Test suite

HANDE has an extensive test suite covering all core functionality. The tests are run using the testcode package (https://github.com/jsspencer/testcode). Note that the data extraction scripts for HANDE require the pandas python library.

testcode can be run from the test_suite subdirectory:

$ testcode.py

As the full test suite is extensive, it can take a long time to run, so the quick and even shorter vquick categories are provided that aim to test most functionality but run in a few minutes. By default the only the quick tests are run. The entire test suite is run every week in a mirrored GitLab repository (https://gitlab.developers.cam.ac.uk/ch/thom/hande-public-testing), using the latest GNU and Intel compilers. The quick tests are also run on every push to the master branch.

Selected data from the HANDE output is compared to known ‘good’ results (‘benchmarks’).

testcode is quite flexible and it’s easy to run subsets of tests, check against different benchmarks, compare previously run tests, run tests concurrently for speed, etc. Please see the testcode documentation for more details.


For algorithmic reasons, certain compilation and runtime options (principally POP_SIZE and processor/thread count) result in different Markov chains and hence different exact results (but same results on average). The tests should therefore be run using the same compilation options and the same parallel distribution as was used for the benchmarks. The latter for MPI parallelisation is done automatically by testcode. Separate tests exist for both POP_SIZE=32 and POP_SIZE=64.

Similarly, the tests will not pass to default accuracy if using SINGLE_PRECISION. There is a single_precision category, consisting of the tests which will pass with a tolerance set to \(10^{-5}\).

Currently there are no QMC tests suitable for OpenMP parallelisation due to difficulties with making the scheduler behave deterministically without affecting performance of production simulations. It is advised that you make sure to set the shell variable OMP_NUM_THREADS to 1 when running the test suite - otherwise these will all be marked SKIPPED.

What if the tests fail?

A common cause for tests failing is that the configuration causes a different Markov Chain to be run, or part of the code has been disabled in your build. testcode should determine that some tests are inappropriate and skip them. To force testcode to skip some tests, see below.

A second cause of failure is that some floating point values have rounded differently on different architectures. The tolerances used for the tests can also be adjusted as specified below:

Skipping Tests

If there is a unique line printed out in the output for jobs which are to be skipped, this can be used to tell testcode this, by modifying the skip_args line in the test_suite/userconfig file. See the testcode documentation for more details

Adjusting Test Tolerances

The tolerance for an individual job can be modified as specified in the testcode documentation. As an example, to modify the tolerance because of the following failure:

dmqmc/np1/heisenberg_1d - replica.in: **FAILED**.
    ERROR: absolute error 1.00e-06 greater than 1.00e-10. (Test: 17.378583.  Benchmark: 17.378584.)

The follow section can be inserted into test_suite/jobconfig. Note the backslash-quoting of the backslashes, as the tolerance value is interpreted as a python tuple containing a python string.

#Job specific tolerances:
tolerance = (1e-5,1e-5,'\\sum\\rho_{ij}M2{ji}')