#369 completing the addition of BrondCounts as optional metric

R/g.applymetrics.R

@@ -286,14 +286,19 @@ epochsize = ws3 #epochsize in seconds
   #================================================
   # Brond Counts
   if (do.brondcounts == TRUE) {
-    if (ncol(data) == 4) data= data[,2:4]
-    mycounts = activityCounts::counts(data=data, hertz=sf,
+    if (ncol(data) > 3) data= data[,2:4]
+    mycounts = activityCounts::counts(data=data, hertz=sf, 
                       x_axis=1, y_axis=2, z_axis=3,
                       start_time = Sys.time()) # ignoring timestamps, because GGIR has its own timestamps
-    allmetrics$BrondCount_x = mycounts[, 2]
-    allmetrics$BrondCount_y = mycounts[, 3]
-    allmetrics$BrondCount_z = mycounts[, 4]
+    if (sf < 30) {
+      warning("\nNote: activityCounts not designed for handling sample frequencies below 30 Hertz")
+    }
+    # activityCount output is per second
+    # aggregate to our epoch size:
+    allmetrics$BrondCount_x = sumPerEpoch(mycounts[,2], sf=1, epochsize)
+    allmetrics$BrondCount_y = sumPerEpoch(mycounts[,3], sf=1, epochsize)
+    allmetrics$BrondCount_z = sumPerEpoch(mycounts[,4], sf=1, epochsize)
   }
-
   return(allmetrics)
 } 
+

R/g.getmeta.R

@@ -172,7 +172,7 @@ g.getmeta = function(datafile,desiredtz = "",windowsizes = c(5,900,3600),
   if (sf == 0) stop("Sample frequency not recognised") #assume 80Hertz in the absense of any other info
   header = INFI$header
   options(warn=-1)
-  if (useRDA == FALSE) decn =g.dotorcomma(datafile,dformat,mon=mon, desiredtz=desiredtz, rmc.dec = rmc.dec)
+  if (useRDA == FALSE) decn =g.dotorcomma(datafile, dformat, mon=mon, desiredtz=desiredtz, rmc.dec = rmc.dec)
   options(warn=0)
 
   ID = g.getidfromheaderobject(filename=filename,header=header,dformat=dformat,mon=mon)
@@ -516,7 +516,6 @@ g.getmeta = function(datafile,desiredtz = "",windowsizes = c(5,900,3600),
         BrondCount_x = accmetrics$BrondCount_x
         BrondCount_y  = accmetrics$BrondCount_y
         BrondCount_z = accmetrics$BrondCount_z
-
         #--------------------------------------------------------------------
         if (length(myfun) != 0) { # apply external function to the data to extract extra features
           #starttime
@@ -636,7 +635,6 @@ g.getmeta = function(datafile,desiredtz = "",windowsizes = c(5,900,3600),
           metashort[count:(count-1+length(BrondCount_y)),col_msi] = BrondCount_y; col_msi = col_msi + 1
           metashort[count:(count-1+length(BrondCount_z)),col_msi] = BrondCount_z; col_msi = col_msi + 1
         }
-
         if (length(myfun) != 0) { # if an external function is applied.
           NcolEF = ncol(OutputExternalFunction)-1 # number of extra columns needed
           metashort[count:(count-1+nrow(OutputExternalFunction)),col_msi:(col_msi+NcolEF)] = as.matrix(OutputExternalFunction); col_msi = col_msi + NcolEF + 1

R/g.part1.R

@@ -504,6 +504,7 @@ g.part1 = function(datadir=c(),outputdir=c(),f0=1,f1=c(),windowsizes = c(5,900,3
                       do.hfx=do.hfx, do.hfy=do.hfy, do.hfz=do.hfz,
                       do.bfx=do.bfx, do.bfy=do.bfy, do.bfz=do.bfz, 
                       do.zcx=do.zcx, do.zcy=do.zcy, do.zcz=do.zcz,
+                      do.brondcounts=do.brondcounts,
                       lb = lb, hb = hb,  n = n,
                       desiredtz=desiredtz, daylimit=daylimit, windowsizes=windowsizes,
                       tempoffset=C$tempoffset, scale=C$scale, offset=C$offset,
@@ -576,7 +577,6 @@ g.part1 = function(datadir=c(),outputdir=c(),f0=1,f1=c(),windowsizes = c(5,900,3
           outputfoldername = unlist(strsplit(datadir,"/"))[length(unlist(strsplit(datadir,"/")))]
           metadatadir = paste(outputdir,"/output_",outputfoldername,sep="")
         }
-
         rm(M); rm(I); rm(C)
         # } # for loop
       }

R/g.shell.GGIR.R

@@ -429,6 +429,7 @@ g.shell.GGIR = function(mode = 1:5, datadir = c(), outputdir = c(), studyname =
     cat('\n')
     cat(paste0(rep('_',options()$width),collapse=''))
     cat("\nPart 1\n")
+    print(do.brondcounts)
     g.part1(datadir = datadir, outputdir = outputdir,
             f0 = f0, f1 = f1, windowsizes = windowsizes,
             desiredtz = desiredtz, chunksize = chunksize,
@@ -449,6 +450,7 @@ g.shell.GGIR = function(mode = 1:5, datadir = c(), outputdir = c(), studyname =
             do.hfx=do.hfx, do.hfy=do.hfy, do.hfz=do.hfz,
             do.bfx=do.bfx, do.bfy=do.bfy, do.bfz=do.bfz,
             do.zcx=do.zcx, do.zcy=do.zcy, do.zcz=do.zcz,
+            do.brondcounts=do.brondcounts,
             printsummary=printsummary,
             do.cal = do.cal,print.filename=print.filename,
             overwrite=overwrite,backup.cal.coef=backup.cal.coef,

inst/NEWS.Rd

@@ -6,6 +6,7 @@
 \itemize{
   \item Part 1: Depricating function g.metric as its functionality has been taken over by g.applymetrics.
   \item Part 2: Adding warning when ID cannot be extracted from file based on argument idloc.
+  \item Part 1: Adding BrondCounts as optional acceleration metric and dependency on activityCounts.
 }
 }
 

man/g.applymetrics.Rd

@@ -54,9 +54,10 @@ Dataframe with metric values in columns average per epoch (ws3)
   do.dev_roll_med_acc_x=FALSE,do.dev_roll_med_acc_y=FALSE,
   do.dev_roll_med_acc_z=FALSE,do.enmoa=FALSE,
   do.lfx=FALSE, do.lfy=FALSE, do.lfz=FALSE, 
-                          do.hfx=FALSE, do.hfy=FALSE, do.hfz=FALSE, 
-                          do.bfx=FALSE, do.bfy=FALSE, do.bfz=FALSE,
-                          do.zcx=FALSE, do.zcy=FALSE, do.zcz=FALSE)
+  do.hfx=FALSE, do.hfy=FALSE, do.hfz=FALSE, 
+  do.bfx=FALSE, do.bfy=FALSE, do.bfz=FALSE,
+  do.zcx=FALSE, do.zcy=FALSE, do.zcz=FALSE, do.brondcounts=FALSE)
+
   extractedmetrics = g.applymetrics(data,n=4,sf=40,ws3=5,metrics2do)
 }
 

tests/testthat/test_part1_with_allmetrics.R

@@ -5,32 +5,36 @@ test_that("Part 1 can run with all metrics", {
   #=======================
   # Part 1 with all metrics
   Ndays = 2
-  create_test_acc_csv(Nmin=Ndays*1440, sf = 9) # 9 Hertz,  because metric zc filters at 4 Hertz
+  # Using sf = 30 Hertz  because metric zc filters at 4 Hertz and brondcounts requires 30 Hertz
+  create_test_acc_csv(Nmin = Ndays * 1440, sf = 30) 
   create_test_sleeplog_csv()
   fn = "123A_testaccfile.csv"
   sleeplog_fn = "testsleeplogfile.csv"
-  metadatadir = paste0(getwd(),"/output_test")
+  metadatadir = paste0(getwd(), "/output_test")
   desiredtz="Europe/London"
   dn = "output_test"
-  if (file.exists(dn))  unlink(dn,recursive=TRUE)
-  g.part1(datadir=fn,outputdir=getwd(),f0=1,f1=1,overwrite=TRUE,desiredtz=desiredtz,
+  if (file.exists(dn))  unlink(dn, recursive = TRUE)
+  g.part1(datadir = fn, outputdir = getwd(),f0 = 1 , f1 = 1, overwrite = TRUE, desiredtz = desiredtz,
           studyname="test",do.cal = FALSE,
           # We are not doing all the metrics, because Travis-CI cannot allocate enough memory
           do.enmo = TRUE,do.lfenmo = TRUE,
           do.bfen = TRUE,
           do.hfenplus = TRUE,
-          do.mad = TRUE, do.sgAccEN=FALSE,do.zcx=TRUE, do.brondcounts=TRUE,
-          windowsizes = c(15,3600,3600), do.parallel=FALSE,
-          minimumFileSizeMB=0)
-  rn = dir("output_test/meta/basic/",full.names = TRUE)
+          do.mad = TRUE, do.sgAccEN=FALSE,do.zcx=TRUE, do.brondcounts = TRUE,
+          windowsizes = c(15, 3600, 3600), do.parallel = FALSE,
+          minimumFileSizeMB = 0)
+  rn = dir("output_test/meta/basic/", full.names = TRUE)
   load(rn[1])
-  expect_that(ncol(M$metashort),equals(7))
+  expect_that(ncol(M$metashort),equals(10))
   expect_that(nrow(M$metashort),equals(11280))
-  expect_that(round(mean(M$metashort$BFEN),digits=4),equals(0.0413))
-  expect_that(round(mean(M$metashort$LFENMO),digits=4),equals(0.0442))
-  expect_that(round(mean(M$metashort$HFENplus),digits=4),equals(0.0904))
-  expect_that(round(mean(M$metashort$MAD),digits=4),equals(0.0073))
-  expect_that(round(mean(M$metashort$ZCX),digits=4),equals(17.4165))
+  expect_that(round(mean(M$metashort$BFEN), digits = 4), equals(0.0458))
+  expect_that(round(mean(M$metashort$LFENMO), digits = 4), equals(0.0447))
+  expect_that(round(mean(M$metashort$HFENplus), digits = 4), equals(0.0914))
+  expect_that(round(mean(M$metashort$MAD), digits = 4), equals(0.0073))
+  expect_that(round(mean(M$metashort$ZCX), digits = 4), equals(14.9395))
+  expect_equal(sum(M$metashort$BrondCounts_x), 17630)
+  expect_equal(sum(M$metashort$BrondCounts_y), 61354)
+  expect_equal(sum(M$metashort$BrondCounts_z), 958370)
 
   if (file.exists(fn)) file.remove(fn)
   if (file.exists(sleeplog_fn)) file.remove(sleeplog_fn)