My PhD research (computational organic chemistry) often generates large data sets (>10000 entires) of 'conformers' - where a conformer is basically the spatial arrangement of atoms in space.
From 10000 conformers, there are generally around 10 'unique' shapes, with all of the 10000 roughly corresponding to one of these 10 shapes.
In order to try and sort these conformers, I looked at the possibility of clustering. I generated 20 variables from the data set (measurements of various angles which ultimately determine the shape of the molecule) and ran the two step clustering analysis in SPSS.
This works fine, and does sort the conformers into sensible clusters. The issue I have is how to visualise this clustering. At the moment, the only things I can plot are the variables I imported into SPSS to begin with, but depending on which two I choose, I get a random graph which has dimensions (angles in this case). An example is below:
In the examples I've seen of similar work, the axis tend to be dimensionless, but I'm unsure of how to achieve this, or if I'm even approaching this in the right way.
Any advice would be appreciated.