Test Support (numpy.testing)

Common test support for all numpy test scripts.

This single module should provide all the common functionality for numpy tests in a single location, so that test scripts can just import it and work right away. For background, see the Testing Guidelines

Asserts

assert_allclose(actual, desired[, rtol, ...])	Raises an AssertionError if two objects are not equal up to desired tolerance.
assert_array_almost_equal_nulp(x, y[, nulp])	Compare two arrays relatively to their spacing.
assert_array_max_ulp(a, b[, maxulp, dtype])	Check that all items of arrays differ in at most N Units in the Last Place.
assert_array_equal(x, y[, err_msg, verbose])	Raises an AssertionError if two array_like objects are not equal.
assert_array_less(x, y[, err_msg, verbose])	Raises an AssertionError if two array_like objects are not ordered by less than.
assert_equal(actual, desired[, err_msg, verbose])	Raises an AssertionError if two objects are not equal.
assert_raises(assert_raises)	Fail unless an exception of class exception_class is thrown by callable when invoked with arguments args and keyword arguments kwargs.
assert_raises_regex(exception_class, ...)	Fail unless an exception of class exception_class and with message that matches expected_regexp is thrown by callable when invoked with arguments args and keyword arguments kwargs.
assert_warns(warning_class, *args, **kwargs)	Fail unless the given callable throws the specified warning.
assert_no_warnings(*args, **kwargs)	Fail if the given callable produces any warnings.
assert_no_gc_cycles(*args, **kwargs)	Fail if the given callable produces any reference cycles.
assert_string_equal(actual, desired)	Test if two strings are equal.

Asserts (not recommended)

It is recommended to use one of assert_allclose, assert_array_almost_equal_nulp or assert_array_max_ulp instead of these functions for more consistent floating point comparisons.

assert_(val[, msg])	Assert that works in release mode.
assert_almost_equal(actual, desired[, ...])	Raises an AssertionError if two items are not equal up to desired precision.
assert_approx_equal(actual, desired[, ...])	Raises an AssertionError if two items are not equal up to significant digits.
assert_array_almost_equal(x, y[, decimal, ...])	Raises an AssertionError if two objects are not equal up to desired precision.
print_assert_equal(test_string, actual, desired)	Test if two objects are equal, and print an error message if test fails.

Decorators

dec.deprecated([conditional])	Deprecated since version 1.21.
dec.knownfailureif(fail_condition[, msg])	Deprecated since version 1.21.
dec.setastest([tf])	Deprecated since version 1.21.
dec.skipif(skip_condition[, msg])	Deprecated since version 1.21.
dec.slow(t)	Deprecated since version 1.21.
decorate_methods(cls, decorator[, testmatch])	Apply a decorator to all methods in a class matching a regular expression.

Test Running

Tester	alias of numpy.testing._private.nosetester.NoseTester
clear_and_catch_warnings([record, modules])	Context manager that resets warning registry for catching warnings
measure(code_str[, times, label])	Return elapsed time for executing code in the namespace of the caller.
run_module_suite([file_to_run, argv])	Run a test module.
rundocs([filename, raise_on_error])	Run doctests found in the given file.
suppress_warnings([forwarding_rule])	Context manager and decorator doing much the same as warnings.catch_warnings.

Guidelines

• Testing Guidelines
  • Introduction
  • Testing NumPy
    • Running tests from inside Python
    • Running tests from the command line
    • Other methods of running tests
  • Writing your own tests
    • Using C code in tests
    • Labeling tests
    • Easier setup and teardown functions / methods
    • Parametric tests
    • Doctests
    • tests/
    • __init__.py and setup.py
  • Tips & Tricks
    • Creating many similar tests
    • Known failures & skipping tests
    • Tests on random data
    • Documentation for numpy.test

previous

numpy.digitize

next

numpy.testing.assert_allclose