accel.plot.7days {accelmissing}R Documentation

Daily Activity Plot

Description

Displays an individual's physical activity pattern of a day during one week.

Usage

accel.plot.7days(PA, label, flag, time.range = c("00:00", "23:59"),  
mark.missing = 0, axis.time = TRUE, save.plot = FALSE,  
directory.plot = getwd() )

Arguments

PA

an N by T matrix including activity counts, where N is the total number of daily profiles, and T is the total minutes of a day (T=1440).

label

an N by 2 matrix including the labels corresponding to PA matrix. The first column, label[,1], includes the person id, and the second column, label[,2], includes the day label of 1 to 7, indicating Sunday to Saturday.

flag

an N by T matrix with the values of either 1 or 0 which indicating wearing or missing. This matrix can be created from create.flag().

time.range

Define the time range for display. Default is midnight to midnight, which is coded by time.range = c("00:00", "23:59").

save.plot

If TRUE, pdf files are saved in your current directory or designated directory. Default is FALSE.

mark.missing

If mark.missing = 0 (default), the nonwearing time is marked by 0 while the wearing time is marked by 1 in flag matrix. If mark.missing = 1, it is the opposite.

axis.time

If TRUE, the x-axis displays the clock times, 8:00, 8:01, 8:02, etc. If FALSE, displays the time index by minute, 481, 482, 483, etc.

directory.plot

Directory to save the plots when save.plot=TRUE. If no input, plots are saved to your current directory.

Value

Plot of activity counts with smoothing curve and missing flag.

Author(s)

Jung Ae Lee <jungaeleeb@gmail.com>

References

[1] Lee JA, Gill J (2016). Missing value imputation for physical activity data measured by accelerometer. Statistical Methods in Medical Research.
[2] Ramsay, J. O., Wickham, H., Graves, S., and Hooker, G. (2014). fda: Functional Data Analysis. R package version 2.4.3.

Examples

data(acceldata2) ; data=acceldata2 # read data before imputation	
data(accelimp) # read data after imputation
	
# plot 7 days before imputation 
accel.plot.7days(PA=data$PA[1:7, ], label=data$label[1:7, ], flag=data$flag[1:7, ],
 time.range=c("09:00", "20:59"), save.plot=FALSE)

# plot 7 days after imputation
accel.plot.7days(PA=accelimp[[1]][1:7, ], label=data$label[1:7, ], flag=data$flag[1:7, ], 
time.range=c("09:00", "20:59"), save.plot=FALSE)
	
# save the plot
# setwd("yourfolder")  #--- set the directory to save plot when save.plot=TRUE
# accel.plot.7days(PA=accelimp[[1]], label=data$label, flag=data$flag, 
# time.range=c("09:00", "20:59"),  save.plot=TRUE)

[Package accelmissing version 1.4 Index]