I have a concern about data organisation and the best approach to simplify some multi-layered data. Simply, I have a 10 replicates of small wood beams (BeamID, ~10) subjected to a 10 different treatment (TreatID, ~10), and each beam is load tested which produces a series data of a Load with consequent Displacement (ranging from 10 to 50 rows per test; I have code that corrects for disparities in row length). Each wood beam is tested multiple times (Rep, ~10).
My plan was to lump all this data into a 5-D array:
Array[Load, Deflection, BeamID, TreatID, Rep]
This way, I should be able to plot the load~deflection curves for a given BeamID, TreatID, for all Reps by using Array[ , ,1,1, ], right? So the hypothetical output for Array[ , ,1,1,1], would be:
+------------+--------+-----+
| Deflection | Load | Rep |
+------------+--------+-----+
| 0 | 0 | 1 |
| 6.35 | 10.5 | 1 |
| 12.7 | 20.8 | 1 |
| 19.05 | 45.3 | 1 |
| 25.4 | 75.2 | 1 |
+------------+--------+-----+
And Array[ , ,1,1,2] would be:
+------------+--------+-----+
| Deflection | Load | Rep |
+------------+--------+-----+
| 0 | 0 | 2 |
| 7.3025 | 12.075 | 2 |
| 14.605 | 23.92 | 2 |
| 21.9075 | 52.095 | 2 |
| 29.21 | 86.48 | 2 |
+------------+--------+-----+
Or I think I could keep it as a simpler, 'melted' dataframe, which would have columns for Load and Deflection, and BeamID, TreatID, and Rep would be repeated for each row of the test output.
+------------+--------+-----+--------+---------+
| Deflection | Load | Rep | BeamID | TreatID |
+------------+--------+-----+--------+---------+
| 0 | 0 | 1 | 1 | 1 |
| 6.35 | 10.5 | 1 | 1 | 1 |
| 12.7 | 20.8 | 1 | 1 | 1 |
| 19.05 | 45.3 | 1 | 1 | 1 |
| 25.4 | 75.2 | 1 | 1 | 1 |
| 0 | 0 | 2 | 1 | 1 |
| 7.3025 | 12.075 | 2 | 1 | 1 |
| 14.605 | 23.92 | 2 | 1 | 1 |
| 21.9075 | 52.095 | 2 | 1 | 1 |
| 29.21 | 86.48 | 2 | 1 | 1 |
+------------+--------+-----+--------+---------+
However, with the latter, I'm not sure how I could easily and discretely pull out all the Rep test values for a specific BeamID and TreatID, especially since I use a linear model to fit a 3rd order polynomial for an specific test to extract the slope of the curves. Having it as a continuous dataframe means I'd have to specify starting and stopping points to start the linear model, correct?
Thoughts, suggestions? Am I headed in the right direction in using a 5-D array? R is a new programming language for me, so please pardon my misunderstandings.