Huge differences in 10-min bouted LIG between p5 and visual report

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marcuslop...@gmail.com

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Oct 7, 2022, 7:49:38 PM10/7/22
to R package GGIR
Hello GGIR Team and users,

I observed that the within-day estimates of PA presented in the visual report (second page) are based on 10-min bouted PA with 80% bout.crit for both LIG and MVPA. However, the 10-min bouted LIG from g.part5 output significantly differs from the visual reports. Please, see the attached image as an example.

In this example, we have less than 10 minutes of bouted LIG in part5 output but at least 1 hour of LIG in the visual report (yellow). This discrepancy is not observed for bouted MVPA. I tried changing the bout.metric parameter, but none of the resulting part5 outputs seem to match the visual report. Any ideas?

Code:
g.shell.GGIR(#-------------------------------
             # General parameters
             #-------------------------------
             datadir="D:/99.ELEVA2022/TELE 8/csv",  
             outputdir="D:/REl_Output",
             mode=c(1:5),
             overwrite = TRUE,
             do.imp=TRUE,
             idloc=1,
             print.filename=TRUE,
             printsummary=TRUE,
             storefolderstructure = FALSE,  
             do.parallel = FALSE,
             bout.metric = 1,
             #-------------------------------
             # Part 1 parameters:
             #-------------------------------
             do.enmo = TRUE,
             chunksize=1,
             #-------------------------------
             # Part 2 parameters:
             #-------------------------------
             strategy = 2,
             maxdur = 0,
             qwindow=c(0,24),  
             mvpathreshold =c(44.8, 100.6),
             #-------------------------------
             # Part 3 parameters:
             #-------------------------------
             acc.metric="ENMO",
             #-------------------------------
             # Part 4 parameters:
             #-------------------------------
             nnights = c(),
             do.visual = TRUE,
             #-------------------------------
             # Part 5 parameters:
             #-------------------------------
             threshold.lig = c(44.8),
             threshold.mod = c(100.6),
             threshold.vig = c(428.8),
             boutdur.in = c(30),
             boutdur.lig = c(10),
             boutdur.mvpa = c(10),
             timewindow = c("MM"),
             part5_agg2_60seconds = FALSE,
             visualreport=TRUE,
             #-----------------------------------
             # Report generation
             #-------------------------------
             do.report=c(1,2,4,5))

Regards,
Marcus Lopes
participant60_example.png

Vincent van Hees

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Oct 9, 2022, 7:28:27 AM10/9/22
to marcuslop...@gmail.com, R package GGIR
Dear Marcus,

The visualisreport (pdf) is not an attempt to reflect the exact part 5 classification. The visual report is only intended to give a quick idea of the data. For example, as you can see in the visualisation no effort is made to visualise the distinct bouted- and non-bouted behaviours extracted in part 5.

If you want to visualise those then consider exporting the time series in part 5 to csv or RData file (see package documentation) and creating your own visualisation.

Thanks,

Vincent

Dr. Vincent van Hees | Independent consultant | https://accelting.com/
image

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marcuslop...@gmail.com

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Oct 19, 2022, 1:05:20 PM10/19/22
to R package GGIR
Hi Vincent,

I understand that the PA data of the visual report is extracted from part2, therefore is not expected to match the exact values of part5. I have examined the code of the g.plot5 function to check how the visual report is created. According to the lines 251-301, both LPA and MVPA plotted from midnight to midnight are 10-min bouted with 80% bout.crit. Thus, I expected that the plot would be similar but not equal to the 10-min bouted PA of part5. This is true for MVPA, but there is a huge difference for LPA (hours in the plot, zero in part5 output). I was confused about why there is a match for MVPA while not for LPA.

I will be comparing the plotted data with the time series output to understand what is happening. 
Thank you for your support,
Marcus
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