MFC
High-fidelity multiphase flow simulation
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To run MFC's test suite, run
It will generate and run test cases, comparing their output to previous runs from versions of MFC considered accurate. golden files, stored in the tests/
directory contain this data, aggregating .dat
files generated when running MFC. A test is considered passing when our error tolerances are met in order to maintain a high level of stability and accuracy. Run ./mfc.sh test -h
for a full list of accepted arguments.
Most notably, you can consult the full list of tests by running
To restrict to a given range, use the --from
(-f
) and --to
(-t
) options. To run a (non-contiguous) subset of tests, use the --only
(-o
) option instead. To specify a computer, pass the -c
flag to ./mfc.sh run
like so:
where <computer name>
could be phoenix
or any of the others in the templates). You can create new templates with the appropriate run commands or omit this option. The use of --
in the above command passes options to the ./mfc.sh run
command underlying the ./mfc.sh test
.
To (re)generate golden files, append the --generate
option:
It is recommended that a range be specified when generating golden files for new test cases, as described in the previous section, in an effort not to regenerate the golden files of existing test cases.
Note: If you output new variables and want to update the golden files to include these without modifying the original data, use the --add-new-variables
option instead.
Adding a new test case can be done by modifying cases.py. The function list_cases
is responsible for generating the list of test cases. Loops and conditionals are used to vary parameters, whose defaults can be found in the BASE_CFG
case object within case.py. The function operates on two variables:
stack
: A stack that holds the variations to the default case parameters. By pushing and popping the stack inside loops and conditionals, it is easier to nest test case descriptions, as it holds the variations that are common to all future test cases within the same indentation level (in most scenarios).cases
: A list that holds fully-formed Case
objects, that will be returned at the end of the function.Internally a test case is described as:
where:
trace
is a string that contains a human-readable description of what parameters were varied, or more generally what the case is meant to test. Each trace
must be distinct.params
is the fully resolved case dictionary, as would appear in a Python case input file.ppn
is the number of processes per node to use when running the case.To illustrate, consider the following excerpt from list_cases
:
When pushing to the stack or creating a new case with the define_case_d
function, you must specify:
stack
: The current stack.trace
: A human-readable string describing what you are currently varying.variations
: A Python dictionary with case parameter variations.ppn
: The number of processes per node to use (default is 1).If a trace is empty (that is, the empty string ""
), it will not appear in the final trace, but any case parameter variations associated with it will still be applied.
Finally, the case is appended to the cases
list, which will be returned by the list_cases
function.
To test the post-processing code, append the -a
or --test-all
option:
This argument will re-run the test stack with ‘parallel_io='T’, which generates silo_hdf5 files. It will also turn most write parameters (
*_wrt) on. Then, it searches through the silo files using
h5dumpto ensure that there are no
NaNs or
Infinitys. Although adding this option does not guarantee that accurate
.silo` files are generated, it does ensure that the post-process code does not fail or produce malformed data.