Enable g.calibrate to handle temperature data from ad-hoc csv file

[vincentvanhees]

Fixes #991

Checklist before merging:

• Existing tests still work (check by running the test suite, e.g. from RStudio).
• Added tests (if you added functionality) or fixed existing test (if you fixed a bug).
• Updated or expanded the documentation.
• Updated release notes in inst/NEWS.Rd with a user-readable summary. Please, include references to relevant issues or PR discussions.
• Added your name to the contributors lists in the DESCRIPTION file, if you think you made a significant contribution.

[vincentvanhees]

Hi @l-k- I am just tagging you to give you a heads up that I have prepared this small PR. It is a fairly straightforward minor fix I think and will merge this tomorrow.

[codecov]

Codecov Report

Attention: 3 lines in your changes are missing coverage. Please review.

Comparison is base (ededec3) 78.41% compared to head (8ee7673) 78.43%.

Files	Patch %	Lines
R/g.calibrate.R	25.00%	3 Missing ⚠️

Additional details and impacted files

@@            Coverage Diff             @@
##           master     #992      +/-   ##
==========================================
+ Coverage   78.41%   78.43%   +0.01%     
==========================================
  Files          99       99              
  Lines       13371    13368       -3     
==========================================
  Hits        10485    10485              
+ Misses       2886     2883       -3     

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[l-k-]

I think this might actually be incorrect?

We get P$data from read.myacc.csv, and there it gets populated with columns c("timestamp","accx","accy","accz","temperature"), in that exact order. You can see it here:
https://github.com/wadpac/GGIR/blob/master/R/read.myacc.csv.R#L172-L179

So it doesn't matter where the acceleration and temperature columns were located in the original csv file. P$data$temperature is always 4th or 5th column (depending on whether there is a timestamp column), no matter what params_rawdata[["rmc.col.temp"]] value was. And acceleration columns are always either 1:3 or 2:4, no matter what params_rawdata[["rmc.col.acc"]] values were.

It was just a coincidence that our test file had rmc.col.acc = 2:4, rmc.col.temp = 5, like what read.myacc.csv produces.

I'll send an alternative PR in a bit.

[vincentvanhees]

Thanks for spotting that Lena, I will now close this PR.