The Python class moarchiving.BiobjectiveNondominatedSortedList implements a bi-objective non-dominated archive with list as parent class. It is heavily based on the bisect module. It provides easy and fast access to the overall hypervolume, the contributing hypervolume of each element, and to the uncrowded hypervolume improvement of any given point in objective space.

Either simply via

pip install moarchiving

or from GitHub via

pip install git+https://github.com/CMA-ES/moarchiving.git@master

The single file moarchiving.py (from the moarchiving/ folder) can also be directly used by itself when copied in the current folder or in a path visible to Python (e.g. a path contained in sys.path).

python -m moarchiving.test

on a system shell should output something like

doctest.testmod(moarchiving.moarchiving)
TestResults(failed=0, attempted=77)

from moarchiving import BiobjectiveNondominatedSortedList as NDA

nda = NDA()  # a new empty non-dominated archive
# add a pair to the list if non-dominated and removed dominated entries
nda.add([2, 1], info={'f': [2, 1], 'x': "don't know"})
nda == [[2, 1], ]  # is True
nda.add([1, 1])  # dominates previous entry
nda.discarded == [[2, 1]]  # just now removed element(s)
nda == [[1, 1]]  # is True

moarchiving uses the fractions.Fraction type to avoid rounding errors when computing hypervolume differences, but its usage can also easily be switched off by assigning the class attribute hypervolume_computation_float_type and hypervolume_final_float_type to float. The Fraction type can become prohibitively computationally expensive with increasing precision.

• 0.6.0 the infos attribute is a list with corresponding (arbitrary) information, e.g. for keeping the respective solutions.
• 0.5.3 fixed assertion error when not using fractions.Fraction
• 0.5.2 first published version

• Code on Github
• Documentation (possibly slightly outdated) in
  • performance test examples from a notebook
  • apidocs format
  • epydocs format