Merge pull request #1 from wadpac/review

thanks, #2 and #3 now highlight outstanding action points

step1_applyGGIR.R

@@ -11,11 +11,11 @@ library(GGIR)
 f0 = 1 #c() #file to start with if used in serial analyses
 f1 = 10 # c() #file to end with if used in serial analyses (modify accordingly, if infinite then it will process until last file)
 mode= c(1,2)    #What part of the analysis needs to be done (options: 1,2,3,4 and 5)
-datadir = "/media/windows-share/London/data_spring2017/output_RDAfiles/raw" #Where is the raw accelerometer data? (leave as c() if you work with milestone data and mode > 1
+datadir = "/media/sf_VBox_Shared/London/run_05-10/raw" #Where is the raw accelerometer data? (leave as c() if you work with milestone data and mode > 1
 dayborder = 4
-outputdir = "/media/windows-share/London/data_spring2017/" #Name directory where output needs to be stored
+outputdir = "/media/sf_VBox_Shared/London/run_05-10/" #Name directory where output needs to be stored
 studyname = "RDAfiles"  #name of study, only needed if datadir is a list of filenames
-selectdaysfile = "/media/windows-share/London/data_spring2017/wearcodes_2017May2.csv"
+selectdaysfile = "/media/sf_VBox_Shared/London/run_05-10/wearcodes.csv"
 
 #=====================================================================================
 # load functions from functions folder (replace by require(GGIR) once package is updated)

step2_convert2csv.R

@@ -6,7 +6,7 @@ graphics.off()
 # INPUT NEEDED:
 # setwd("D:/sharedfolder/first5") #<= the folder in which there is a folder named output_...
 # setwd("D:/dropbox/Dropbox/Accelerometry/GGIR/development") #<= the folder in which there is a folder named output_...
-path = "/media/windows-share/London/data_spring2017"
+path = "/media/sf_VBox_Shared/London/run_05-10/"
 setwd(path)
 studyname = "RDAfiles"
 exportrawdata = FALSE
@@ -16,10 +16,10 @@ library(GGIR)
 # Define output directories:
 outdir = "accelerometer_5second" # epoch data
 newdir = paste0(path,"/output_",studyname,"/",outdir)
-if (dir.exists(newdir) == FALSE) dir.create(newdir)
+if (file.exists(newdir) == FALSE) dir.create(newdir)
 
 
-ufn = unique(dir(paste0(path,"/output_",studyname,"/raw"))) # Define which files need to beprocessed:
+ufn = unique(dir(paste0(path,"/output_",studyname,"/meta/ms2.out"))) # Define which files need to beprocessed:
 # Alternatively, only use data from files for which there is a corresponding diary:
 # ann = read.csv("D:/dropbox/Dropbox/Accelerometry/GGIR/development/input_cls/data_annotations.csv")
 # ufn = as.character(unique(ann$filename))