Miscellaneous
Fingerprints of finite point sets
AMDs and PDDs also work for finite point sets. The functions calculate.finite_AMD()
and
calculate.finite_PDD()
accept just a numpy array containing the points, returning the
fingerprint of the finite point set. Unlike amd.AMD
and amd.PDD
no integer k
is passed;
instead the distances to all neighbours are found (number of columns = no of points - 1).
Simplex-wise distance distributions
As the name suggests
Inverse design
It is possible to reconstruct a periodic set up to isometry from its PDD if the periodic set
satisfies certain conditions (a ‘general position’) and the PDD has enough columns. This is
implemented via the functions calculate.PDD_reconstructable()
, which returns the PDD
of a periodic set with enough columns, and reconstruct.reconstruct()
which returns
the motif given the PDD and unit cell.