend and week nights
th3 = nightsummary.tmp$weekday[this_sleepparam]
if (only.use.sleeplog == TRUE) {
validcleaningcode = 0
} else if (only.use.sleeplog == FALSE) {
validcleaningcode = 1
}
personSummary[i, cntt + 7] = length(which(nightsummary.tmp$cleaningcode[this_sleepparam] <= validcleaningcode &
(th3 == "Friday" | th3 == "Saturday")))
personSummary[i, cntt + 8] = length(which(nightsummary.tmp$cleaningcode[this_sleepparam] <= validcleaningcode &
(th3 == "Monday" | th3 == "Tuesday" | th3 == "Wednesday" |
th3 == "Thursday" | th3 == "Sunday")))
personSummarynames = c(personSummarynames, paste("n_WE_nights_complete", sep = ""), paste("n_WD_nights_complete",
sep = ""))
# number of days with sleep during the day
personSummary[i, cntt + 9] = length(which(nightsummary.tmp$daysleep[this_sleepparam] == 1 &
(th3 == "Friday" | th3 == "Saturday")))
personSummary[i, cntt + 10] = length(which(nightsummary.tmp$daysleep[this_sleepparam] == 1 &
(th3 == "Monday" | th3 == "Tuesday" |
th3 == "Wednesday" | th3 == "Thursday" |
th3 == "Sunday")))
personSummarynames = c(personSummarynames, paste("n_WEnights_daysleeper", sep = ""), paste("n_WDnights_daysleeper",
sep = ""))
cnt = cntt + 10
#-------------------------------------------
# sleep log summary
turn_numeric = function(x, varnames) {
cnx = colnames(x)
for (i in 1:length(varnames)) {
if (varnames[i] %in% cnx) {
x[, varnames[i]] = as.numeric(x[, varnames[i]])
}
}
return(x)
}
if (params_sleep[["sleepwindowType"]] == "SPT") {
gdn = c("guider_SptDuration", "guider_onset", "guider_wakeup")
} else if (params_sleep[["sleepwindowType"]] == "TimeInBed") {
gdn = c("guider_inbedDuration", "guider_inbedStart", "guider_inbedEnd")
}
if (dotwice == 1) {
nightsummary.tmp = turn_numeric(x = nightsummary.tmp, varnames = gdn)
}
varnames_tmp = c("SptDuration", "sleeponset",
"wakeup", "WASO", "SleepDurationInSpt",
"number_sib_sleepperiod", "duration_sib_wakinghours",
"number_of_awakenings", "number_sib_wakinghours",
"duration_sib_wakinghours_atleast15min",
"sleeplatency", "sleepefficiency", "number_of_awakenings",
"guider_inbedDuration", "guider_inbedStart",
"guider_inbedEnd", "guider_SptDuration", "guider_onset",
"guider_wakeup", "SleepRegularityIndex",
"SriFractionValid")
nightsummary.tmp = turn_numeric(x = nightsummary.tmp,
varnames = varnames_tmp)
weekday = nightsummary.tmp$weekday[this_sleepparam]
if (dotwice == 1) {
for (k in 1:3) {
if (k == 1) {
TW = "AD"
Seli = 1:length(weekday)
} else if (k == 2) {
TW = "WD"
Seli = which(weekday == "Monday" | weekday == "Tuesday" | weekday == "Wednesday" | weekday ==
"Thursday" | weekday == "Sunday")
} else if (k == 3) {
TW = "WE"
Seli = which(weekday == "Friday" | weekday == "Saturday")
}
relevant_rows = this_sleepparam[Seli]
if (length(relevant_rows) > 0) {
for (gdni in 1:length(gdn)) {
personSummary[i, cnt + 1] = mean(nightsummary.tmp[relevant_rows, gdn[gdni]], na.rm = TRUE)
personSummary[i, cnt + 2] = sd(nightsummary.tmp[relevant_rows, gdn[gdni]], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste(gdn[gdni], "_", TW, "_mn", sep = ""),
paste(gdn[gdni], "_", TW, "_sd", sep = ""))
cnt = cnt + 2
}
}
if ("nonwear_perc_spt" %in% colnames(nightsummary.tmp)) {
personSummary[i, cnt + 1] = mean(nightsummary.tmp$nonwear_perc_spt[this_sleepparam[Seli]], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("nonwear_perc_spt_", TW, "_mn", sep = ""))
cnt = cnt + 1
}
if ("ACC_spt_mg" %in% colnames(nightsummary.tmp)) {
personSummary[i, cnt + 1] = mean(nightsummary.tmp$ACC_spt_mg[this_sleepparam[Seli]], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("ACC_spt_mg_", TW, "_mn", sep = ""))
cnt = cnt + 1
}
}
}
nightsummary$cleaningcode = as.numeric(nightsummary$cleaningcode)
nightsummary$ID = as.character(nightsummary$ID)
# uid = as.character(uid)
#-------------------------------------------
# accelerometer summary
#----------------------------------------------
if (only.use.sleeplog == FALSE) {
# when sleep log is not available
if (dotwice == 2) {
CRIT = which(nightsummary$filename == uniquefn[i] & (nightsummary$cleaningcode == 0 | nightsummary$cleaningcode ==
1))
} else {
CRIT = which(nightsummary$filename == uniquefn[i])
}
} else {
CRIT = which(nightsummary$filename == uniquefn[i] & nightsummary$cleaningcode == 0) #when sleep log is available
}
personSummarynames_backup = c()
if (length(CRIT) > 0) {
# summarise data if there is data
#-----------------------------------------------
for (j in 1:length(udef)) {
weekday = nightsummary.tmp$weekday[which(nightsummary.tmp$sleepparam == udef[j])]
for (k in 1:3) {
if (ncol(personSummary) < (cnt + 50)) {
# expand personSummary matrix if there is a change that is not big enough
expansion = matrix(NA, nrow(personSummary), 50)
if (nrow(expansion) != nrow(personSummary))
expansion = t(expansion)
personSummary = cbind(personSummary, expansion)
}
if (k == 1) {
TW = "AD"
Seli = 1:length(weekday)
} else if (k == 2) {
TW = "WD"
Seli = which(weekday == "Monday" | weekday == "Tuesday" | weekday == "Wednesday" | weekday ==
"Thursday" | weekday == "Sunday")
} else if (k == 3) {
TW = "WE"
Seli = which(weekday == "Friday" | weekday == "Saturday")
}
indexUdef = which(nightsummary.tmp$sleepparam == udef[j])[Seli]
personSummary[i, (cnt + 1)] = mean(nightsummary.tmp$SptDuration[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 2)] = sd(nightsummary.tmp$SptDuration[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SptDuration_", TW, "_", udefn[j], "_mn",
sep = ""), paste("SptDuration_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 3)] = mean(nightsummary.tmp$SleepDurationInSpt[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 4)] = sd(nightsummary.tmp$SleepDurationInSpt[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SleepDurationInSpt_", TW, "_", udefn[j],
"_mn", sep = ""), paste("SleepDurationInSpt_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 5)] = mean(nightsummary.tmp$WASO[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 6)] = sd(nightsummary.tmp$WASO[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("WASO_", TW, "_", udefn[j], "_mn", sep = ""),
paste("WASO_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 7)] = mean(nightsummary.tmp$duration_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 8)] = sd(nightsummary.tmp$duration_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("duration_sib_wakinghours_", TW, "_",
udefn[j], "_mn", sep = ""), paste("duration_sib_wakinghours_", TW, "_", udefn[j], "_sd",
sep = ""))
personSummary[i, (cnt + 9)] = mean(nightsummary.tmp$number_sib_sleepperiod[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 10)] = sd(nightsummary.tmp$number_sib_sleepperiod[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("number_sib_sleepperiod_", TW, "_", udefn[j],
"_mn", sep = ""), paste("number_sib_sleepperiod_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 11)] = mean(nightsummary.tmp$number_of_awakenings[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 12)] = sd(nightsummary.tmp$number_of_awakenings[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("number_of_awakenings_", TW, "_", udefn[j],
"_mn", sep = ""), paste("number_of_awakenings_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 13)] = mean(nightsummary.tmp$number_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 14)] = sd(nightsummary.tmp$number_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("number_sib_wakinghours_", TW, "_", udefn[j],
"_mn", sep = ""), paste("number_sib_wakinghours_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 15)] = mean(nightsummary.tmp$duration_sib_wakinghours_atleast15min[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 16)] = sd(nightsummary.tmp$duration_sib_wakinghours_atleast15min[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("duration_sib_wakinghours_atleast15min_",
TW, "_", udefn[j], "_mn", sep = ""), paste("duration_sib_wakinghours_atleast15min_",
TW, "_", udefn[j], "_sd", sep = ""))
# average sibd during the day
AVEsibdDUR = c(nightsummary.tmp$duration_sib_wakinghours[indexUdef]/nightsummary.tmp$number_sib_wakinghours[indexUdef])
if (length(which(nightsummary.tmp$number_sib_wakinghours[indexUdef] == 0))) {
AVEsibdDUR[which(nightsummary.tmp$number_sib_wakinghours[indexUdef] == 0)] = 0
}
personSummary[i, (cnt + 17)] = mean(AVEsibdDUR, na.rm = TRUE)
personSummary[i, (cnt + 18)] = sd(AVEsibdDUR, na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("average_dur_sib_wakinghours_", TW, "_",
udefn[j], "_mn", sep = ""), paste("average_dur_sib_wakinghours_", TW, "_", udefn[j],
"_sd", sep = ""))
NDAYsibd = length(which(nightsummary.tmp$number_sib_wakinghours[indexUdef] > 0))
if (length(NDAYsibd) == 0) NDAYsibd = 0
personSummary[i, (cnt + 19)] = NDAYsibd
personSummarynames = c(personSummarynames, paste("n_days_w_sib_wakinghours_", TW, "_",
udefn[j], sep = ""))
personSummary[i, (cnt + 20)] = mean(nightsummary.tmp$sleeponset[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 21)] = sd(nightsummary.tmp$sleeponset[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("sleeponset_", TW, "_", udefn[j], "_mn",
sep = ""), paste("sleeponset_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 22)] = mean(nightsummary.tmp$wakeup[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 23)] = sd(nightsummary.tmp$wakeup[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("wakeup_", TW, "_", udefn[j], "_mn",
sep = ""), paste("wakeup_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 24)] = mean(nightsummary.tmp$SleepRegularityIndex[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 25)] = sd(nightsummary.tmp$SleepRegularityIndex[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SleepRegularityIndex_", TW, "_", udefn[j],
"_mn", sep = ""), paste("SleepRegularityIndex_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 26)] = mean(nightsummary.tmp$SriFractionValid[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 27)] = sd(nightsummary.tmp$SriFractionValid[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SriFractionValid_", TW, "_", udefn[j],
"_mn", sep = ""), paste("SriFractionValid_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 27
if (params_sleep[["sleepwindowType"]] == "TimeInBed") {
sleepefficiency = nightsummary.tmp$sleepefficiency[indexUdef]
latency = nightsummary.tmp$sleeplatency[indexUdef]
if (params_sleep[["sib_must_fully_overlap_with_TimeInBed"]][1] == FALSE) {
negative_latency = which(latency < 0)
N_neg_lat = length(negative_latency)
if (N_neg_lat > 0) latency = latency[-negative_latency]
personSummary[i, (cnt + 1)] = N_neg_lat
personSummarynames = c(personSummarynames, "N_nights_negative_latency")
cnt = cnt + 1
Nlatency = length(latency)
if (Nlatency > 0) {
meanLatency = mean(latency, na.rm = TRUE)
meanSleepefficiency = mean(sleepefficiency, na.rm = TRUE)
} else {
meanLatency = NA
meanSleepefficiency = NA
}
if (Nlatency > 1) {
sdLatency = sd(latency, na.rm = TRUE)
sdSleepefficiency = sd(sleepefficiency, na.rm = TRUE)
} else {
sdLatency = NA
sdSleepefficiency = NA
}
} else {
meanLatency = mean(latency, na.rm = TRUE)
meanSleepefficiency = mean(sleepefficiency, na.rm = TRUE)
sdLatency = sd(latency, na.rm = TRUE)
sdSleepefficiency = sd(sleepefficiency, na.rm = TRUE)
}
personSummary[i, (cnt + 1)] = meanSleepefficiency
personSummary[i, (cnt + 2)] = sdSleepefficiency
personSummarynames = c(personSummarynames, paste("sleep_efficiency_", TW, "_", udefn[j],
"_mn", sep = ""), paste("sleep_efficiency_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 2
personSummary[i, (cnt + 1)] = meanLatency
personSummary[i, (cnt + 2)] = sdLatency
personSummarynames = c(personSummarynames, paste("sleeplatency_", TW, "_", udefn[j],
"_mn", sep = ""), paste("sleeplatency_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 3)] = mean(nightsummary.tmp$guider_inbedStart[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 4)] = sd(nightsummary.tmp$guider_inbedStart[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("guider_inbedStart_", TW, "_", udefn[j],
"_mn", sep = ""), paste("guider_inbedStart_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 4
personSummary[i, (cnt + 1)] = mean(nightsummary.tmp$guider_inbedEnd[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 2)] = sd(nightsummary.tmp$guider_inbedEnd[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("guider_inbedEnd_", TW, "_", udefn[j],
"_mn", sep = ""), paste("guider_inbedEnd_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 3)] = mean(nightsummary.tmp$guider_inbedDuration[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 4)] = sd(nightsummary.tmp$guider_inbedDuration[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("guider_inbedDuration_", TW, "_", udefn[j],
"_mn", sep = ""), paste("guider_inbedDuration_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 4
}
}
}
personSummary[i, cnt + 1] = as.character(nightsummary$GGIRversion[this_file[1]])
cnt = cnt + 1
personSummarynames = c(personSummarynames, "GGIRversion")
personSummarynames_backup = personSummarynames
}
}
# replace matrix values 'NA' and 'NaN' by empty cells
for (colli in 1:ncol(personSummary)) {
missingv = which(is.na(personSummary[, colli]) == TRUE |
personSummary[, colli] == "NA" |
personSummary[, colli] == "NaN")
if (length(missingv) > 0) {
personSummary[missingv, colli] = ""
}
}
personSummary = as.data.frame(personSummary, stringsAsFactors = TRUE)
if (length(personSummarynames) != ncol(personSummary)) {
if (length(personSummarynames_backup) > 0) {
names(personSummary) = personSummarynames_backup
} else {
if (length(personSummarynames) > ncol(personSummary)) {
names(personSummary)[1:length(personSummarynames)] = personSummarynames
} else {
names(personSummary) = personSummarynames[1:ncol(personSummary)]
}
}
} else {
names(personSummary) = personSummarynames
}
# remove empty columns in personpersonSummary, if any
emptycolumns = which(is.na(colnames(personSummary)) == TRUE)
if (length(emptycolumns) > 0) {
personSummary = personSummary[, -emptycolumns]
}
}
#######################################################
if (nrow(nightsummary) == 0) {
if (verbose == TRUE) {
if (dotwice == 1) {
cat("\npart 4 full report not stored, because no results available")
} else {
cat("\npart 4 cleaned report not stored, because no results available")
}
}
} else {
nightsummary_clean = tidyup_df(nightsummary)
personSummary_clean = tidyup_df(personSummary)
if (dotwice == 1) {
data.table::fwrite(nightsummary_clean, file = paste(resultfolder, "/results/QC/part4_nightsummary_sleep_full.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
data.table::fwrite(personSummary_clean, file = paste(resultfolder, "/results/QC/part4_summary_sleep_full.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
} else {
data.table::fwrite(nightsummary_clean, file = paste(resultfolder, "/results/part4_nightsummary_sleep_cleaned.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
data.table::fwrite(personSummary_clean, file = paste(resultfolder, "/results/part4_summary_sleep_cleaned.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
}
}
}
}
}
}
wadpac/GGIR documentation built on March 5, 2025, 11 p.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Defines functions g.report.part4
Documented in g.report.part4
g.report.part4 = function(datadir = c(), metadatadir = c(), f0 = c(), f1 = c(),
data_cleaning_file = c(), params_sleep, params_output,
verbose = TRUE) {
# description: function to merge generate report from milestone data generated by g.part4 (if store.ms was
# set to TRUE)
output = NULL
ms4.out = "/meta/ms4.out"
if (file.exists(paste(metadatadir, ms4.out, sep = ""))) {
if (length(dir(paste(metadatadir, ms4.out, sep = ""))) == 0) {
try.generate.report = FALSE
} else {
try.generate.report = TRUE
}
} else {
try.generate.report = FALSE
}
if (try.generate.report == TRUE) {
resultfolder = metadatadir #resultfolder = 'Q:/studies/sleep/output_pi_sleep_wrist'
meta.sleep.folder = paste(metadatadir, "/meta/ms3.out", sep = "")
if (length(params_sleep[["loglocation"]]) > 0) {
only.use.sleeplog = TRUE
} else {
only.use.sleeplog = FALSE
}
# ============================================================================ Go through
# accelerometer datafiles and merge with sleep log data
fnames = dir(meta.sleep.folder)
if (f1 > length(fnames)) {
if (verbose == TRUE) cat(paste0("\nf1 changed from, ", f1, " to ", length(fnames)))
f1 = length(fnames)
}
if (length(f1) == 0 | f1 > length(fnames))
f1 = length(fnames)
#-----------------------------------------------------
colnames_nightsummary2 = c("ID", "night", "sleeponset", "wakeup", "SptDuration", "sleepparam", "guider_onset",
"guider_wakeup", "guider_SptDuration", "error_onset", "error_wake", "error_dur", "fraction_night_invalid",
"SleepDurationInSpt", "WASO", "duration_sib_wakinghours", "number_sib_sleepperiod", "number_of_awakenings",
"number_sib_wakinghours", "duration_sib_wakinghours_atleast15min", "sleeponset_ts", "wakeup_ts", "guider_onset_ts",
"guider_wakeup_ts", "sleeplatency", "sleepefficiency", "page", "daysleeper", "weekday", "calendar_date",
"filename", "cleaningcode", "sleeplog_used", "sleeplog_ID", "acc_available", "guider", "SleepRegularityIndex", "SriFractionValid",
"longitudinal_axis")
nightsummary2 = as.data.frame(matrix(0, 0, length(colnames_nightsummary2)))
if (params_sleep[["sleepwindowType"]] == "TimeInBed") {
colnames(nightsummary2) = gsub(replacement = "guider_inbedStart", pattern = "guider_onset", x = colnames(nightsummary2))
colnames(nightsummary2) = gsub(replacement = "guider_inbedEnd", pattern = "guider_wakeup", x = colnames(nightsummary2))
colnames(nightsummary2) = gsub(replacement = "guider_inbedDuration", pattern = "guider_SptDuration",
x = colnames(nightsummary2))
}
sumi = 1
sleeplog_used = rep(" ", ((f1 - f0) + 1))
fnames.ms4 = list.files(paste0(metadatadir, ms4.out), full.names = TRUE)
if (length(fnames.ms4) < f1)
f1 = length(fnames.ms4)
if (verbose == TRUE) cat(" loading all the milestone data from part 4 this can take a few minutes\n")
myfun = function(x) {
tail_expansion_log = NULL
load(file = x)
cut = which(nightsummary[, 1] == "")
if (length(cut) > 0 & length(cut) < nrow(nightsummary)) {
nightsummary = nightsummary[-cut, ]
}
if (length(tail_expansion_log) != 0) {
nightsummary = nightsummary[-which(nightsummary$night == max(nightsummary$night)),] # remove last row because it may not be trustworthy
}
if ("GGIRversion" %in% colnames(nightsummary) == FALSE) {
if (nrow(nightsummary) > 0) {
nightsummary$GGIRversion = "" #before 3.0-10 this column did not exist
} else {
nightsummary[1, ] = NA
nightsummary$GGIRversion = NA
nightsummary = nightsummary[0, ]
}
}
out = as.matrix(nightsummary)
}
nightsummary2 = as.data.frame(do.call(rbind, lapply(fnames.ms4, myfun)), stringsAsFactors = FALSE)
nightsummary2$night = as.numeric(gsub(" ", "", nightsummary2$night))
nightsummary2$calendar_date = as.Date(nightsummary2$calendar_date, format = "%d/%m/%Y")
nightsummary2$calendar_date = format(nightsummary2$calendar_date, format = "%Y-%m-%d")
nightsummary2$filename = gsub(".RData$", "", nightsummary2$filename)
# ====================================== Add non-wearing during SPT from part 5, if it is availabe:
ms5.out = "/meta/ms5.out"
if (file.exists(paste(metadatadir, ms5.out, sep = ""))) {
if (length(dir(paste(metadatadir, ms5.out, sep = ""))) == 0) {
try.add.part5.variable = FALSE #do not run this function if there is no milestone data from g.part5
} else {
# check WW windows are calculated in the first file
load(dir(paste(metadatadir, ms5.out, sep = ""), full.names = T)[1]) # this loads object output
if ("WW" %in% output$window) {
try.add.part5.variable = TRUE
} else {
try.add.part5.variable = FALSE #do not run this function if WW windows are not calculated
}
}
} else {
try.add.part5.variable = FALSE #do not run this function if there is no milestone data from g.part5
}
if (try.add.part5.variable == TRUE) {
# ====================================================================== loop through meta-files
fnames.ms5 = list.files(paste0(metadatadir, ms5.out), full.names = TRUE)
if (f1 > length(fnames.ms5))
f1 = length(fnames.ms5)
# cat(' loading all the milestone data from part 5 this can take a few minutes\n')
myfun5 = function(x) {
load(file = x) # this loads the content of a RData file that has object output
cut = which(output[, 1] == "")
if (length(cut) > 0 & length(cut) < nrow(output)) {
output = output[-cut, which(colnames(output) != "")]
}
WW = which(output[, "window"] == "WW")
out = as.matrix(output[WW, which(colnames(output) %in% c("ID", "nonwear_perc_spt", "ACC_spt_mg", "night_number", "window"))])
}
outputp5 = as.data.frame(do.call(rbind, lapply(fnames.ms5[f0:f1], myfun5)), stringsAsFactors = FALSE)
dupl = which(duplicated(outputp5[, c("ID", "night_number")]) == TRUE)
# Note: another approach to removing duplicates could be to take the average...
if (length(dupl) > 0) {
# some days in part 5 can have two SPTs, remove first and keep second SPT
outputp5 = outputp5[-dupl, ] #-dupl2[1]
}
colnames(outputp5)[which(colnames(outputp5) == "night_number")] = "night"
# merge should now work, but if ID is numeric and stored as character with a leading zero then
# part 5 ID will not have this leading zero, so, we need fix this now:
remove_oldID = FALSE
if (is.character(nightsummary2$ID) & is.character(outputp5$ID)) {
options(warn = -1)
# next line could generate warning about NA creation when content is not numeric this is why
# we turn of warnings
testnumeric = !is.na(as.numeric(nightsummary2$ID))
options(warn = 0)
if (length(which(testnumeric == TRUE)) > (nrow(nightsummary2) * (2/3))) {
nightsummary2$ID_old = nightsummary2$ID
nightsummary2$ID = as.character(as.numeric(nightsummary2$ID))
remove_oldID = TRUE
}
}
# merge in variable
outputp5$night = as.numeric(outputp5$night)
nightsummary2 = base::merge(nightsummary2, outputp5, by = c("ID", "night"), all.x = TRUE)
if (remove_oldID == TRUE) {
nightsummary2$ID = nightsummary2$ID_old
nightsummary2 = nightsummary2[, -which(names(nightsummary2) == "ID_old")]
}
nightsummary2 = nightsummary2[order(nightsummary2$ID, nightsummary2$night), ]
nightsummary2$nonwear_perc_spt = as.numeric(nightsummary2$nonwear_perc_spt)
nightsummary2$ACC_spt_mg = as.numeric(nightsummary2$ACC_spt_mg)
}
# =============
skip = FALSE
if (length(nightsummary2) != 0) {
NumberNotNA = length(which(is.na(nightsummary2[, 3:25]) == FALSE))
if (NumberNotNA == 0) {
skip = TRUE
warning("\nCannot create report part 4 report, because no sleep estimates present in milestone data.", call. = FALSE)
}
} else {
skip = TRUE
warning("\nCannot create report part 4 report, because no milestone data found for part4.", call. = FALSE)
}
if (skip == FALSE) {
# skip if no data was loaded or if it all rows were NA values
#----------------
nightsummary = nightsummary2
pko = which(nightsummary$sleeponset == 0 & nightsummary$wakeup == 0 & nightsummary$SptDuration == 0)
if (length(pko) > 0) {
nightsummary = nightsummary[-pko, ]
}
##################################################### COLLAPSING nightsummary TO A ONELINE
##################################################### personsummary PER PARTICIPANT
if (nrow(nightsummary) == 0) {
if (verbose == TRUE) cat("report not stored, because no results available")
} else {
nightsummary_clean = tidyup_df(nightsummary)
data.table::fwrite(nightsummary_clean, file = paste(resultfolder, "/results/QC/part4_nightsummary_sleep_full.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
nightsummary_bu = nightsummary
}
####
summarynames_backup = c()
for (dotwice in 1:2) {
# store data twice, once full and once cleaned
if (dotwice == 2) {
# ignore nights that were derived without sleep log?
if (only.use.sleeplog == TRUE) {
del = which(nightsummary$cleaningcode > 0 | nightsummary$sleeplog_used == "FALSE" |
nightsummary$guider == "NotWorn" | nightsummary$guider == "NotWorn+invalid")
} else {
# only delete nights with no or no valid accelerometer data or when accelerometer not worn, but consider nights with
# missing sleep log data
del = which(nightsummary$cleaningcode > 1 | nightsummary$guider == "NotWorn" |
nightsummary$guider == "NotWorn+invalid")
}
if (length(del) > 0) {
nightsummary = nightsummary_bu[-del, ]
}
# Ignore nights based on data_cleaning_file if this is provided include_window = rep(TRUE,
# nrow(x)) allow for forced relying on guider based on external data_cleaning_file
if (length(data_cleaning_file) > 0) {
DaCleanFile = data.table::fread(data_cleaning_file, data.table = FALSE)
if ("night_part4" %in% colnames(DaCleanFile)) {
days2exclude = which(paste(nightsummary$ID, nightsummary$night) %in% paste(DaCleanFile$ID, DaCleanFile$night_part4))
if (length(days2exclude) > 0) {
nightsummary = nightsummary[-days2exclude, ]
}
}
}
# ignore also all columns related to error (difference between guider and final estimate,
# which were mainly used for methodological research
coldel = which(colnames(nightsummary) %in% c("error_onset", "error_wake", "error_dur") == TRUE)
if (length(coldel) > 0)
nightsummary = nightsummary[, -coldel]
}
NIDS = max(c(length(unique(nightsummary$filename)), length(unique(nightsummary$ID))))
NDEF = length(unique(nightsummary$sleepparam))
uuu = unique(nightsummary$sleepparam)
rem = which(uuu == 0 | uuu == "0" | is.na(uuu) == TRUE)
if (length(rem) > 0) {
uuu = uuu[-rem]
NDEF = length(uuu)
}
if (params_output[["storefolderstructure"]] == TRUE) {
personSummary = matrix(0, NIDS, ((NDEF * 3 * 22) + 15 + (6 * 3)))
} else {
personSummary = matrix(0, NIDS, ((NDEF * 3 * 22) + 13 + (6 * 3)))
}
# unique filenames, previously we used unique IDs, but that would not allow
# for repeated measurements of the same ID to be summarised separately
uniquefn = unique(nightsummary$filename)
if (nrow(nightsummary) > 0) {
for (i in 1:length(uniquefn)) {
personSummarynames = c() #moved here on 3/12/2014
# fully cleaned from nights that need to be deleted
this_file = which(nightsummary$filename == uniquefn[i])
nightsummary.tmp = nightsummary[this_file, ] #back up
udef = as.character(unique(nightsummary.tmp$sleepparam))
if (length(which(as.character(udef) == "0") > 0))
udef = udef[-c(which(as.character(udef) == "0"))]
udefn = udef
#-------------------------------------------
# general info about file
personSummary[i, 1] = nightsummary.tmp$ID[1] #id
personSummarynames = c(personSummarynames, "ID")
personSummary[i, 2] = uniquefn[i] #as.character(nightsummary$filename[which(nightsummary$ID == uid[i])][1]) #filename
if (length(unlist(strsplit(as.character(personSummary[i, 2]), ".RDa"))) > 1)
personSummary[i, 2] = unlist(strsplit(personSummary[i, 2], ".RDa"))[1]
personSummarynames = c(personSummarynames, "filename")
cntt = 2
personSummary[i, cntt + 1] = as.character(nightsummary$calendar_date[this_file[1]]) #date
personSummarynames = c(personSummarynames, "calendar_date")
personSummary[i, cntt + 2] = nightsummary$weekday[this_file[1]] #date
personSummarynames = c(personSummarynames, "weekday")
# sleep log used
personSummary[i, cntt + 3] = as.character(nightsummary.tmp$sleeplog_used[1])
personSummarynames = c(personSummarynames, paste("sleeplog_used", sep = ""))
this_sleepparam = which(nightsummary.tmp$sleepparam == udef[1])
# sleep log ID
personSummary[i, cntt + 4] = as.character(nightsummary.tmp$sleeplog_ID[1])
personSummarynames = c(personSummarynames, paste("sleeplog_ID", sep = ""))
# total number of nights with acceleration and accelerometer worn
personSummary[i, cntt + 5] = length(which((nightsummary.tmp$acc_available[this_sleepparam] == "TRUE" |
nightsummary.tmp$acc_available[this_sleepparam] == "1") &
nightsummary.tmp$cleaningcode[this_sleepparam] != 2))
personSummarynames = c(personSummarynames, paste("n_nights_acc", sep = ""))
# total number of nights with sleep log
n_nights_sleeplog = length(nightsummary.tmp$night[which(nightsummary.tmp$sleepparam == udef[1] &
nightsummary.tmp$guider == "sleeplog")]) # number of nights with sleeplog
personSummary[i, cntt + 6] = n_nights_sleeplog
personSummarynames = c(personSummarynames, paste("n_nights_sleeplog", sep = ""))
# total number of complete weekend and week nights
th3 = nightsummary.tmp$weekday[this_sleepparam]
if (only.use.sleeplog == TRUE) {
validcleaningcode = 0
} else if (only.use.sleeplog == FALSE) {
validcleaningcode = 1
}
personSummary[i, cntt + 7] = length(which(nightsummary.tmp$cleaningcode[this_sleepparam] <= validcleaningcode &
(th3 == "Friday" | th3 == "Saturday")))
personSummary[i, cntt + 8] = length(which(nightsummary.tmp$cleaningcode[this_sleepparam] <= validcleaningcode &
(th3 == "Monday" | th3 == "Tuesday" | th3 == "Wednesday" |
th3 == "Thursday" | th3 == "Sunday")))
personSummarynames = c(personSummarynames, paste("n_WE_nights_complete", sep = ""), paste("n_WD_nights_complete",
sep = ""))
# number of days with sleep during the day
personSummary[i, cntt + 9] = length(which(nightsummary.tmp$daysleep[this_sleepparam] == 1 &
(th3 == "Friday" | th3 == "Saturday")))
personSummary[i, cntt + 10] = length(which(nightsummary.tmp$daysleep[this_sleepparam] == 1 &
(th3 == "Monday" | th3 == "Tuesday" |
th3 == "Wednesday" | th3 == "Thursday" |
th3 == "Sunday")))
personSummarynames = c(personSummarynames, paste("n_WEnights_daysleeper", sep = ""), paste("n_WDnights_daysleeper",
sep = ""))
cnt = cntt + 10
#-------------------------------------------
# sleep log summary
turn_numeric = function(x, varnames) {
cnx = colnames(x)
for (i in 1:length(varnames)) {
if (varnames[i] %in% cnx) {
x[, varnames[i]] = as.numeric(x[, varnames[i]])
}
}
return(x)
}
if (params_sleep[["sleepwindowType"]] == "SPT") {
gdn = c("guider_SptDuration", "guider_onset", "guider_wakeup")
} else if (params_sleep[["sleepwindowType"]] == "TimeInBed") {
gdn = c("guider_inbedDuration", "guider_inbedStart", "guider_inbedEnd")
}
if (dotwice == 1) {
nightsummary.tmp = turn_numeric(x = nightsummary.tmp, varnames = gdn)
}
varnames_tmp = c("SptDuration", "sleeponset",
"wakeup", "WASO", "SleepDurationInSpt",
"number_sib_sleepperiod", "duration_sib_wakinghours",
"number_of_awakenings", "number_sib_wakinghours",
"duration_sib_wakinghours_atleast15min",
"sleeplatency", "sleepefficiency", "number_of_awakenings",
"guider_inbedDuration", "guider_inbedStart",
"guider_inbedEnd", "guider_SptDuration", "guider_onset",
"guider_wakeup", "SleepRegularityIndex",
"SriFractionValid")
nightsummary.tmp = turn_numeric(x = nightsummary.tmp,
varnames = varnames_tmp)
weekday = nightsummary.tmp$weekday[this_sleepparam]
if (dotwice == 1) {
for (k in 1:3) {
if (k == 1) {
TW = "AD"
Seli = 1:length(weekday)
} else if (k == 2) {
TW = "WD"
Seli = which(weekday == "Monday" | weekday == "Tuesday" | weekday == "Wednesday" | weekday ==
"Thursday" | weekday == "Sunday")
} else if (k == 3) {
TW = "WE"
Seli = which(weekday == "Friday" | weekday == "Saturday")
}
relevant_rows = this_sleepparam[Seli]
if (length(relevant_rows) > 0) {
for (gdni in 1:length(gdn)) {
personSummary[i, cnt + 1] = mean(nightsummary.tmp[relevant_rows, gdn[gdni]], na.rm = TRUE)
personSummary[i, cnt + 2] = sd(nightsummary.tmp[relevant_rows, gdn[gdni]], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste(gdn[gdni], "_", TW, "_mn", sep = ""),
paste(gdn[gdni], "_", TW, "_sd", sep = ""))
cnt = cnt + 2
}
}
if ("nonwear_perc_spt" %in% colnames(nightsummary.tmp)) {
personSummary[i, cnt + 1] = mean(nightsummary.tmp$nonwear_perc_spt[this_sleepparam[Seli]], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("nonwear_perc_spt_", TW, "_mn", sep = ""))
cnt = cnt + 1
}
if ("ACC_spt_mg" %in% colnames(nightsummary.tmp)) {
personSummary[i, cnt + 1] = mean(nightsummary.tmp$ACC_spt_mg[this_sleepparam[Seli]], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("ACC_spt_mg_", TW, "_mn", sep = ""))
cnt = cnt + 1
}
}
}
nightsummary$cleaningcode = as.numeric(nightsummary$cleaningcode)
nightsummary$ID = as.character(nightsummary$ID)
# uid = as.character(uid)
#-------------------------------------------
# accelerometer summary
#----------------------------------------------
if (only.use.sleeplog == FALSE) {
# when sleep log is not available
if (dotwice == 2) {
CRIT = which(nightsummary$filename == uniquefn[i] & (nightsummary$cleaningcode == 0 | nightsummary$cleaningcode ==
1))
} else {
CRIT = which(nightsummary$filename == uniquefn[i])
}
} else {
CRIT = which(nightsummary$filename == uniquefn[i] & nightsummary$cleaningcode == 0) #when sleep log is available
}
personSummarynames_backup = c()
if (length(CRIT) > 0) {
# summarise data if there is data
#-----------------------------------------------
for (j in 1:length(udef)) {
weekday = nightsummary.tmp$weekday[which(nightsummary.tmp$sleepparam == udef[j])]
for (k in 1:3) {
if (ncol(personSummary) < (cnt + 50)) {
# expand personSummary matrix if there is a change that is not big enough
expansion = matrix(NA, nrow(personSummary), 50)
if (nrow(expansion) != nrow(personSummary))
expansion = t(expansion)
personSummary = cbind(personSummary, expansion)
}
if (k == 1) {
TW = "AD"
Seli = 1:length(weekday)
} else if (k == 2) {
TW = "WD"
Seli = which(weekday == "Monday" | weekday == "Tuesday" | weekday == "Wednesday" | weekday ==
"Thursday" | weekday == "Sunday")
} else if (k == 3) {
TW = "WE"
Seli = which(weekday == "Friday" | weekday == "Saturday")
}
indexUdef = which(nightsummary.tmp$sleepparam == udef[j])[Seli]
personSummary[i, (cnt + 1)] = mean(nightsummary.tmp$SptDuration[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 2)] = sd(nightsummary.tmp$SptDuration[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SptDuration_", TW, "_", udefn[j], "_mn",
sep = ""), paste("SptDuration_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 3)] = mean(nightsummary.tmp$SleepDurationInSpt[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 4)] = sd(nightsummary.tmp$SleepDurationInSpt[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SleepDurationInSpt_", TW, "_", udefn[j],
"_mn", sep = ""), paste("SleepDurationInSpt_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 5)] = mean(nightsummary.tmp$WASO[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 6)] = sd(nightsummary.tmp$WASO[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("WASO_", TW, "_", udefn[j], "_mn", sep = ""),
paste("WASO_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 7)] = mean(nightsummary.tmp$duration_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 8)] = sd(nightsummary.tmp$duration_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("duration_sib_wakinghours_", TW, "_",
udefn[j], "_mn", sep = ""), paste("duration_sib_wakinghours_", TW, "_", udefn[j], "_sd",
sep = ""))
personSummary[i, (cnt + 9)] = mean(nightsummary.tmp$number_sib_sleepperiod[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 10)] = sd(nightsummary.tmp$number_sib_sleepperiod[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("number_sib_sleepperiod_", TW, "_", udefn[j],
"_mn", sep = ""), paste("number_sib_sleepperiod_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 11)] = mean(nightsummary.tmp$number_of_awakenings[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 12)] = sd(nightsummary.tmp$number_of_awakenings[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("number_of_awakenings_", TW, "_", udefn[j],
"_mn", sep = ""), paste("number_of_awakenings_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 13)] = mean(nightsummary.tmp$number_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 14)] = sd(nightsummary.tmp$number_sib_wakinghours[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("number_sib_wakinghours_", TW, "_", udefn[j],
"_mn", sep = ""), paste("number_sib_wakinghours_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 15)] = mean(nightsummary.tmp$duration_sib_wakinghours_atleast15min[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 16)] = sd(nightsummary.tmp$duration_sib_wakinghours_atleast15min[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("duration_sib_wakinghours_atleast15min_",
TW, "_", udefn[j], "_mn", sep = ""), paste("duration_sib_wakinghours_atleast15min_",
TW, "_", udefn[j], "_sd", sep = ""))
# average sibd during the day
AVEsibdDUR = c(nightsummary.tmp$duration_sib_wakinghours[indexUdef]/nightsummary.tmp$number_sib_wakinghours[indexUdef])
if (length(which(nightsummary.tmp$number_sib_wakinghours[indexUdef] == 0))) {
AVEsibdDUR[which(nightsummary.tmp$number_sib_wakinghours[indexUdef] == 0)] = 0
}
personSummary[i, (cnt + 17)] = mean(AVEsibdDUR, na.rm = TRUE)
personSummary[i, (cnt + 18)] = sd(AVEsibdDUR, na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("average_dur_sib_wakinghours_", TW, "_",
udefn[j], "_mn", sep = ""), paste("average_dur_sib_wakinghours_", TW, "_", udefn[j],
"_sd", sep = ""))
NDAYsibd = length(which(nightsummary.tmp$number_sib_wakinghours[indexUdef] > 0))
if (length(NDAYsibd) == 0) NDAYsibd = 0
personSummary[i, (cnt + 19)] = NDAYsibd
personSummarynames = c(personSummarynames, paste("n_days_w_sib_wakinghours_", TW, "_",
udefn[j], sep = ""))
personSummary[i, (cnt + 20)] = mean(nightsummary.tmp$sleeponset[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 21)] = sd(nightsummary.tmp$sleeponset[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("sleeponset_", TW, "_", udefn[j], "_mn",
sep = ""), paste("sleeponset_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 22)] = mean(nightsummary.tmp$wakeup[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 23)] = sd(nightsummary.tmp$wakeup[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("wakeup_", TW, "_", udefn[j], "_mn",
sep = ""), paste("wakeup_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 24)] = mean(nightsummary.tmp$SleepRegularityIndex[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 25)] = sd(nightsummary.tmp$SleepRegularityIndex[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SleepRegularityIndex_", TW, "_", udefn[j],
"_mn", sep = ""), paste("SleepRegularityIndex_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 26)] = mean(nightsummary.tmp$SriFractionValid[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 27)] = sd(nightsummary.tmp$SriFractionValid[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("SriFractionValid_", TW, "_", udefn[j],
"_mn", sep = ""), paste("SriFractionValid_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 27
if (params_sleep[["sleepwindowType"]] == "TimeInBed") {
sleepefficiency = nightsummary.tmp$sleepefficiency[indexUdef]
latency = nightsummary.tmp$sleeplatency[indexUdef]
if (params_sleep[["sib_must_fully_overlap_with_TimeInBed"]][1] == FALSE) {
negative_latency = which(latency < 0)
N_neg_lat = length(negative_latency)
if (N_neg_lat > 0) latency = latency[-negative_latency]
personSummary[i, (cnt + 1)] = N_neg_lat
personSummarynames = c(personSummarynames, "N_nights_negative_latency")
cnt = cnt + 1
Nlatency = length(latency)
if (Nlatency > 0) {
meanLatency = mean(latency, na.rm = TRUE)
meanSleepefficiency = mean(sleepefficiency, na.rm = TRUE)
} else {
meanLatency = NA
meanSleepefficiency = NA
}
if (Nlatency > 1) {
sdLatency = sd(latency, na.rm = TRUE)
sdSleepefficiency = sd(sleepefficiency, na.rm = TRUE)
} else {
sdLatency = NA
sdSleepefficiency = NA
}
} else {
meanLatency = mean(latency, na.rm = TRUE)
meanSleepefficiency = mean(sleepefficiency, na.rm = TRUE)
sdLatency = sd(latency, na.rm = TRUE)
sdSleepefficiency = sd(sleepefficiency, na.rm = TRUE)
}
personSummary[i, (cnt + 1)] = meanSleepefficiency
personSummary[i, (cnt + 2)] = sdSleepefficiency
personSummarynames = c(personSummarynames, paste("sleep_efficiency_", TW, "_", udefn[j],
"_mn", sep = ""), paste("sleep_efficiency_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 2
personSummary[i, (cnt + 1)] = meanLatency
personSummary[i, (cnt + 2)] = sdLatency
personSummarynames = c(personSummarynames, paste("sleeplatency_", TW, "_", udefn[j],
"_mn", sep = ""), paste("sleeplatency_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 3)] = mean(nightsummary.tmp$guider_inbedStart[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 4)] = sd(nightsummary.tmp$guider_inbedStart[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("guider_inbedStart_", TW, "_", udefn[j],
"_mn", sep = ""), paste("guider_inbedStart_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 4
personSummary[i, (cnt + 1)] = mean(nightsummary.tmp$guider_inbedEnd[indexUdef], na.rm = TRUE)
personSummary[i, (cnt + 2)] = sd(nightsummary.tmp$guider_inbedEnd[indexUdef], na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("guider_inbedEnd_", TW, "_", udefn[j],
"_mn", sep = ""), paste("guider_inbedEnd_", TW, "_", udefn[j], "_sd", sep = ""))
personSummary[i, (cnt + 3)] = mean(nightsummary.tmp$guider_inbedDuration[indexUdef],
na.rm = TRUE)
personSummary[i, (cnt + 4)] = sd(nightsummary.tmp$guider_inbedDuration[indexUdef],
na.rm = TRUE)
personSummarynames = c(personSummarynames, paste("guider_inbedDuration_", TW, "_", udefn[j],
"_mn", sep = ""), paste("guider_inbedDuration_", TW, "_", udefn[j], "_sd", sep = ""))
cnt = cnt + 4
}
}
}
personSummary[i, cnt + 1] = as.character(nightsummary$GGIRversion[this_file[1]])
cnt = cnt + 1
personSummarynames = c(personSummarynames, "GGIRversion")
personSummarynames_backup = personSummarynames
}
}
# replace matrix values 'NA' and 'NaN' by empty cells
for (colli in 1:ncol(personSummary)) {
missingv = which(is.na(personSummary[, colli]) == TRUE |
personSummary[, colli] == "NA" |
personSummary[, colli] == "NaN")
if (length(missingv) > 0) {
personSummary[missingv, colli] = ""
}
}
personSummary = as.data.frame(personSummary, stringsAsFactors = TRUE)
if (length(personSummarynames) != ncol(personSummary)) {
if (length(personSummarynames_backup) > 0) {
names(personSummary) = personSummarynames_backup
} else {
if (length(personSummarynames) > ncol(personSummary)) {
names(personSummary)[1:length(personSummarynames)] = personSummarynames
} else {
names(personSummary) = personSummarynames[1:ncol(personSummary)]
}
}
} else {
names(personSummary) = personSummarynames
}
# remove empty columns in personpersonSummary, if any
emptycolumns = which(is.na(colnames(personSummary)) == TRUE)
if (length(emptycolumns) > 0) {
personSummary = personSummary[, -emptycolumns]
}
}
#######################################################
if (nrow(nightsummary) == 0) {
if (verbose == TRUE) {
if (dotwice == 1) {
cat("\npart 4 full report not stored, because no results available")
} else {
cat("\npart 4 cleaned report not stored, because no results available")
}
}
} else {
nightsummary_clean = tidyup_df(nightsummary)
personSummary_clean = tidyup_df(personSummary)
if (dotwice == 1) {
data.table::fwrite(nightsummary_clean, file = paste(resultfolder, "/results/QC/part4_nightsummary_sleep_full.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
data.table::fwrite(personSummary_clean, file = paste(resultfolder, "/results/QC/part4_summary_sleep_full.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
} else {
data.table::fwrite(nightsummary_clean, file = paste(resultfolder, "/results/part4_nightsummary_sleep_cleaned.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
data.table::fwrite(personSummary_clean, file = paste(resultfolder, "/results/part4_summary_sleep_cleaned.csv",
sep = ""), row.names = FALSE, na = "",
sep = params_output[["sep_reports"]],
dec = params_output[["dec_reports"]])
}
}
}
}
}
}
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Embedding an R snippet on your website
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.