Description Usage Arguments Details Value Author(s) See Also Examples
This function makes plot for accelerometer collected data (counts) over time for the whole monitor period, or a user specified time period or day with a midnight marking to separate monitored days.
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data |
Data with classified wear and nonwear status from
|
day |
A part of data during a user specified day for plot. |
start |
Define a starting time for plot. |
end |
Define a ending time for plot. |
cts |
The name of the counts column. The default is "axis1". |
TS |
The column name for timestamp. The default is "TimeStamp". |
summary |
List output of |
If a local time-zone is specified for wearkingMarking
, it is possible
that daylight savings starts or ends during the period shown. In this case
a dotted line will indicate its position and the appropriate time-zone
abbreviations will be included.
Plot with midnight marking.
Leena Choi leena.choi@Vanderbilt.Edu
wearingMarking
, sumVct
, summaryData
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 | data(dataSec)
mydata1m = dataCollapser(dataSec, TS = "TimeStamp", col = "counts", by = 60)
data1m = wearingMarking(dataset = mydata1m,
frame = 90,
perMinuteCts = 1,
TS = "TimeStamp",
cts = "counts",
streamFrame = NULL,
allowanceFrame= 2,
newcolname = "wearing")
## change "cts" default from "axis1" to "counts"
options(pa.cts = "counts")
## plot the whole data
plotData(data=data1m)
## plot the data from 60 min to 900 min
plotData(data=data1m, start=60, end=900)
## plot the data for day 2
plotData(data=data1m, day=2)
## include summaryData
sumdat <- summaryData(data=data1m)
plotData(data=data1m, summary=sumdat)
## present daylight saving time change
data(deliveryData)
options(pa.cts = "vm")
wm <- wearingMarking(dataset = deliveryData, TS="TimeStamp", tz="America/Chicago")
sumdat <- summaryData(wm)
plotData(data=wm, summary = sumdat)
## valid data after delivery marking
del <- markDelivery(wm)
sumdat <- summaryData(wm, delivery = del)
plotData(data=wm, summary = sumdat)
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