Hi everyone, Despite being a bit lost in the matrix debate, today I was working on something which might want to use what is being described. You can see an array only version at:
http://fable.svn.sourceforge.net/viewvc/fable/ImageD11/trunk/test/demo/latred.py?revision=2741&view=markup The problem is in diffraction from crystals. We measure "scattering vectors" which are in "reciprocal space" and use these to find crystal structures in "real space". These spaces are a covariant/contravariat pair*. The purpose of the code in the script is to construct a lattice class which can work with vectors that are directly measured, or come from an FFT of those vectors, which averages lots of peaks into fewer peaks. [nb, for a single lattice this is a solved problem in many software packages]. I used a keyword argument space="real" or space="reciprocal" to indicate which space a vector is in. It might be a good case to think about putting in RowVector and ColumnVector and trying to deal with the consequences. It is not in this code yet, but the lattice symmetry should show up soon. I have not understood how to distinguish a metric tensor (flips RowVector to ColumnVector) from a reciprocal metric tensor (flips back) from a simple rotation matrix (applies a symmetry operator, like 2-fold rotation, so doesn't flip at all). I fear the limitation is in my maths? Best, Jon * Some heretics have been known to scale reciprocal space by 2pi. See "Vectors and Tensors in Crystallography" by Donald Sands for an overview. _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
