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| -rw-r--r-- | README.rst | 44 |
1 files changed, 24 insertions, 20 deletions
@@ -14,35 +14,39 @@ Adaptive Quadrature Using Explicit Interpolants", Pedro Gonnet, ACM TOMS 37, Usage example ------------- -``` -import numpy -import vquad +.. code-block:: python -# Simple usage. -igral, err = vquad.vquad(numpy.cos, -1, 1, rtol=1e-10) + import numpy + import vquad -# Object interface. -it = vquad.Vquad(numpy.cos, -1, 1) -igral, err = it.improve_until(rtol=1e-10) + # Simple usage. + igral, err = vquad.vquad(numpy.cos, -1, 1, rtol=1e-10) -# Evaluate interpolant. -xs = numpy.linspace(-1, 1, 101) -ys = it(xs) -``` + # Object interface. + it = vquad.Vquad(numpy.cos, -1, 1) + igral, err = it.improve_until(rtol=1e-10) -Benachmarks and tests ---------------------- + # Evaluate interpolant. + xs = numpy.linspace(-1, 1, 101) + ys = it(xs) + + +Benchmarks and tests +-------------------- Vquad includes extensive tests and benchmarks. The tests focus on verifying correctness and can be run with -``` -python3 -m pytest -s -``` + +.. code-block:: bash + + python3 -m pytest -s + The `-s` shows some statistics that are gathered during the testing. The benchmarks take longer to run and allow to quantitatively compare the performance of the algorithm. The benchmark is run by executing the vquad module. To get help, run: -``` -python3 -m vquad -h -``` + +.. code-block:: bash + + python3 -m vquad -h |