[R-sig-Geo] STIDF - endTime, STI -> Track

[Edzer Pebesma]

On 05/28/2015 12:28 PM, Chris English wrote:
> Hi,
> 
> I am wondering about the role of endTime in STIDF objects.  I am examining eye tracking data (previously cleaned of blinks) in relation to 
> presented stimuli that is for some subjects an optical illusion and for others not.  I want to examine where they were looking and when.
> 
> My process is to make a STIDF from the eye tracking data case and a STSDF of the stimuli that was presented where and for how long,
> convert the STIDF to a Track then do some 'over' analysis.
> 
> If I build my endTime for the STIDF using the delta() function on N samples, I think I get something like N-1 endTimes, or every sample
> is an endTime so N = N.
> 
> If instead I am thinking of endTime(s) as an interval during which there is a cross hair and some tangential stimulus on the screen and
> endTime is when a subject responds in some manner I can't build an STDIF due to the following test:
> 
>> eye_5v1_stidf <- STIDF(eye_5v1_sp, eye_5v1_time, eye_5v1_data,
> + eye_5v1_endTime)
> Error: nrow(object at time) == length(object at endTime) is not TRUE
>> nrow(eye_5v1_time)
> [1] 4724
>> length(eye_5v1_endTime)
> [1] 63
>>  

endTime is meant to give the end time of the time interval an
observation refers to, and so the number of endTime s has to be
identical to the number of time instances (number of observations). I
guess you figure that out.

> 
> Indeed, it is not true. But what information do I have in endTime other than my sensor sampling rate adjusted for blinks?  What I hoped to
> achieve was to compare the spacetime aspects of the Track data through time periods consistent with the time periods in the STSDF.
> Perhaps 'over' takes care of this for me and I don't have to attend if I just accept that endTime in the case of the STIDF is the end of each
> sample.
> 
> The eye tracking data I am examining is fairly simple: x, y, cumulative sum of samples in ms, duration between samples; from which
> an STI can be constructed.  Not much more data than where the eyes were when.  It would seem that there would be a lot of simple sensor
> data of this sort so I wonder if Track can relax its requirement of STIDF to allow STI. 

Good point - I wonder that too. For now, you could feed it a data.frame
with zero columns, e.g. data.frame(matrix(nrow=n, ncol=0))

-- 
Edzer Pebesma
Institute for Geoinformatics (ifgi),  University of Münster,
Heisenbergstraße 2, 48149 Münster, Germany; +49 251 83 33081
Journal of Statistical Software:   http://www.jstatsoft.org/
Computers & Geosciences:   http://elsevier.com/locate/cageo/
Spatial Statistics Society http://www.spatialstatistics.info

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