# Regression testing¶

Clawpack includes a number of tests that can be used to check for a working installation or to see whether new changes to the code have broken anything.

## Running the tests¶

If you use multiple git branches, before running the tests you should check that you have checked out appropriate branches of all relevant repositories; see Keeping track of repository versions with Git.

### PyClaw¶

Regression tests can be performed via:

cd $CLAW/pyclaw/examples nosetests  For more details, see Running and writing tests in PyClaw. (You may need to install nose if nosetests is not on your system.) ### Fortran codes¶ A few quick tests can be perfomed of the classic, amrclaw, or geoclaw codes by running make tests in the corresponding tests subdirectory, e.g.: cd$CLAW/classic/tests
make tests


This uses nosetests to run a few Python scripts that in turn run the Fortran codes and then compare a small set of values derived from the output of the run with values that are stored in these directories. If one of these tests fails then there is a problem to be investigated, but these tests do not provide good coverage of the code or check that everything is working properly.

A somewhat more complete set of tests can be run by executing all of the codes in the examples subdirectories and comparing the resulting plots with those archived in the Clawpack Gallery. An attempt at automating this can be found in the $CLAW/amrclaw/examples directory, which uses the imagediff tool described below. This is still under development. ### Travis continuous integration¶ Most Clawpack git repositories now contain a file .travis.yml at the top level so that every time a pull request is issued on Github, a basic set of tests is run. This uses the Travis continuous integration platform. Shortly after a PR is issued, Travis will run the commands in the .travis.yml and report the results on the PR page. Look for a green check mark (good) or a red X (bad) next to a commit hash and click on it to see the Travis output. [Sample output] ## Diff tools for checking test output¶ ### chardiff tool for line-by-line comparison of output files¶ If _output_old and _output_new are two sets of output files from old and new versions of a code, then it is often useful to do a line by line comparison of all of the files in each directory and display any differences. Standard tools such as xxdiff in linux or opendiff on a Mac are not very good for this since they try to match up blocks of lines to give the best match and may not compare the files line by line. The Python script$CLAW/clawutil/src/python/clawutil/chardiff.py can be used for this purpose:

$python$CLAW/clawutil/src/python/clawutil/chardiff.py _output_old _output_new


will create a new directory with html files showing all differences. It can also be used to compare two individual files. See the docstring for more details.

If _plots_old and _plots_new contain two sets of plots that we hope are identical, the Python script $CLAW/clawutil/src/python/clawutil/imagediff.py can be used to compare the corresponding images in each directory and produce html files that show each pair of images side by side. If the images are not identical it also shows an image indicating which pixels are different in the two: $ python $CLAW/clawutil/src/python/clawutil/imagediff.py _plots_old _plots_new  will create a new directory with html files showing all differences. It can also be used to compare two individual files. See the docstring for more details. ## Running and writing tests in PyClaw¶ ### Running the tests¶ The PyClaw test suite is built around nosetests for automatic test discovery, with supplementary functionality from the pyclaw.util module. To run the complete test suite with helpful output, issue the following command at the top-level of the pyclaw source directory: nosetests -vs  To run the parallel versions of the tests (if petsc4py is installed), run: mpirun -n 4 nosetests -vs  Replace 4 with the number of processes you’d like test on. Try prime numbers if you’re really trying to break things! The -vs switch tells nose to be verbose and to show you stdout, which can be useful when debugging tests. To run the tests with less output, omit the -vs. ### Running serial tests simultaneously¶ When running the tests, if your machine has multiple cores you can take advantage of them by doing: nosetests -vs --processes=2  (replace “2” with the number of processes you want to spawn). However, using large numbers of processes occasionally causes spurious failure of some tests due to issues with the operating system. If you see this behavior, it’s best to run the tests in serial or with a small number of processes. ### Running a specific test¶ The PyClaw tests are associated with particular applications in the examples/ sub- directory of the primary repository directory. If you want to run tests for a specific application, simply specify the directory containing the application you are interested in: nosetests -vs examples/acoustics_3d_variable  You can also specify a single file to run the tests it contains. ### Doctests¶ Several of the main PyClaw modules also have doctests (tests in their docstrings). You can run them by executing the corresponding module: cd$PYCLAW/src/pyclaw
python grid.py
python state.py


If the tests pass, you will see no output. You can get more output by using the -v option:

python state.py -v


### Writing New Tests¶

If you contribute new functionality to PyClaw, it is expected that you will also write at least one or two new tests that exercise your contribution, so that further changes to other parts of PyClaw or your code don’t break your feature.

This section describes some functions in pyclaw.util that facilitate testing. You do not have to use any of the functionality offered by pyclaw.util, but it may simplify your test-writing and allow you to check more cases than you would easily specify by hand.

The most important function in pyclaw.util is pyclaw.util.gen_variants(), which allows you to perform combinatorial testing without manually specifying every feature you’d like to perform. Currently, gen_variants() can multiplicatively exercise kernel_languages (Fortran or Python) and pure PyClaw or PetClaw implementations. This allows you to write one function that tests four variants.

Another function provided by util is pyclaw.util.test_app(). The test_app() function will run an application as if started from the command line with the specified keyword arguments passed in. This is useful for testing specific code that does not necessarily work with petclaw, for example, and is not expected to.

You will notice that both gen_variants() and test_app() require a verifier method as an argument. These functions both effectively run tests and verify output with the following function calls:

output = application(**kwargs)
check_values = verifier(output)


The verifier method needs to return None if there is no problem with the output, or a sequence of three values describing what was expected, what it received, and more details about the error. A very simple verifier method that you can use is pyclaw.util.check_diff(), which can use either an absolute tolerance or a relative tolerance to compare an expected value against the test output from the application.

See examples/acoustics_1d_homogeneous/test_acoustics.py for a comprehensive example of how to use gen_variants() and check_diff(). See examples/shallow_sphere/test_shallow_sphere.py for an example that uses test_app() and also loads a known solution from disk using numpy.