activityCounts.R
In activityCounts: Generate ActiLife Counts

## ---- include = T, echo= FALSE-------------------------------------------
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

## ---- eval = FALSE-------------------------------------------------------
#  install.packages("activityCounts")

## ----eval=FALSE----------------------------------------------------------
#  install.packages("devtools")
#  devtools::install_github("walkabillylab/activityCounts")

## ----setup---------------------------------------------------------------
library(activityCounts)

## ----eval=FALSE----------------------------------------------------------
#  # install.packages("tidyverse")
#  raw_accel_data <- tidyverse::read_csv("~/your_raw_accelerometer_data.csv")

## ----eval=FALSE----------------------------------------------------------
#  # assume sampling frequency is 100 Hz
#  sampling_frequency <- 100
#  counts_measures <- activityCounts::counts(data = raw_accel_data, hertz = sampling_frequency)

## ------------------------------------------------------------------------
data("sampleXYZ")
head(sampleXYZ)

## ----eval=FALSE----------------------------------------------------------
#  sampleXYZ_counts <- counts(data = sampleXYZ, hertz = 100 ,x_axis = 1,y_axis = 2,z_axis = 3)
#  head(sampleXYZ_counts)

## ----eval=FALSE----------------------------------------------------------
#  calculated_output <- counts(data = your_raw_data, hertz = 100, x_axis = 2, y_axis = 3, z_axis = 4)

## ----message=FALSE, warning=FALSE----------------------------------------
summary(sampleCounts)

## ----echo=FALSE, message=FALSE, warning=FALSE----------------------------
library(ggplot2)
ggplot(data = sampleCounts, aes(x = ActiLife_x_counts, y = activityCounts_x_counts)) + geom_point() 
ggplot(data = sampleCounts, aes(x = ActiLife_y_counts, y = activityCounts_y_counts)) + geom_point() 
ggplot(data = sampleCounts, aes(x = ActiLife_z_counts, y = activityCounts_z_counts)) + geom_point()