Nothing
## ----global_options, warning = FALSE, eval = FALSE, echo = FALSE--------------
# knitr::opts_chunk$get("root.dir")
## ----installing the dependencies, eval = FALSE--------------------------------
#
# install.packages("GENEAread", repos = "http://cran.us.r-project.org")
# install.packages("changepoint", repos = "http://cran.us.r-project.org")
# install.packages("signal", repos = "http://cran.us.r-project.org")
# install.packages("mmap", repos = "http://cran.us.r-project.org")
#
# # Load in the libraries
# library(GENEAread)
# library(changepoint)
# library(signal)
# library(mmap)
## ----Installing from Source, eval = FALSE-------------------------------------
# # You will need to change the folder location inside setwd("") to the directory where you saved the tar.gz file
# # Note that R only uses / not \ when refering to a file/directory location
# setwd("/Users/owner/Documents/GENEActiv")
# install.packages("GENEAclassify_1.5.1.tar.gz", repos=NULL, type="source")
## ----loading in the GENEAclassify library, eval = FALSE-----------------------
# library(GENEAclassify)
## ----installing from GitHub, eval = FALSE-------------------------------------
# install.packages("devtools",repos = "http://cran.us.r-project.org")
# library(devtools)
#
# install_github("https://github.com/Langford/GENEAclassify_1.41.git",
# auth_token = "7f0051aaca453eaabf0e60d49bcf752c0fea0668")
#
## ----Run library function again GENEAclassify library,eval=FALSE--------------
#
# library(GENEAclassify)
#
## ----run the vignette,eval = FALSE--------------------------------------------
#
# vignette("GENEAclassifyDemo", package = NULL, lib.loc = NULL, all = TRUE)
#
## ----Loading Data then Segmenting, eval = FALSE-------------------------------
# # Name of the file to analyse
# DataFile = "DataDirectory/jl_left wrist_010094_2012-01-30 20-39-54.bin"
# ImportedData = dataImport(DataFile, downsample = 100, start = 0, end = 0.1)
# head(ImportData)
## ----eval = FALSE-------------------------------------------------------------
# # These are some of the output variables from segmentation and getGENEAsegments
# dataCols <- c("UpDown.mean",
# "UpDown.var",
# "UpDown.sd",
# "Degrees.mean",
# "Degrees.var",
# "Degrees.sd",
# "Magnitude.mean",
# # Frequency Variables
# "Principal.Frequency.median",
# "Principal.Frequency.mad",
# "Principal.Frequency.GENEAratio",
# "Principal.Frequency.sumdiff",
# "Principal.Frequency.meandiff",
# "Principal.Frequency.abssumdiff",
# "Principal.Frequency.sddiff",
# # Light Variables
# "Light.mean",
# "Light.max",
# # Temperature Variables
# "Temp.mean",
# "Temp.sumdiff",
# "Temp.meandiff",
# "Temp.abssumdiff",
# "Temp.sddiff",
# # Step Variables
# "Step.GENEAcount",
# "Step.sd",
# "Step.mean")
#
# # Performing the segmentation now given the dataCols we want to find.
#
# SegDataFile = segmentation(ImportedData, dataCols)
# # View the data from the segmentation
# head(SegDataFile)
## ----segment a datafile, eval = FALSE-----------------------------------------
# # Name of the file to analyse
# DataFile = "DataDirectory/jl_left wrist_010094_2012-01-30 20-39-54.bin"
# SegDataFile = getGENEAsegments(DataFile, dataCols, start = 0, end = 0.1)
## ----Displaying varying step counting alogrithms, eval = FALSE----------------
#
# WalkingData = "TrainingData/Walking/walking_jl_right wrist_024603_2015-12-12 15-36-47.bin"
#
# # Starting with default filter
# W1 = getGENEAsegments(WalkingData, plot.it = TRUE)
#
# # plot.it Shows the crossing points. Turn this on for all plots to see how each filter works
# # List the step outputs here.
# W1$Step.GENEAcount; W1$Step.sd; W1$Step.mean
#
# W2 = getGENEAsegments(WalkingData, filteroder = 4)
# # Changing the filterorder changes the order of the chebyshev filter applied.
# W2$Step.GENEAcount; W2$Step.sd; W2$Step.mean
#
# W3 = getGENEAsegments(WalkingData, boundaries = c(0.15, 1))
# # List the step outputs here.
# W3$Step.GENEAcount; W3$Step.sd; W3$Step.mean
#
# # Changing the deicbel paramter
# W4 = getGENEAsegments(WalkingData, Rp = 3)
# W4$Step.GENEAcount; W4$Step.sd; W4$Step.mean
#
# # Increasing the hystersis
# W5 = getGENEAsegments(WalkingData, hysteresis = 0.1)
# W5$Step.GENEAcount; W5$Step.sd; W5$Step.mean
## ----loading TrainingData.csv, eval = FALSE-----------------------------------
# # Change the file path to the location of GENEAclassify.
# setwd("/Users/owner/Documents/GENEActiv/GENEAclassify_1.41/Data")
# TrainingData = read.table("TrainingData.csv", sep = ",")
#
# # The data can also be called through from the package.
# data(TrainingData)
# TrainingData
## ----eval = FALSE-------------------------------------------------------------
# ClassificationModel = createGENEAmodel(TrainingData,
# features = c("Segment.Duration",
# "UpDown.mean", "UpDown.sd",
# "Degrees.mean", "Degrees.sd",
# "Magnitude.mean",
# "Light.mean",
# "Temp.mean",
# "Step.sd", "Step.count", "Step.mean",
# "Principal.Frequency.median", "Principal.Frequency.mad")
# )
## ----eval = FALSE-------------------------------------------------------------
# ClassificationModel = createGENEAmodel(TrainingData,
# features = c("UpDown.mean", "UpDown.sd",
# "Degrees.mean", "Degrees.sd",
# "Magnitude.mean",
# "Step.sd", "Step.mean",
# "Principal.Frequency.median",
# "Principal.Frequency.mad"))
## ----classifying a File, eval = FALSE-----------------------------------------
# DataFile = "jl_left wrist_010094_2012-01-30 20-39-54.bin" # Change to the file to classify
# ClassifiedFile = classifyGENEA(DataFile,
# trainingfit = ClassificationModel,
# start = "3:00",
# end = "1 3:00")
## ----classifying a Directory, eval = FALSE------------------------------------
# ClassifiedDirectory = classifyGENEA(DataDirectory,
# trainingfit = ClassificationModel,
# start = "3:00",
# end = "1 3:00")
## ----Segmentation RunWalk file, echo = FALSE, eval = FALSE--------------------
# SegData = getGENEAsegments("RunWalk.bin", end = "9:23")
# head(SegData)
## ----List creation,eval = FALSE-----------------------------------------------
# Activity = c("Running",
# "Running",
# "Walking")
## ----Attaching Activities, eval = FALSE---------------------------------------
# SegData = cbind(SegData, ActivitiesListed)
## ----eval = FALSE-------------------------------------------------------------
# SegData$Activity[1:2] = "Running"
# SegData$Activity[3] = "Walking"
## ----eval = FALSE-------------------------------------------------------------
# Cycling = getGENEAsegments("TrainingData/Cycling")
# Cycling$Activity = "Cycling"
#
# NonWear = getGENEAsegments("TrainingData/NonWear")
# NonWear$Activity = "NonWear"
#
# onthego = getGENEAsegments("TrainingData/onthego")
# onthego$Activity = "onthego"
#
# Running = getGENEAsegments("TrainingData/Running")
# Running$Activity = "Running"
#
# Sitting = getGENEAsegments("TrainingData/Sitting")
# Sitting$Activity = "Sitting"
#
# Sleep = getGENEAsegments("TrainingData/Sleep")
# Sleep$Activity = "Sleep"
#
# Standing = getGENEAsegments("TrainingData/Standing")
# Standing$Activity = "Standing"
#
# Swimming = getGENEAsegments("TrainingData/Swimming")
# Swimming$Activity = "Swimming"
#
# Transport = getGENEAsegments("TrainingData/Transport")
# Transport$Activity = "Transport"
#
# Walking = getGENEAsegments("TrainingData/Walking")
# Walking$Activity = "Walking"
#
# Workingout = getGENEAsegments("TrainingData/Workingout")
# Workingout$Activity = "Workingout"
## ----Combining Segments, eval = FALSE-----------------------------------------
# TrainingData = rbind(Cycling,
# NonWear,
# onthego,
# Running,
# Sitting,
# Sleep,
# Standing,
# Swimming,
# Transport,
# Walking,
# Workingout)
## ----eval = FALSE-------------------------------------------------------------
# ClassificationModel = createGENEAmodel(TrainingData,
# features = c("UpDown.mean",
# "UpDown.sd","Degrees.mean",
# "Degrees.sd","Magnitude.mean",
# "Step.sd","Step.mean",
# "Principal.Frequency.median",
# "Principal.Frequency.mad"))
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