Merge pull request #10260 from xoviat/add-pytest-support

ENH: Add pytest support

16 files changed, 3519 insertions, 13 deletions

diff --git a/numpy/conftest.py b/numpy/conftest.py
index ea4197049..15985a75b 100644
--- a/numpy/conftest.py
+++ b/numpy/conftest.py
@@ -5,6 +5,8 @@ from __future__ import division, absolute_import, print_function
 
 import warnings
 import pytest
+import numpy
+import importlib
 
 from numpy.core.multiarray_tests import get_fpu_mode
 
@@ -52,3 +54,33 @@ def check_fpu_mode(request):
         raise AssertionError("FPU precision mode changed from {0:#x} to {1:#x}"
                              " when collecting the test".format(old_mode, 
                                                                 new_mode))
+
+
+def pytest_addoption(parser):
+    parser.addoption("--runslow", action="store_true",
+                     default=False, help="run slow tests")
+
+
+def pytest_collection_modifyitems(config, items):
+    if config.getoption("--runslow"):
+        # --runslow given in cli: do not skip slow tests
+        return
+    skip_slow = pytest.mark.skip(reason="need --runslow option to run")
+    for item in items:
+        if "slow" in item.keywords:
+            item.add_marker(skip_slow)
+
+
+@pytest.fixture(autouse=True)
+def add_np(doctest_namespace):
+    doctest_namespace['np'] = numpy
+
+
+for module, replacement in {
+    'numpy.testing.decorators': 'numpy.testing.pytest_tools.decorators',
+    'numpy.testing.utils': 'numpy.testing.pytest_tools.utils',
+}.items():
+    module = importlib.import_module(module)
+    replacement = importlib.import_module(replacement)
+    module.__dict__.clear()
+    module.__dict__.update(replacement.__dict__)
diff --git a/numpy/ma/core.py b/numpy/ma/core.py
index 1edfba42e..fe092f552 100644
--- a/numpy/ma/core.py
+++ b/numpy/ma/core.py
@@ -6937,6 +6937,7 @@ def transpose(a, axes=None):
      [[False False]
      [False  True]],
            fill_value = 999999)
+
     >>> ma.transpose(x)
     masked_array(data =
      [[0 2]
diff --git a/numpy/testing/decorators.py b/numpy/testing/decorators.py
index b63850090..21bcdd798 100644
--- a/numpy/testing/decorators.py
+++ b/numpy/testing/decorators.py
@@ -3,4 +3,6 @@ Back compatibility decorators module. It will import the appropriate
 set of tools
 
 """
+import os
+
 from .nose_tools.decorators import *
diff --git a/numpy/testing/nose_tools/decorators.py b/numpy/testing/nose_tools/decorators.py
index 12531e734..243c0c8c1 100644
--- a/numpy/testing/nose_tools/decorators.py
+++ b/numpy/testing/nose_tools/decorators.py
@@ -19,6 +19,9 @@ import collections
 
 from .utils import SkipTest, assert_warns
 
+__all__ = ['slow', 'setastest', 'skipif', 'knownfailureif', 'deprecated',
+           'parametrize',]
+
 
 def slow(t):
     """
diff --git a/numpy/testing/nose_tools/parameterized.py b/numpy/testing/nose_tools/parameterized.py
index 372928e3d..d094f7c7f 100644
--- a/numpy/testing/nose_tools/parameterized.py
+++ b/numpy/testing/nose_tools/parameterized.py
@@ -252,7 +252,8 @@ def default_name_func(func, num, p):
     return base_name + name_suffix
 
 
-_test_runner_override = None
+# force nose for numpy purposes.
+_test_runner_override = 'nose'
 _test_runner_guess = False
 _test_runners = set(["unittest", "unittest2", "nose", "nose2", "pytest"])
 _test_runner_aliases = {
diff --git a/numpy/testing/nose_tools/utils.py b/numpy/testing/nose_tools/utils.py
index 6c77e5e21..2d97b5c1e 100644
--- a/numpy/testing/nose_tools/utils.py
+++ b/numpy/testing/nose_tools/utils.py
@@ -1849,6 +1849,7 @@ def _gen_alignment_data(dtype=float32, type='binary', max_size=24):
 
 class IgnoreException(Exception):
     "Ignoring this exception due to disabled feature"
+    pass
 
 
 @contextlib.contextmanager
diff --git a/numpy/testing/noseclasses.py b/numpy/testing/noseclasses.py
index 563ed14ea..144c4e7e4 100644
--- a/numpy/testing/noseclasses.py
+++ b/numpy/testing/noseclasses.py
@@ -1,6 +1,5 @@
 """
 Back compatibility noseclasses module. It will import the appropriate
 set of tools
-
 """
-from .nose_tools.noseclasses import *
+from .nose_tools.noseclasses import *
\ No newline at end of file
diff --git a/numpy/testing/nosetester.py b/numpy/testing/nosetester.py
index b726684c9..949fae03e 100644
--- a/numpy/testing/nosetester.py
+++ b/numpy/testing/nosetester.py
@@ -3,8 +3,11 @@ Back compatibility nosetester module. It will import the appropriate
 set of tools
 
 """
+import os
+
 from .nose_tools.nosetester import *
 
+
 __all__ = ['get_package_name', 'run_module_suite', 'NoseTester',
            '_numpy_tester', 'get_package_name', 'import_nose',
            'suppress_warnings']
diff --git a/numpy/testing/pytest_tools/__init__.py b/numpy/testing/pytest_tools/__init__.py
new file mode 100644
index 000000000..e69de29bb
--- /dev/null
+++ b/numpy/testing/pytest_tools/__init__.py
diff --git a/numpy/testing/pytest_tools/decorators.py b/numpy/testing/pytest_tools/decorators.py
new file mode 100644
index 000000000..08a39e0c0
--- /dev/null
+++ b/numpy/testing/pytest_tools/decorators.py
@@ -0,0 +1,278 @@
+"""
+Compatibility shim for pytest compatibility with the nose decorators.
+
+Decorators for labeling and modifying behavior of test objects.
+
+Decorators that merely return a modified version of the original
+function object are straightforward.
+
+Decorators that return a new function will not preserve meta-data such as
+function name, setup and teardown functions and so on.
+
+"""
+from __future__ import division, absolute_import, print_function
+
+import collections
+
+from .utils import SkipTest, assert_warns
+
+__all__ = ['slow', 'setastest', 'skipif', 'knownfailureif', 'deprecated',
+           'parametrize',]
+
+
+def slow(t):
+    """
+    Label a test as 'slow'.
+
+    The exact definition of a slow test is obviously both subjective and
+    hardware-dependent, but in general any individual test that requires more
+    than a second or two should be labeled as slow (the whole suite consits of
+    thousands of tests, so even a second is significant).
+
+    Parameters
+    ----------
+    t : callable
+        The test to mark as slow.
+
+    Returns
+    -------
+    t : callable
+        The decorated test `t`.
+
+    Examples
+    --------
+    The `numpy.testing` module includes ``import decorators as dec``.
+    A test can be decorated as slow like this::
+
+      from numpy.testing import *
+
+      @dec.slow
+      def test_big(self):
+          print('Big, slow test')
+
+    """
+    import pytest
+
+    return pytest.mark.slow(t)
+
+
+def setastest(tf=True):
+    """
+    Signals to nose that this function is or is not a test.
+
+    Parameters
+    ----------
+    tf : bool
+        If True, specifies that the decorated callable is a test.
+        If False, specifies that the decorated callable is not a test.
+        Default is True.
+
+    Examples
+    --------
+    `setastest` can be used in the following way::
+
+      from numpy.testing.decorators import setastest
+
+      @setastest(False)
+      def func_with_test_in_name(arg1, arg2):
+          pass
+
+    """
+    def set_test(t):
+        t.__test__ = tf
+        return t
+    return set_test
+
+
+def skipif(skip_condition, msg=None):
+    """
+    Make function raise SkipTest exception if a given condition is true.
+
+    If the condition is a callable, it is used at runtime to dynamically
+    make the decision. This is useful for tests that may require costly
+    imports, to delay the cost until the test suite is actually executed.
+
+    Parameters
+    ----------
+    skip_condition : bool or callable
+        Flag to determine whether to skip the decorated test.
+    msg : str, optional
+        Message to give on raising a SkipTest exception. Default is None.
+
+    Returns
+    -------
+    decorator : function
+        Decorator which, when applied to a function, causes SkipTest
+        to be raised when `skip_condition` is True, and the function
+        to be called normally otherwise.
+
+    Notes
+    -----
+    Undecorated functions are returned and that may lead to some lost
+    information. Note that this function differ from the pytest fixture
+    ``pytest.mark.skipif``. The latter marks test functions on import and the
+    skip is handled during collection, hence it cannot be used for non-test
+    functions, nor does it handle callable conditions.
+
+    """
+    def skip_decorator(f):
+        # Local import to avoid a hard pytest dependency and only incur the
+        # import time overhead at actual test-time.
+        import inspect
+        import pytest
+
+        if msg is None:
+            out = 'Test skipped due to test condition'
+        else:
+            out = msg
+
+        # Allow for both boolean or callable skip conditions.
+        if isinstance(skip_condition, collections.Callable):
+            skip_val = lambda: skip_condition()
+        else:
+            skip_val = lambda: skip_condition
+
+        # We need to define *two* skippers because Python doesn't allow both
+        # return with value and yield inside the same function.
+        def get_msg(func,msg=None):
+            """Skip message with information about function being skipped."""
+            if msg is None:
+                out = 'Test skipped due to test condition'
+            else:
+                out = msg
+            return "Skipping test: %s: %s" % (func.__name__, out)
+
+        def skipper_func(*args, **kwargs):
+            """Skipper for normal test functions."""
+            if skip_val():
+                raise SkipTest(get_msg(f, msg))
+            else:
+                return f(*args, **kwargs)
+
+        def skipper_gen(*args, **kwargs):
+            """Skipper for test generators."""
+            if skip_val():
+                raise SkipTest(get_msg(f, msg))
+            else:
+                for x in f(*args, **kwargs):
+                    yield x
+
+        # Choose the right skipper to use when building the actual decorator.
+        if inspect.isgeneratorfunction(f):
+            skipper = skipper_gen
+        else:
+            skipper = skipper_func
+        return skipper
+
+    return skip_decorator
+
+
+def knownfailureif(fail_condition, msg=None):
+    """
+    Make function raise KnownFailureException exception if given condition is true.
+
+    If the condition is a callable, it is used at runtime to dynamically
+    make the decision. This is useful for tests that may require costly
+    imports, to delay the cost until the test suite is actually executed.
+
+    Parameters
+    ----------
+    fail_condition : bool or callable
+        Flag to determine whether to mark the decorated test as a known
+        failure (if True) or not (if False).
+    msg : str, optional
+        Message to give on raising a KnownFailureException exception.
+        Default is None.
+
+    Returns
+    -------
+    decorator : function
+        Decorator, which, when applied to a function, causes
+        KnownFailureException to be raised when `fail_condition` is True,
+        and the function to be called normally otherwise.
+
+    Notes
+    -----
+    The decorator itself is not decorated in the pytest case unlike for nose.
+
+    """
+    import pytest
+    from .utils import KnownFailureException
+
+    if msg is None:
+        msg = 'Test skipped due to known failure'
+
+    # Allow for both boolean or callable known failure conditions.
+    if isinstance(fail_condition, collections.Callable):
+        fail_val = lambda: fail_condition()
+    else:
+        fail_val = lambda: fail_condition
+
+    def knownfail_decorator(f):
+
+        def knownfailer(*args, **kwargs):
+            if fail_val():
+                raise KnownFailureException(msg)
+            return f(*args, **kwargs)
+
+        return knownfailer
+
+    return knownfail_decorator
+
+
+def deprecated(conditional=True):
+    """
+    Filter deprecation warnings while running the test suite.
+
+    This decorator can be used to filter DeprecationWarning's, to avoid
+    printing them during the test suite run, while checking that the test
+    actually raises a DeprecationWarning.
+
+    Parameters
+    ----------
+    conditional : bool or callable, optional
+        Flag to determine whether to mark test as deprecated or not. If the
+        condition is a callable, it is used at runtime to dynamically make the
+        decision. Default is True.
+
+    Returns
+    -------
+    decorator : function
+        The `deprecated` decorator itself.
+
+    Notes
+    -----
+    .. versionadded:: 1.4.0
+
+    """
+    def deprecate_decorator(f):
+
+        def _deprecated_imp(*args, **kwargs):
+            # Poor man's replacement for the with statement
+            with assert_warns(DeprecationWarning):
+                f(*args, **kwargs)
+
+        if isinstance(conditional, collections.Callable):
+            cond = conditional()
+        else:
+            cond = conditional
+        if cond:
+            return _deprecated_imp
+        else:
+            return f
+    return deprecate_decorator
+
+
+def parametrize(vars, input):
+    """
+    Pytest compatibility class. This implements the simplest level of
+    pytest.mark.parametrize for use in nose as an aid in making the transition
+    to pytest. It achieves that by adding a dummy var parameter and ignoring
+    the doc_func parameter of the base class. It does not support variable
+    substitution by name, nor does it support nesting or classes. See the
+    pytest documentation for usage.
+
+    """
+    import pytest
+
+    return pytest.mark.parametrize(vars, input)
diff --git a/numpy/testing/pytest_tools/noseclasses.py b/numpy/testing/pytest_tools/noseclasses.py
new file mode 100644
index 000000000..2486029fe
--- /dev/null
+++ b/numpy/testing/pytest_tools/noseclasses.py
@@ -0,0 +1,342 @@
+# These classes implement a doctest runner plugin for nose, a "known failure"
+# error class, and a customized TestProgram for NumPy.
+
+# Because this module imports nose directly, it should not
+# be used except by nosetester.py to avoid a general NumPy
+# dependency on nose.
+from __future__ import division, absolute_import, print_function
+
+import os
+import doctest
+import inspect
+
+import numpy
+import pytest
+from .utils import KnownFailureException, SkipTest
+import _pytest.runner
+import _pytest.skipping
+
+
+class NpyPlugin(object):
+    
+    def pytest_runtest_makereport(self, call):
+        if call.excinfo:
+            if call.excinfo.errisinstance(KnownFailureException):
+                #let's substitute the excinfo with a pytest.xfail one
+                call2 = call.__class__(
+                    lambda: _pytest.runner.skip(str(call.excinfo.value)),
+                    call.when)
+                print()
+                print()
+                print(call.excinfo._getreprcrash())
+                print()
+                print(call.excinfo)
+                print()
+                print(call2.excinfo)
+                print()
+                call.excinfo = call2.excinfo
+            if call.excinfo.errisinstance(SkipTest):
+                #let's substitute the excinfo with a pytest.skip one
+                call2 = call.__class__(
+                    lambda: _pytest.runner.skip(str(call.excinfo.value)),
+                    call.when)
+                call.excinfo = call2.excinfo
+
+
+if False:
+    from nose.plugins import doctests as npd
+    from nose.plugins.errorclass import ErrorClass, ErrorClassPlugin
+    from nose.plugins.base import Plugin
+    from nose.util import src
+    from .nosetester import get_package_name
+    # Some of the classes in this module begin with 'Numpy' to clearly distinguish
+    # them from the plethora of very similar names from nose/unittest/doctest
+
+    #-----------------------------------------------------------------------------
+    # Modified version of the one in the stdlib, that fixes a python bug (doctests
+    # not found in extension modules, http://bugs.python.org/issue3158)
+    class NumpyDocTestFinder(doctest.DocTestFinder):
+
+        def _from_module(self, module, object):
+            """
+            Return true if the given object is defined in the given
+            module.
+            """
+            if module is None:
+                return True
+            elif inspect.isfunction(object):
+                return module.__dict__ is object.__globals__
+            elif inspect.isbuiltin(object):
+                return module.__name__ == object.__module__
+            elif inspect.isclass(object):
+                return module.__name__ == object.__module__
+            elif inspect.ismethod(object):
+                # This one may be a bug in cython that fails to correctly set the
+                # __module__ attribute of methods, but since the same error is easy
+                # to make by extension code writers, having this safety in place
+                # isn't such a bad idea
+                return module.__name__ == object.__self__.__class__.__module__
+            elif inspect.getmodule(object) is not None:
+                return module is inspect.getmodule(object)
+            elif hasattr(object, '__module__'):
+                return module.__name__ == object.__module__
+            elif isinstance(object, property):
+                return True  # [XX] no way not be sure.
+            else:
+                raise ValueError("object must be a class or function")
+
+        def _find(self, tests, obj, name, module, source_lines, globs, seen):
+            """
+            Find tests for the given object and any contained objects, and
+            add them to `tests`.
+            """
+
+            doctest.DocTestFinder._find(self, tests, obj, name, module,
+                                        source_lines, globs, seen)
+
+            # Below we re-run pieces of the above method with manual modifications,
+            # because the original code is buggy and fails to correctly identify
+            # doctests in extension modules.
+
+            # Local shorthands
+            from inspect import (
+                isroutine, isclass, ismodule, isfunction, ismethod
+                )
+
+            # Look for tests in a module's contained objects.
+            if ismodule(obj) and self._recurse:
+                for valname, val in obj.__dict__.items():
+                    valname1 = '%s.%s' % (name, valname)
+                    if ( (isroutine(val) or isclass(val))
+                         and self._from_module(module, val)):
+
+                        self._find(tests, val, valname1, module, source_lines,
+                                   globs, seen)
+
+            # Look for tests in a class's contained objects.
+            if isclass(obj) and self._recurse:
+                for valname, val in obj.__dict__.items():
+                    # Special handling for staticmethod/classmethod.
+                    if isinstance(val, staticmethod):
+                        val = getattr(obj, valname)
+                    if isinstance(val, classmethod):
+                        val = getattr(obj, valname).__func__
+
+                    # Recurse to methods, properties, and nested classes.
+                    if ((isfunction(val) or isclass(val) or
+                         ismethod(val) or isinstance(val, property)) and
+                          self._from_module(module, val)):
+                        valname = '%s.%s' % (name, valname)
+                        self._find(tests, val, valname, module, source_lines,
+                                   globs, seen)
+
+
+    # second-chance checker; if the default comparison doesn't
+    # pass, then see if the expected output string contains flags that
+    # tell us to ignore the output
+    class NumpyOutputChecker(doctest.OutputChecker):
+        def check_output(self, want, got, optionflags):
+            ret = doctest.OutputChecker.check_output(self, want, got,
+                                                     optionflags)
+            if not ret:
+                if "#random" in want:
+                    return True
+
+                # it would be useful to normalize endianness so that
+                # bigendian machines don't fail all the tests (and there are
+                # actually some bigendian examples in the doctests). Let's try
+                # making them all little endian
+                got = got.replace("'>", "'<")
+                want = want.replace("'>", "'<")
+
+                # try to normalize out 32 and 64 bit default int sizes
+                for sz in [4, 8]:
+                    got = got.replace("'<i%d'" % sz, "int")
+                    want = want.replace("'<i%d'" % sz, "int")
+
+                ret = doctest.OutputChecker.check_output(self, want,
+                        got, optionflags)
+
+            return ret
+
+
+    # Subclass nose.plugins.doctests.DocTestCase to work around a bug in
+    # its constructor that blocks non-default arguments from being passed
+    # down into doctest.DocTestCase
+    class NumpyDocTestCase(npd.DocTestCase):
+        def __init__(self, test, optionflags=0, setUp=None, tearDown=None,
+                     checker=None, obj=None, result_var='_'):
+            self._result_var = result_var
+            self._nose_obj = obj
+            doctest.DocTestCase.__init__(self, test,
+                                         optionflags=optionflags,
+                                         setUp=setUp, tearDown=tearDown,
+                                         checker=checker)
+
+
+    print_state = numpy.get_printoptions()
+
+    class NumpyDoctest(npd.Doctest):
+        name = 'numpydoctest'   # call nosetests with --with-numpydoctest
+        score = 1000  # load late, after doctest builtin
+
+        # always use whitespace and ellipsis options for doctests
+        doctest_optflags = doctest.NORMALIZE_WHITESPACE | doctest.ELLIPSIS
+
+        # files that should be ignored for doctests
+        doctest_ignore = ['generate_numpy_api.py',
+                          'setup.py']
+
+        # Custom classes; class variables to allow subclassing
+        doctest_case_class = NumpyDocTestCase
+        out_check_class = NumpyOutputChecker
+        test_finder_class = NumpyDocTestFinder
+
+        # Don't use the standard doctest option handler; hard-code the option values
+        def options(self, parser, env=os.environ):
+            Plugin.options(self, parser, env)
+            # Test doctests in 'test' files / directories. Standard plugin default
+            # is False
+            self.doctest_tests = True
+            # Variable name; if defined, doctest results stored in this variable in
+            # the top-level namespace.  None is the standard default
+            self.doctest_result_var = None
+
+        def configure(self, options, config):
+            # parent method sets enabled flag from command line --with-numpydoctest
+            Plugin.configure(self, options, config)
+            self.finder = self.test_finder_class()
+            self.parser = doctest.DocTestParser()
+            if self.enabled:
+                # Pull standard doctest out of plugin list; there's no reason to run
+                # both.  In practice the Unplugger plugin above would cover us when
+                # run from a standard numpy.test() call; this is just in case
+                # someone wants to run our plugin outside the numpy.test() machinery
+                config.plugins.plugins = [p for p in config.plugins.plugins
+                                          if p.name != 'doctest']
+
+        def set_test_context(self, test):
+            """ Configure `test` object to set test context
+
+            We set the numpy / scipy standard doctest namespace
+
+            Parameters
+            ----------
+            test : test object
+                with ``globs`` dictionary defining namespace
+
+            Returns
+            -------
+            None
+
+            Notes
+            -----
+            `test` object modified in place
+            """
+            # set the namespace for tests
+            pkg_name = get_package_name(os.path.dirname(test.filename))
+
+            # Each doctest should execute in an environment equivalent to
+            # starting Python and executing "import numpy as np", and,
+            # for SciPy packages, an additional import of the local
+            # package (so that scipy.linalg.basic.py's doctests have an
+            # implicit "from scipy import linalg" as well.
+            #
+            # Note: __file__ allows the doctest in NoseTester to run
+            # without producing an error
+            test.globs = {'__builtins__':__builtins__,
+                          '__file__':'__main__',
+                          '__name__':'__main__',
+                          'np':numpy}
+            # add appropriate scipy import for SciPy tests
+            if 'scipy' in pkg_name:
+                p = pkg_name.split('.')
+                p2 = p[-1]
+                test.globs[p2] = __import__(pkg_name, test.globs, {}, [p2])
+
+        # Override test loading to customize test context (with set_test_context
+        # method), set standard docstring options, and install our own test output
+        # checker
+        def loadTestsFromModule(self, module):
+            if not self.matches(module.__name__):
+                npd.log.debug("Doctest doesn't want module %s", module)
+                return
+            try:
+                tests = self.finder.find(module)
+            except AttributeError:
+                # nose allows module.__test__ = False; doctest does not and
+                # throws AttributeError
+                return
+            if not tests:
+                return
+            tests.sort()
+            module_file = src(module.__file__)
+            for test in tests:
+                if not test.examples:
+                    continue
+                if not test.filename:
+                    test.filename = module_file
+                # Set test namespace; test altered in place
+                self.set_test_context(test)
+                yield self.doctest_case_class(test,
+                                              optionflags=self.doctest_optflags,
+                                              checker=self.out_check_class(),
+                                              result_var=self.doctest_result_var)
+
+        # Add an afterContext method to nose.plugins.doctests.Doctest in order
+        # to restore print options to the original state after each doctest
+        def afterContext(self):
+            numpy.set_printoptions(**print_state)
+
+        # Ignore NumPy-specific build files that shouldn't be searched for tests
+        def wantFile(self, file):
+            bn = os.path.basename(file)
+            if bn in self.doctest_ignore:
+                return False
+            return npd.Doctest.wantFile(self, file)
+
+
+    class Unplugger(object):
+        """ Nose plugin to remove named plugin late in loading
+
+        By default it removes the "doctest" plugin.
+        """
+        name = 'unplugger'
+        enabled = True  # always enabled
+        score = 4000  # load late in order to be after builtins
+
+        def __init__(self, to_unplug='doctest'):
+            self.to_unplug = to_unplug
+
+        def options(self, parser, env):
+            pass
+
+        def configure(self, options, config):
+            # Pull named plugin out of plugins list
+            config.plugins.plugins = [p for p in config.plugins.plugins
+                                      if p.name != self.to_unplug]
+
+
+
+    # Class allows us to save the results of the tests in runTests - see runTests
+    # method docstring for details
+    class NumpyTestProgram(nose.core.TestProgram):
+        def runTests(self):
+            """Run Tests. Returns true on success, false on failure, and
+            sets self.success to the same value.
+
+            Because nose currently discards the test result object, but we need
+            to return it to the user, override TestProgram.runTests to retain
+            the result
+            """
+            if self.testRunner is None:
+                self.testRunner = nose.core.TextTestRunner(stream=self.config.stream,
+                                                           verbosity=self.config.verbosity,
+                                                           config=self.config)
+            plug_runner = self.config.plugins.prepareTestRunner(self.testRunner)
+            if plug_runner is not None:
+                self.testRunner = plug_runner
+            self.result = self.testRunner.run(self.test)
+            self.success = self.result.wasSuccessful()
+            return self.success
+
diff --git a/numpy/testing/pytest_tools/nosetester.py b/numpy/testing/pytest_tools/nosetester.py
new file mode 100644
index 000000000..46e2b9b8c
--- /dev/null
+++ b/numpy/testing/pytest_tools/nosetester.py
@@ -0,0 +1,566 @@
+"""
+Nose test running.
+
+This module implements ``test()`` and ``bench()`` functions for NumPy modules.
+
+"""
+from __future__ import division, absolute_import, print_function
+
+import os
+import sys
+import warnings
+from numpy.compat import basestring
+import numpy as np
+
+from .utils import import_nose, suppress_warnings
+
+
+__all__ = ['get_package_name', 'run_module_suite', 'NoseTester',
+           '_numpy_tester', 'get_package_name', 'import_nose',
+           'suppress_warnings']
+
+
+def get_package_name(filepath):
+    """
+    Given a path where a package is installed, determine its name.
+
+    Parameters
+    ----------
+    filepath : str
+        Path to a file. If the determination fails, "numpy" is returned.
+
+    Examples
+    --------
+    >>> np.testing.nosetester.get_package_name('nonsense')
+    'numpy'
+
+    """
+
+    fullpath = filepath[:]
+    pkg_name = []
+    while 'site-packages' in filepath or 'dist-packages' in filepath:
+        filepath, p2 = os.path.split(filepath)
+        if p2 in ('site-packages', 'dist-packages'):
+            break
+        pkg_name.append(p2)
+
+    # if package name determination failed, just default to numpy/scipy
+    if not pkg_name:
+        if 'scipy' in fullpath:
+            return 'scipy'
+        else:
+            return 'numpy'
+
+    # otherwise, reverse to get correct order and return
+    pkg_name.reverse()
+
+    # don't include the outer egg directory
+    if pkg_name[0].endswith('.egg'):
+        pkg_name.pop(0)
+
+    return '.'.join(pkg_name)
+
+
+def run_module_suite(file_to_run=None, argv=None):
+    """
+    Run a test module.
+
+    Equivalent to calling ``$ nosetests <argv> <file_to_run>`` from
+    the command line. This version is for pytest rather than nose.
+
+    Parameters
+    ----------
+    file_to_run : str, optional
+        Path to test module, or None.
+        By default, run the module from which this function is called.
+    argv : list of strings
+        Arguments to be passed to the pytest runner. ``argv[0]`` is
+        ignored. All command line arguments accepted by ``pytest``
+        will work. If it is the default value None, sys.argv is used.
+
+        .. versionadded:: 1.14.0
+
+    Examples
+    --------
+    Adding the following::
+
+        if __name__ == "__main__" :
+            run_module_suite(argv=sys.argv)
+
+    at the end of a test module will run the tests when that module is
+    called in the python interpreter.
+
+    Alternatively, calling::
+
+    >>> run_module_suite(file_to_run="numpy/tests/test_matlib.py")
+
+    from an interpreter will run all the test routine in 'test_matlib.py'.
+    """
+    import pytest
+    if file_to_run is None:
+        f = sys._getframe(1)
+        file_to_run = f.f_locals.get('__file__', None)
+        if file_to_run is None:
+            raise AssertionError
+
+    if argv is None:
+        argv = sys.argv[1:] + [file_to_run]
+    else:
+        argv = argv + [file_to_run]
+
+    pytest.main(argv)
+
+if False:
+    # disable run_module_suite and NoseTester
+    # until later
+    class NoseTester(object):
+        """
+        Nose test runner.
+
+        This class is made available as numpy.testing.Tester, and a test function
+        is typically added to a package's __init__.py like so::
+
+          from numpy.testing import Tester
+          test = Tester().test
+
+        Calling this test function finds and runs all tests associated with the
+        package and all its sub-packages.
+
+        Attributes
+        ----------
+        package_path : str
+            Full path to the package to test.
+        package_name : str
+            Name of the package to test.
+
+        Parameters
+        ----------
+        package : module, str or None, optional
+            The package to test. If a string, this should be the full path to
+            the package. If None (default), `package` is set to the module from
+            which `NoseTester` is initialized.
+        raise_warnings : None, str or sequence of warnings, optional
+            This specifies which warnings to configure as 'raise' instead
+            of being shown once during the test execution.  Valid strings are:
+
+              - "develop" : equals ``(Warning,)``
+              - "release" : equals ``()``, don't raise on any warnings.
+
+            Default is "release".
+        depth : int, optional
+            If `package` is None, then this can be used to initialize from the
+            module of the caller of (the caller of (...)) the code that
+            initializes `NoseTester`. Default of 0 means the module of the
+            immediate caller; higher values are useful for utility routines that
+            want to initialize `NoseTester` objects on behalf of other code.
+
+        """
+        def __init__(self, package=None, raise_warnings="release", depth=0):
+            # Back-compat: 'None' used to mean either "release" or "develop"
+            # depending on whether this was a release or develop version of
+            # numpy. Those semantics were fine for testing numpy, but not so
+            # helpful for downstream projects like scipy that use
+            # numpy.testing. (They want to set this based on whether *they* are a
+            # release or develop version, not whether numpy is.) So we continue to
+            # accept 'None' for back-compat, but it's now just an alias for the
+            # default "release".
+            if raise_warnings is None:
+                raise_warnings = "release"
+
+            package_name = None
+            if package is None:
+                f = sys._getframe(1 + depth)
+                package_path = f.f_locals.get('__file__', None)
+                if package_path is None:
+                    raise AssertionError
+                package_path = os.path.dirname(package_path)
+                package_name = f.f_locals.get('__name__', None)
+            elif isinstance(package, type(os)):
+                package_path = os.path.dirname(package.__file__)
+                package_name = getattr(package, '__name__', None)
+            else:
+                package_path = str(package)
+
+            self.package_path = package_path
+
+            # Find the package name under test; this name is used to limit coverage
+            # reporting (if enabled).
+            if package_name is None:
+                package_name = get_package_name(package_path)
+            self.package_name = package_name
+
+            # Set to "release" in constructor in maintenance branches.
+            self.raise_warnings = raise_warnings
+
+        def _test_argv(self, label, verbose, extra_argv):
+            ''' Generate argv for nosetests command
+
+            Parameters
+            ----------
+            label : {'fast', 'full', '', attribute identifier}, optional
+                see ``test`` docstring
+            verbose : int, optional
+                Integer in range 1..3, bigger means more verbose.
+            extra_argv : list, optional
+                List with any extra arguments to pass to nosetests.
+
+            Returns
+            -------
+            argv : list
+                command line arguments that will be passed to nose
+            '''
+            argv = [__file__, self.package_path, '-s']
+            if label and label != 'full':
+                if not isinstance(label, basestring):
+                    raise TypeError('Selection label should be a string')
+                if label == 'fast':
+                    label = 'not slow'
+                argv += ['-A', label]
+
+            argv += [['-q'], [''], ['-v']][min(verbose - 1, 2)]
+
+            # FIXME is this true of pytest
+            # When installing with setuptools, and also in some other cases, the
+            # test_*.py files end up marked +x executable. Nose, by default, does
+            # not run files marked with +x as they might be scripts. However, in
+            # our case nose only looks for test_*.py files under the package
+            # directory, which should be safe.
+            # argv += ['--exe']
+            if extra_argv:
+                argv += extra_argv
+            return argv
+
+        def _show_system_info(self):
+            import pytest
+            import numpy
+
+            print("NumPy version %s" % numpy.__version__)
+            relaxed_strides = numpy.ones((10, 1), order="C").flags.f_contiguous
+            print("NumPy relaxed strides checking option:", relaxed_strides)
+            npdir = os.path.dirname(numpy.__file__)
+            print("NumPy is installed in %s" % npdir)
+
+            if 'scipy' in self.package_name:
+                import scipy
+                print("SciPy version %s" % scipy.__version__)
+                spdir = os.path.dirname(scipy.__file__)
+                print("SciPy is installed in %s" % spdir)
+
+            pyversion = sys.version.replace('\n', '')
+            print("Python version %s" % pyversion)
+            print("pytest version %d.%d.%d" % pytest.__versioninfo__)
+
+        def _get_custom_doctester(self):
+            """ Return instantiated plugin for doctests
+
+            Allows subclassing of this class to override doctester
+
+            A return value of None means use the nose builtin doctest plugin
+            """
+            from .noseclasses import NumpyDoctest
+            return NumpyDoctest()
+
+        def prepare_test_args(self, label='fast', verbose=1, extra_argv=None,
+                              doctests=False, coverage=False, timer=False):
+            """
+            Run tests for module using nose.
+
+            This method does the heavy lifting for the `test` method. It takes all
+            the same arguments, for details see `test`.
+
+            See Also
+            --------
+            test
+
+            """
+            # fail with nice error message if nose is not present
+            import_nose()
+            # compile argv
+            argv = self._test_argv(label, verbose, extra_argv)
+            # our way of doing coverage
+            if coverage:
+                argv += ['--cover-package=%s' % self.package_name, '--with-coverage',
+                         '--cover-tests', '--cover-erase']
+
+            if timer:
+                if timer is True:
+                    argv += ['--with-timer']
+                elif isinstance(timer, int):
+                    argv += ['--with-timer', '--timer-top-n', str(timer)]
+
+            # construct list of plugins
+            import nose.plugins.builtin
+            from nose.plugins import EntryPointPluginManager
+            from .noseclasses import KnownFailurePlugin, Unplugger
+            plugins = [KnownFailurePlugin()]
+            plugins += [p() for p in nose.plugins.builtin.plugins]
+            try:
+                # External plugins (like nose-timer)
+                entrypoint_manager = EntryPointPluginManager()
+                entrypoint_manager.loadPlugins()
+                plugins += [p for p in entrypoint_manager.plugins]
+            except ImportError:
+                # Relies on pkg_resources, not a hard dependency
+                pass
+
+            # add doctesting if required
+            doctest_argv = '--with-doctest' in argv
+            if doctests == False and doctest_argv:
+                doctests = True
+            plug = self._get_custom_doctester()
+            if plug is None:
+                # use standard doctesting
+                if doctests and not doctest_argv:
+                    argv += ['--with-doctest']
+            else:  # custom doctesting
+                if doctest_argv:  # in fact the unplugger would take care of this
+                    argv.remove('--with-doctest')
+                plugins += [Unplugger('doctest'), plug]
+                if doctests:
+                    argv += ['--with-' + plug.name]
+            return argv, plugins
+
+        def test(self, label='fast', verbose=1, extra_argv=None,
+                 doctests=False, coverage=False, raise_warnings=None,
+                 timer=False):
+            """
+            Run tests for module using nose.
+
+            Parameters
+            ----------
+            label : {'fast', 'full', '', attribute identifier}, optional
+                Identifies the tests to run. This can be a string to pass to
+                the nosetests executable with the '-A' option, or one of several
+                special values.  Special values are:
+                * 'fast' - the default - which corresponds to the ``nosetests -A``
+                  option of 'not slow'.
+                * 'full' - fast (as above) and slow tests as in the
+                  'no -A' option to nosetests - this is the same as ''.
+                * None or '' - run all tests.
+                attribute_identifier - string passed directly to nosetests as '-A'.
+            verbose : int, optional
+                Verbosity value for test outputs, in the range 1..3. Default is 1.
+            extra_argv : list, optional
+                List with any extra arguments to pass to nosetests.
+            doctests : bool, optional
+                If True, run doctests in module. Default is False.
+            coverage : bool, optional
+                If True, report coverage of NumPy code. Default is False.
+                (This requires the `coverage module:
+                 <http://nedbatchelder.com/code/modules/coverage.html>`_).
+            raise_warnings : None, str or sequence of warnings, optional
+                This specifies which warnings to configure as 'raise' instead
+                of being shown once during the test execution.  Valid strings are:
+
+                  - "develop" : equals ``(Warning,)``
+                  - "release" : equals ``()``, don't raise on any warnings.
+
+                The default is to use the class initialization value.
+            timer : bool or int, optional
+                Timing of individual tests with ``nose-timer`` (which needs to be
+                installed).  If True, time tests and report on all of them.
+                If an integer (say ``N``), report timing results for ``N`` slowest
+                tests.
+
+            Returns
+            -------
+            result : object
+                Returns the result of running the tests as a
+                ``nose.result.TextTestResult`` object.
+
+            Notes
+            -----
+            Each NumPy module exposes `test` in its namespace to run all tests for it.
+            For example, to run all tests for numpy.lib:
+
+            >>> np.lib.test() #doctest: +SKIP
+
+            Examples
+            --------
+            >>> result = np.lib.test() #doctest: +SKIP
+            Running unit tests for numpy.lib
+            ...
+            Ran 976 tests in 3.933s
+
+            OK
+
+            >>> result.errors #doctest: +SKIP
+            []
+            >>> result.knownfail #doctest: +SKIP
+            []
+            """
+
+            # cap verbosity at 3 because nose becomes *very* verbose beyond that
+            verbose = min(verbose, 3)
+
+            from . import utils
+            utils.verbose = verbose
+
+            argv, plugins = self.prepare_test_args(
+                    label, verbose, extra_argv, doctests, coverage, timer)
+
+            if doctests:
+                print("Running unit tests and doctests for %s" % self.package_name)
+            else:
+                print("Running unit tests for %s" % self.package_name)
+
+            self._show_system_info()
+
+            # reset doctest state on every run
+            import doctest
+            doctest.master = None
+
+            if raise_warnings is None:
+                raise_warnings = self.raise_warnings
+
+            _warn_opts = dict(develop=(Warning,),
+                              release=())
+            if isinstance(raise_warnings, basestring):
+                raise_warnings = _warn_opts[raise_warnings]
+
+            with suppress_warnings("location") as sup:
+                # Reset the warning filters to the default state,
+                # so that running the tests is more repeatable.
+                warnings.resetwarnings()
+                # Set all warnings to 'warn', this is because the default 'once'
+                # has the bad property of possibly shadowing later warnings.
+                warnings.filterwarnings('always')
+                # Force the requested warnings to raise
+                for warningtype in raise_warnings:
+                    warnings.filterwarnings('error', category=warningtype)
+                # Filter out annoying import messages.
+                sup.filter(message='Not importing directory')
+                sup.filter(message="numpy.dtype size changed")
+                sup.filter(message="numpy.ufunc size changed")
+                sup.filter(category=np.ModuleDeprecationWarning)
+                # Filter out boolean '-' deprecation messages. This allows
+                # older versions of scipy to test without a flood of messages.
+                sup.filter(message=".*boolean negative.*")
+                sup.filter(message=".*boolean subtract.*")
+                # Filter out distutils cpu warnings (could be localized to
+                # distutils tests). ASV has problems with top level import,
+                # so fetch module for suppression here.
+                with warnings.catch_warnings():
+                    warnings.simplefilter("always")
+                    from ...distutils import cpuinfo
+                sup.filter(category=UserWarning, module=cpuinfo)
+                # See #7949: Filter out deprecation warnings due to the -3 flag to
+                # python 2
+                if sys.version_info.major == 2 and sys.py3kwarning:
+                    # This is very specific, so using the fragile module filter
+                    # is fine
+                    import threading
+                    sup.filter(DeprecationWarning,
+                               r"sys\.exc_clear\(\) not supported in 3\.x",
+                               module=threading)
+                    sup.filter(DeprecationWarning, message=r"in 3\.x, __setslice__")
+                    sup.filter(DeprecationWarning, message=r"in 3\.x, __getslice__")
+                    sup.filter(DeprecationWarning, message=r"buffer\(\) not supported in 3\.x")
+                    sup.filter(DeprecationWarning, message=r"CObject type is not supported in 3\.x")
+                    sup.filter(DeprecationWarning, message=r"comparing unequal types not supported in 3\.x")
+                # Filter out some deprecation warnings inside nose 1.3.7 when run
+                # on python 3.5b2. See
+                #     https://github.com/nose-devs/nose/issues/929
+                # Note: it is hard to filter based on module for sup (lineno could
+                #       be implemented).
+                warnings.filterwarnings("ignore", message=".*getargspec.*",
+                                        category=DeprecationWarning,
+                                        module=r"nose\.")
+
+                from .noseclasses import NumpyTestProgram
+
+                t = NumpyTestProgram(argv=argv, exit=False, plugins=plugins)
+
+            return t.result
+
+        def bench(self, label='fast', verbose=1, extra_argv=None):
+            """
+            Run benchmarks for module using nose.
+
+            Parameters
+            ----------
+            label : {'fast', 'full', '', attribute identifier}, optional
+                Identifies the benchmarks to run. This can be a string to pass to
+                the nosetests executable with the '-A' option, or one of several
+                special values.  Special values are:
+                * 'fast' - the default - which corresponds to the ``nosetests -A``
+                  option of 'not slow'.
+                * 'full' - fast (as above) and slow benchmarks as in the
+                  'no -A' option to nosetests - this is the same as ''.
+                * None or '' - run all tests.
+                attribute_identifier - string passed directly to nosetests as '-A'.
+            verbose : int, optional
+                Integer in range 1..3, bigger means more verbose.
+            extra_argv : list, optional
+                List with any extra arguments to pass to nosetests.
+
+            Returns
+            -------
+            success : bool
+                Returns True if running the benchmarks works, False if an error
+                occurred.
+
+            Notes
+            -----
+            Benchmarks are like tests, but have names starting with "bench" instead
+            of "test", and can be found under the "benchmarks" sub-directory of the
+            module.
+
+            Each NumPy module exposes `bench` in its namespace to run all benchmarks
+            for it.
+
+            Examples
+            --------
+            >>> success = np.lib.bench() #doctest: +SKIP
+            Running benchmarks for numpy.lib
+            ...
+            using 562341 items:
+            unique:
+            0.11
+            unique1d:
+            0.11
+            ratio: 1.0
+            nUnique: 56230 == 56230
+            ...
+            OK
+
+            >>> success #doctest: +SKIP
+            True
+
+            """
+
+            print("Running benchmarks for %s" % self.package_name)
+            self._show_system_info()
+
+            argv = self._test_argv(label, verbose, extra_argv)
+            argv += ['--match', r'(?:^|[\\b_\\.%s-])[Bb]ench' % os.sep]
+
+            # import nose or make informative error
+            nose = import_nose()
+
+            # get plugin to disable doctests
+            from .noseclasses import Unplugger
+            add_plugins = [Unplugger('doctest')]
+
+            return nose.run(argv=argv, addplugins=add_plugins)
+else:
+
+    class NoseTester(object):
+        def __init__(self, package=None, raise_warnings="release", depth=0):
+            pass
+
+        def test(self, label='fast', verbose=1, extra_argv=None,
+                 doctests=False, coverage=False, raise_warnings=None,
+                 timer=False):
+            pass
+
+        def bench(self, label='fast', verbose=1, extra_argv=None):
+            pass
+
+
+def _numpy_tester():
+    if hasattr(np, "__version__") and ".dev0" in np.__version__:
+        mode = "develop"
+    else:
+        mode = "release"
+    return NoseTester(raise_warnings=mode, depth=1)
diff --git a/numpy/testing/pytest_tools/utils.py b/numpy/testing/pytest_tools/utils.py
new file mode 100644
index 000000000..19982ec54
--- /dev/null
+++ b/numpy/testing/pytest_tools/utils.py
@@ -0,0 +1,2275 @@
+"""
+Utility function to facilitate testing.
+
+"""
+from __future__ import division, absolute_import, print_function
+
+import os
+import sys
+import re
+import operator
+import warnings
+from functools import partial, wraps
+import shutil
+import contextlib
+from tempfile import mkdtemp, mkstemp
+
+from numpy.core import(
+     float32, empty, arange, array_repr, ndarray, isnat, array)
+from numpy.lib.utils import deprecate
+
+if sys.version_info[0] >= 3:
+    from io import StringIO
+else:
+    from StringIO import StringIO
+
+__all__ = [
+        'assert_equal', 'assert_almost_equal', 'assert_approx_equal',
+        'assert_array_equal', 'assert_array_less', 'assert_string_equal',
+        'assert_array_almost_equal', 'assert_raises', 'build_err_msg',
+        'decorate_methods', 'jiffies', 'memusage', 'print_assert_equal',
+        'raises', 'rand', 'rundocs', 'runstring', 'verbose', 'measure',
+        'assert_', 'assert_array_almost_equal_nulp', 'assert_raises_regex',
+        'assert_array_max_ulp', 'assert_warns', 'assert_no_warnings',
+        'assert_allclose', 'IgnoreException', 'clear_and_catch_warnings',
+        'SkipTest', 'KnownFailureException', 'temppath', 'tempdir', 'IS_PYPY',
+        'HAS_REFCOUNT', 'suppress_warnings', 'assert_array_compare',
+        '_assert_valid_refcount', '_gen_alignment_data',
+        ]
+
+
+class KnownFailureException(Exception):
+    """Raise this exception to mark a test as a known failing test.
+
+    """
+    def __new__(cls, *args, **kwargs):
+        # import _pytest here to avoid hard dependency
+        import _pytest
+        return _pytest.skipping.xfail(*args, **kwargs)
+
+
+class SkipTest(Exception):
+    """Raise this exception to mark a skipped test.
+
+    """
+    def __new__(cls, *args, **kwargs):
+        # import _pytest here to avoid hard dependency
+        import _pytest
+        return _pytest.runner.Skipped(*args, **kwargs)
+
+
+class IgnoreException(Exception):
+    """Ignoring this exception due to disabled feature
+
+    This exception seems unused and can be removed.
+
+    """
+    pass
+
+
+KnownFailureTest = KnownFailureException  # backwards compat
+
+verbose = 0
+
+IS_PYPY = '__pypy__' in sys.modules
+HAS_REFCOUNT = getattr(sys, 'getrefcount', None) is not None
+
+
+def import_nose():
+    """ Not wanted for pytest, make it a dummy function
+
+    """
+    pass
+
+
+def assert_(val, msg=''):
+    """
+    Assert that works in release mode.
+    Accepts callable msg to allow deferring evaluation until failure.
+
+    The Python built-in ``assert`` does not work when executing code in
+    optimized mode (the ``-O`` flag) - no byte-code is generated for it.
+
+    For documentation on usage, refer to the Python documentation.
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    if not val:
+        try:
+            smsg = msg()
+        except TypeError:
+            smsg = msg
+        raise AssertionError(smsg)
+
+
+def gisnan(x):
+    """like isnan, but always raise an error if type not supported instead of
+    returning a TypeError object.
+
+    Notes
+    -----
+    isnan and other ufunc sometimes return a NotImplementedType object instead
+    of raising any exception. This function is a wrapper to make sure an
+    exception is always raised.
+
+    This should be removed once this problem is solved at the Ufunc level."""
+    from numpy.core import isnan
+    st = isnan(x)
+    if isinstance(st, type(NotImplemented)):
+        raise TypeError("isnan not supported for this type")
+    return st
+
+
+def gisfinite(x):
+    """like isfinite, but always raise an error if type not supported instead of
+    returning a TypeError object.
+
+    Notes
+    -----
+    isfinite and other ufunc sometimes return a NotImplementedType object instead
+    of raising any exception. This function is a wrapper to make sure an
+    exception is always raised.
+
+    This should be removed once this problem is solved at the Ufunc level."""
+    from numpy.core import isfinite, errstate
+    with errstate(invalid='ignore'):
+        st = isfinite(x)
+        if isinstance(st, type(NotImplemented)):
+            raise TypeError("isfinite not supported for this type")
+    return st
+
+
+def gisinf(x):
+    """like isinf, but always raise an error if type not supported instead of
+    returning a TypeError object.
+
+    Notes
+    -----
+    isinf and other ufunc sometimes return a NotImplementedType object instead
+    of raising any exception. This function is a wrapper to make sure an
+    exception is always raised.
+
+    This should be removed once this problem is solved at the Ufunc level."""
+    from numpy.core import isinf, errstate
+    with errstate(invalid='ignore'):
+        st = isinf(x)
+        if isinstance(st, type(NotImplemented)):
+            raise TypeError("isinf not supported for this type")
+    return st
+
+
+@deprecate(message="numpy.testing.rand is deprecated in numpy 1.11. "
+                   "Use numpy.random.rand instead.")
+def rand(*args):
+    """Returns an array of random numbers with the given shape.
+
+    This only uses the standard library, so it is useful for testing purposes.
+    """
+    import random
+    from numpy.core import zeros, float64
+    results = zeros(args, float64)
+    f = results.flat
+    for i in range(len(f)):
+        f[i] = random.random()
+    return results
+
+
+if os.name == 'nt':
+    # Code "stolen" from enthought/debug/memusage.py
+    def GetPerformanceAttributes(object, counter, instance=None,
+                                 inum=-1, format=None, machine=None):
+        # NOTE: Many counters require 2 samples to give accurate results,
+        # including "% Processor Time" (as by definition, at any instant, a
+        # thread's CPU usage is either 0 or 100).  To read counters like this,
+        # you should copy this function, but keep the counter open, and call
+        # CollectQueryData() each time you need to know.
+        # See http://msdn.microsoft.com/library/en-us/dnperfmo/html/perfmonpt2.asp
+        # My older explanation for this was that the "AddCounter" process forced
+        # the CPU to 100%, but the above makes more sense :)
+        import win32pdh
+        if format is None:
+            format = win32pdh.PDH_FMT_LONG
+        path = win32pdh.MakeCounterPath( (machine, object, instance, None, inum, counter))
+        hq = win32pdh.OpenQuery()
+        try:
+            hc = win32pdh.AddCounter(hq, path)
+            try:
+                win32pdh.CollectQueryData(hq)
+                type, val = win32pdh.GetFormattedCounterValue(hc, format)
+                return val
+            finally:
+                win32pdh.RemoveCounter(hc)
+        finally:
+            win32pdh.CloseQuery(hq)
+
+    def memusage(processName="python", instance=0):
+        # from win32pdhutil, part of the win32all package
+        import win32pdh
+        return GetPerformanceAttributes("Process", "Virtual Bytes",
+                                        processName, instance,
+                                        win32pdh.PDH_FMT_LONG, None)
+elif sys.platform[:5] == 'linux':
+
+    def memusage(_proc_pid_stat='/proc/%s/stat' % (os.getpid())):
+        """
+        Return virtual memory size in bytes of the running python.
+
+        """
+        try:
+            f = open(_proc_pid_stat, 'r')
+            l = f.readline().split(' ')
+            f.close()
+            return int(l[22])
+        except Exception:
+            return
+else:
+    def memusage():
+        """
+        Return memory usage of running python. [Not implemented]
+
+        """
+        raise NotImplementedError
+
+
+if sys.platform[:5] == 'linux':
+    def jiffies(_proc_pid_stat='/proc/%s/stat' % (os.getpid()),
+                _load_time=[]):
+        """
+        Return number of jiffies elapsed.
+
+        Return number of jiffies (1/100ths of a second) that this
+        process has been scheduled in user mode. See man 5 proc.
+
+        """
+        import time
+        if not _load_time:
+            _load_time.append(time.time())
+        try:
+            f = open(_proc_pid_stat, 'r')
+            l = f.readline().split(' ')
+            f.close()
+            return int(l[13])
+        except Exception:
+            return int(100*(time.time()-_load_time[0]))
+else:
+    # os.getpid is not in all platforms available.
+    # Using time is safe but inaccurate, especially when process
+    # was suspended or sleeping.
+    def jiffies(_load_time=[]):
+        """
+        Return number of jiffies elapsed.
+
+        Return number of jiffies (1/100ths of a second) that this
+        process has been scheduled in user mode. See man 5 proc.
+
+        """
+        import time
+        if not _load_time:
+            _load_time.append(time.time())
+        return int(100*(time.time()-_load_time[0]))
+
+
+def build_err_msg(arrays, err_msg, header='Items are not equal:',
+                  verbose=True, names=('ACTUAL', 'DESIRED'), precision=8):
+    msg = ['\n' + header]
+    if err_msg:
+        if err_msg.find('\n') == -1 and len(err_msg) < 79-len(header):
+            msg = [msg[0] + ' ' + err_msg]
+        else:
+            msg.append(err_msg)
+    if verbose:
+        for i, a in enumerate(arrays):
+
+            if isinstance(a, ndarray):
+                # precision argument is only needed if the objects are ndarrays
+                r_func = partial(array_repr, precision=precision)
+            else:
+                r_func = repr
+
+            try:
+                r = r_func(a)
+            except Exception as exc:
+                r = '[repr failed for <{}>: {}]'.format(type(a).__name__, exc)
+            if r.count('\n') > 3:
+                r = '\n'.join(r.splitlines()[:3])
+                r += '...'
+            msg.append(' %s: %s' % (names[i], r))
+    return '\n'.join(msg)
+
+
+def assert_equal(actual, desired, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two objects are not equal.
+
+    Given two objects (scalars, lists, tuples, dictionaries or numpy arrays),
+    check that all elements of these objects are equal. An exception is raised
+    at the first conflicting values.
+
+    Parameters
+    ----------
+    actual : array_like
+        The object to check.
+    desired : array_like
+        The expected object.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired are not equal.
+
+    Examples
+    --------
+    >>> np.testing.assert_equal([4,5], [4,6])
+    ...
+    <type 'exceptions.AssertionError'>:
+    Items are not equal:
+    item=1
+     ACTUAL: 5
+     DESIRED: 6
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    if isinstance(desired, dict):
+        if not isinstance(actual, dict):
+            raise AssertionError(repr(type(actual)))
+        assert_equal(len(actual), len(desired), err_msg, verbose)
+        for k, i in desired.items():
+            if k not in actual:
+                raise AssertionError(repr(k))
+            assert_equal(actual[k], desired[k], 'key=%r\n%s' % (k, err_msg), verbose)
+        return
+    if isinstance(desired, (list, tuple)) and isinstance(actual, (list, tuple)):
+        assert_equal(len(actual), len(desired), err_msg, verbose)
+        for k in range(len(desired)):
+            assert_equal(actual[k], desired[k], 'item=%r\n%s' % (k, err_msg), verbose)
+        return
+    from numpy.core import ndarray, isscalar, signbit
+    from numpy.lib import iscomplexobj, real, imag
+    if isinstance(actual, ndarray) or isinstance(desired, ndarray):
+        return assert_array_equal(actual, desired, err_msg, verbose)
+    msg = build_err_msg([actual, desired], err_msg, verbose=verbose)
+
+    # Handle complex numbers: separate into real/imag to handle
+    # nan/inf/negative zero correctly
+    # XXX: catch ValueError for subclasses of ndarray where iscomplex fail
+    try:
+        usecomplex = iscomplexobj(actual) or iscomplexobj(desired)
+    except ValueError:
+        usecomplex = False
+
+    if usecomplex:
+        if iscomplexobj(actual):
+            actualr = real(actual)
+            actuali = imag(actual)
+        else:
+            actualr = actual
+            actuali = 0
+        if iscomplexobj(desired):
+            desiredr = real(desired)
+            desiredi = imag(desired)
+        else:
+            desiredr = desired
+            desiredi = 0
+        try:
+            assert_equal(actualr, desiredr)
+            assert_equal(actuali, desiredi)
+        except AssertionError:
+            raise AssertionError(msg)
+
+    # isscalar test to check cases such as [np.nan] != np.nan
+    if isscalar(desired) != isscalar(actual):
+        raise AssertionError(msg)
+
+    # Inf/nan/negative zero handling
+    try:
+        # If one of desired/actual is not finite, handle it specially here:
+        # check that both are nan if any is a nan, and test for equality
+        # otherwise
+        if not (gisfinite(desired) and gisfinite(actual)):
+            isdesnan = gisnan(desired)
+            isactnan = gisnan(actual)
+            if isdesnan or isactnan:
+                if not (isdesnan and isactnan):
+                    raise AssertionError(msg)
+            else:
+                if not desired == actual:
+                    raise AssertionError(msg)
+            return
+        elif desired == 0 and actual == 0:
+            if not signbit(desired) == signbit(actual):
+                raise AssertionError(msg)
+    # If TypeError or ValueError raised while using isnan and co, just handle
+    # as before
+    except (TypeError, ValueError, NotImplementedError):
+        pass
+
+    try:
+        # If both are NaT (and have the same dtype -- datetime or timedelta)
+        # they are considered equal.
+        if (isnat(desired) == isnat(actual) and
+                array(desired).dtype.type == array(actual).dtype.type):
+            return
+        else:
+            raise AssertionError(msg)
+
+    # If TypeError or ValueError raised while using isnan and co, just handle
+    # as before
+    except (TypeError, ValueError, NotImplementedError):
+        pass
+
+    # Explicitly use __eq__ for comparison, ticket #2552
+    if not (desired == actual):
+        raise AssertionError(msg)
+
+
+def print_assert_equal(test_string, actual, desired):
+    """
+    Test if two objects are equal, and print an error message if test fails.
+
+    The test is performed with ``actual == desired``.
+
+    Parameters
+    ----------
+    test_string : str
+        The message supplied to AssertionError.
+    actual : object
+        The object to test for equality against `desired`.
+    desired : object
+        The expected result.
+
+    Examples
+    --------
+    >>> np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 1])
+    >>> np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 2])
+    Traceback (most recent call last):
+    ...
+    AssertionError: Test XYZ of func xyz failed
+    ACTUAL:
+    [0, 1]
+    DESIRED:
+    [0, 2]
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import pprint
+
+    if not (actual == desired):
+        msg = StringIO()
+        msg.write(test_string)
+        msg.write(' failed\nACTUAL: \n')
+        pprint.pprint(actual, msg)
+        msg.write('DESIRED: \n')
+        pprint.pprint(desired, msg)
+        raise AssertionError(msg.getvalue())
+
+
+def assert_almost_equal(actual,desired,decimal=7,err_msg='',verbose=True):
+    """
+    Raises an AssertionError if two items are not equal up to desired
+    precision.
+
+    .. note:: It is recommended to use one of `assert_allclose`,
+              `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
+              instead of this function for more consistent floating point
+              comparisons.
+
+    The test verifies that the elements of ``actual`` and ``desired`` satisfy.
+
+        ``abs(desired-actual) < 1.5 * 10**(-decimal)``
+
+    That is a looser test than originally documented, but agrees with what the
+    actual implementation in `assert_array_almost_equal` did up to rounding
+    vagaries. An exception is raised at conflicting values. For ndarrays this
+    delegates to assert_array_almost_equal
+
+    Parameters
+    ----------
+    actual : array_like
+        The object to check.
+    desired : array_like
+        The expected object.
+    decimal : int, optional
+        Desired precision, default is 7.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+      If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    >>> import numpy.testing as npt
+    >>> npt.assert_almost_equal(2.3333333333333, 2.33333334)
+    >>> npt.assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
+    ...
+    <type 'exceptions.AssertionError'>:
+    Items are not equal:
+     ACTUAL: 2.3333333333333002
+     DESIRED: 2.3333333399999998
+
+    >>> npt.assert_almost_equal(np.array([1.0,2.3333333333333]),
+    ...                         np.array([1.0,2.33333334]), decimal=9)
+    ...
+    <type 'exceptions.AssertionError'>:
+    Arrays are not almost equal
+    <BLANKLINE>
+    (mismatch 50.0%)
+     x: array([ 1.        ,  2.33333333])
+     y: array([ 1.        ,  2.33333334])
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    from numpy.core import ndarray
+    from numpy.lib import iscomplexobj, real, imag
+
+    # Handle complex numbers: separate into real/imag to handle
+    # nan/inf/negative zero correctly
+    # XXX: catch ValueError for subclasses of ndarray where iscomplex fail
+    try:
+        usecomplex = iscomplexobj(actual) or iscomplexobj(desired)
+    except ValueError:
+        usecomplex = False
+
+    def _build_err_msg():
+        header = ('Arrays are not almost equal to %d decimals' % decimal)
+        return build_err_msg([actual, desired], err_msg, verbose=verbose,
+                             header=header)
+
+    if usecomplex:
+        if iscomplexobj(actual):
+            actualr = real(actual)
+            actuali = imag(actual)
+        else:
+            actualr = actual
+            actuali = 0
+        if iscomplexobj(desired):
+            desiredr = real(desired)
+            desiredi = imag(desired)
+        else:
+            desiredr = desired
+            desiredi = 0
+        try:
+            assert_almost_equal(actualr, desiredr, decimal=decimal)
+            assert_almost_equal(actuali, desiredi, decimal=decimal)
+        except AssertionError:
+            raise AssertionError(_build_err_msg())
+
+    if isinstance(actual, (ndarray, tuple, list)) \
+            or isinstance(desired, (ndarray, tuple, list)):
+        return assert_array_almost_equal(actual, desired, decimal, err_msg)
+    try:
+        # If one of desired/actual is not finite, handle it specially here:
+        # check that both are nan if any is a nan, and test for equality
+        # otherwise
+        if not (gisfinite(desired) and gisfinite(actual)):
+            if gisnan(desired) or gisnan(actual):
+                if not (gisnan(desired) and gisnan(actual)):
+                    raise AssertionError(_build_err_msg())
+            else:
+                if not desired == actual:
+                    raise AssertionError(_build_err_msg())
+            return
+    except (NotImplementedError, TypeError):
+        pass
+    if abs(desired - actual) >= 1.5 * 10.0**(-decimal):
+        raise AssertionError(_build_err_msg())
+
+
+def assert_approx_equal(actual,desired,significant=7,err_msg='',verbose=True):
+    """
+    Raises an AssertionError if two items are not equal up to significant
+    digits.
+
+    .. note:: It is recommended to use one of `assert_allclose`,
+              `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
+              instead of this function for more consistent floating point
+              comparisons.
+
+    Given two numbers, check that they are approximately equal.
+    Approximately equal is defined as the number of significant digits
+    that agree.
+
+    Parameters
+    ----------
+    actual : scalar
+        The object to check.
+    desired : scalar
+        The expected object.
+    significant : int, optional
+        Desired precision, default is 7.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+      If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    >>> np.testing.assert_approx_equal(0.12345677777777e-20, 0.1234567e-20)
+    >>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345671e-20,
+                                       significant=8)
+    >>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345672e-20,
+                                       significant=8)
+    ...
+    <type 'exceptions.AssertionError'>:
+    Items are not equal to 8 significant digits:
+     ACTUAL: 1.234567e-021
+     DESIRED: 1.2345672000000001e-021
+
+    the evaluated condition that raises the exception is
+
+    >>> abs(0.12345670e-20/1e-21 - 0.12345672e-20/1e-21) >= 10**-(8-1)
+    True
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+
+    (actual, desired) = map(float, (actual, desired))
+    if desired == actual:
+        return
+    # Normalized the numbers to be in range (-10.0,10.0)
+    # scale = float(pow(10,math.floor(math.log10(0.5*(abs(desired)+abs(actual))))))
+    with np.errstate(invalid='ignore'):
+        scale = 0.5*(np.abs(desired) + np.abs(actual))
+        scale = np.power(10, np.floor(np.log10(scale)))
+    try:
+        sc_desired = desired/scale
+    except ZeroDivisionError:
+        sc_desired = 0.0
+    try:
+        sc_actual = actual/scale
+    except ZeroDivisionError:
+        sc_actual = 0.0
+    msg = build_err_msg([actual, desired], err_msg,
+                header='Items are not equal to %d significant digits:' %
+                                 significant,
+                verbose=verbose)
+    try:
+        # If one of desired/actual is not finite, handle it specially here:
+        # check that both are nan if any is a nan, and test for equality
+        # otherwise
+        if not (gisfinite(desired) and gisfinite(actual)):
+            if gisnan(desired) or gisnan(actual):
+                if not (gisnan(desired) and gisnan(actual)):
+                    raise AssertionError(msg)
+            else:
+                if not desired == actual:
+                    raise AssertionError(msg)
+            return
+    except (TypeError, NotImplementedError):
+        pass
+    if np.abs(sc_desired - sc_actual) >= np.power(10., -(significant-1)):
+        raise AssertionError(msg)
+
+
+def assert_array_compare(comparison, x, y, err_msg='', verbose=True,
+                         header='', precision=6, equal_nan=True,
+                         equal_inf=True):
+    __tracebackhide__ = True  # Hide traceback for py.test
+    from numpy.core import array, isnan, isinf, any, inf
+    x = array(x, copy=False, subok=True)
+    y = array(y, copy=False, subok=True)
+
+    def isnumber(x):
+        return x.dtype.char in '?bhilqpBHILQPefdgFDG'
+
+    def istime(x):
+        return x.dtype.char in "Mm"
+
+    def chk_same_position(x_id, y_id, hasval='nan'):
+        """Handling nan/inf: check that x and y have the nan/inf at the same
+        locations."""
+        try:
+            assert_array_equal(x_id, y_id)
+        except AssertionError:
+            msg = build_err_msg([x, y],
+                                err_msg + '\nx and y %s location mismatch:'
+                                % (hasval), verbose=verbose, header=header,
+                                names=('x', 'y'), precision=precision)
+            raise AssertionError(msg)
+
+    try:
+        cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
+        if not cond:
+            msg = build_err_msg([x, y],
+                                err_msg
+                                + '\n(shapes %s, %s mismatch)' % (x.shape,
+                                                                  y.shape),
+                                verbose=verbose, header=header,
+                                names=('x', 'y'), precision=precision)
+            raise AssertionError(msg)
+
+        if isnumber(x) and isnumber(y):
+            has_nan = has_inf = False
+            if equal_nan:
+                x_isnan, y_isnan = isnan(x), isnan(y)
+                # Validate that NaNs are in the same place
+                has_nan = any(x_isnan) or any(y_isnan)
+                if has_nan:
+                    chk_same_position(x_isnan, y_isnan, hasval='nan')
+
+            if equal_inf:
+                x_isinf, y_isinf = isinf(x), isinf(y)
+                # Validate that infinite values are in the same place
+                has_inf = any(x_isinf) or any(y_isinf)
+                if has_inf:
+                    # Check +inf and -inf separately, since they are different
+                    chk_same_position(x == +inf, y == +inf, hasval='+inf')
+                    chk_same_position(x == -inf, y == -inf, hasval='-inf')
+
+            if has_nan and has_inf:
+                x = x[~(x_isnan | x_isinf)]
+                y = y[~(y_isnan | y_isinf)]
+            elif has_nan:
+                x = x[~x_isnan]
+                y = y[~y_isnan]
+            elif has_inf:
+                x = x[~x_isinf]
+                y = y[~y_isinf]
+
+            # Only do the comparison if actual values are left
+            if x.size == 0:
+                return
+
+        elif istime(x) and istime(y):
+            # If one is datetime64 and the other timedelta64 there is no point
+            if equal_nan and x.dtype.type == y.dtype.type:
+                x_isnat, y_isnat = isnat(x), isnat(y)
+
+                if any(x_isnat) or any(y_isnat):
+                    chk_same_position(x_isnat, y_isnat, hasval="NaT")
+
+                if any(x_isnat) or any(y_isnat):
+                    x = x[~x_isnat]
+                    y = y[~y_isnat]
+
+        val = comparison(x, y)
+
+        if isinstance(val, bool):
+            cond = val
+            reduced = [0]
+        else:
+            reduced = val.ravel()
+            cond = reduced.all()
+            reduced = reduced.tolist()
+        if not cond:
+            match = 100-100.0*reduced.count(1)/len(reduced)
+            msg = build_err_msg([x, y],
+                                err_msg
+                                + '\n(mismatch %s%%)' % (match,),
+                                verbose=verbose, header=header,
+                                names=('x', 'y'), precision=precision)
+            if not cond:
+                raise AssertionError(msg)
+    except ValueError:
+        import traceback
+        efmt = traceback.format_exc()
+        header = 'error during assertion:\n\n%s\n\n%s' % (efmt, header)
+
+        msg = build_err_msg([x, y], err_msg, verbose=verbose, header=header,
+                            names=('x', 'y'), precision=precision)
+        raise ValueError(msg)
+
+
+def assert_array_equal(x, y, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two array_like objects are not equal.
+
+    Given two array_like objects, check that the shape is equal and all
+    elements of these objects are equal. An exception is raised at
+    shape mismatch or conflicting values. In contrast to the standard usage
+    in numpy, NaNs are compared like numbers, no assertion is raised if
+    both objects have NaNs in the same positions.
+
+    The usual caution for verifying equality with floating point numbers is
+    advised.
+
+    Parameters
+    ----------
+    x : array_like
+        The actual object to check.
+    y : array_like
+        The desired, expected object.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired objects are not equal.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    The first assert does not raise an exception:
+
+    >>> np.testing.assert_array_equal([1.0,2.33333,np.nan],
+    ...                               [np.exp(0),2.33333, np.nan])
+
+    Assert fails with numerical inprecision with floats:
+
+    >>> np.testing.assert_array_equal([1.0,np.pi,np.nan],
+    ...                               [1, np.sqrt(np.pi)**2, np.nan])
+    ...
+    <type 'exceptions.ValueError'>:
+    AssertionError:
+    Arrays are not equal
+    <BLANKLINE>
+    (mismatch 50.0%)
+     x: array([ 1.        ,  3.14159265,         NaN])
+     y: array([ 1.        ,  3.14159265,         NaN])
+
+    Use `assert_allclose` or one of the nulp (number of floating point values)
+    functions for these cases instead:
+
+    >>> np.testing.assert_allclose([1.0,np.pi,np.nan],
+    ...                            [1, np.sqrt(np.pi)**2, np.nan],
+    ...                            rtol=1e-10, atol=0)
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
+                         verbose=verbose, header='Arrays are not equal')
+
+
+def assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two objects are not equal up to desired
+    precision.
+
+    .. note:: It is recommended to use one of `assert_allclose`,
+              `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
+              instead of this function for more consistent floating point
+              comparisons.
+
+    The test verifies identical shapes and that the elements of ``actual`` and
+    ``desired`` satisfy.
+
+        ``abs(desired-actual) < 1.5 * 10**(-decimal)``
+
+    That is a looser test than originally documented, but agrees with what the
+    actual implementation did up to rounding vagaries. An exception is raised
+    at shape mismatch or conflicting values. In contrast to the standard usage
+    in numpy, NaNs are compared like numbers, no assertion is raised if both
+    objects have NaNs in the same positions.
+
+    Parameters
+    ----------
+    x : array_like
+        The actual object to check.
+    y : array_like
+        The desired, expected object.
+    decimal : int, optional
+        Desired precision, default is 6.
+    err_msg : str, optional
+      The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    the first assert does not raise an exception
+
+    >>> np.testing.assert_array_almost_equal([1.0,2.333,np.nan],
+                                             [1.0,2.333,np.nan])
+
+    >>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
+    ...                                      [1.0,2.33339,np.nan], decimal=5)
+    ...
+    <type 'exceptions.AssertionError'>:
+    AssertionError:
+    Arrays are not almost equal
+    <BLANKLINE>
+    (mismatch 50.0%)
+     x: array([ 1.     ,  2.33333,      NaN])
+     y: array([ 1.     ,  2.33339,      NaN])
+
+    >>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
+    ...                                      [1.0,2.33333, 5], decimal=5)
+    <type 'exceptions.ValueError'>:
+    ValueError:
+    Arrays are not almost equal
+     x: array([ 1.     ,  2.33333,      NaN])
+     y: array([ 1.     ,  2.33333,  5.     ])
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    from numpy.core import around, number, float_, result_type, array
+    from numpy.core.numerictypes import issubdtype
+    from numpy.core.fromnumeric import any as npany
+
+    def compare(x, y):
+        try:
+            if npany(gisinf(x)) or npany( gisinf(y)):
+                xinfid = gisinf(x)
+                yinfid = gisinf(y)
+                if not (xinfid == yinfid).all():
+                    return False
+                # if one item, x and y is +- inf
+                if x.size == y.size == 1:
+                    return x == y
+                x = x[~xinfid]
+                y = y[~yinfid]
+        except (TypeError, NotImplementedError):
+            pass
+
+        # make sure y is an inexact type to avoid abs(MIN_INT); will cause
+        # casting of x later.
+        dtype = result_type(y, 1.)
+        y = array(y, dtype=dtype, copy=False, subok=True)
+        z = abs(x - y)
+
+        if not issubdtype(z.dtype, number):
+            z = z.astype(float_)  # handle object arrays
+
+        return z < 1.5 * 10.0**(-decimal)
+
+    assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,
+             header=('Arrays are not almost equal to %d decimals' % decimal),
+             precision=decimal)
+
+
+def assert_array_less(x, y, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two array_like objects are not ordered by less
+    than.
+
+    Given two array_like objects, check that the shape is equal and all
+    elements of the first object are strictly smaller than those of the
+    second object. An exception is raised at shape mismatch or incorrectly
+    ordered values. Shape mismatch does not raise if an object has zero
+    dimension. In contrast to the standard usage in numpy, NaNs are
+    compared, no assertion is raised if both objects have NaNs in the same
+    positions.
+
+
+
+    Parameters
+    ----------
+    x : array_like
+      The smaller object to check.
+    y : array_like
+      The larger object to compare.
+    err_msg : string
+      The error message to be printed in case of failure.
+    verbose : bool
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+      If actual and desired objects are not equal.
+
+    See Also
+    --------
+    assert_array_equal: tests objects for equality
+    assert_array_almost_equal: test objects for equality up to precision
+
+
+
+    Examples
+    --------
+    >>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1.1, 2.0, np.nan])
+    >>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1, 2.0, np.nan])
+    ...
+    <type 'exceptions.ValueError'>:
+    Arrays are not less-ordered
+    (mismatch 50.0%)
+     x: array([  1.,   1.,  NaN])
+     y: array([  1.,   2.,  NaN])
+
+    >>> np.testing.assert_array_less([1.0, 4.0], 3)
+    ...
+    <type 'exceptions.ValueError'>:
+    Arrays are not less-ordered
+    (mismatch 50.0%)
+     x: array([ 1.,  4.])
+     y: array(3)
+
+    >>> np.testing.assert_array_less([1.0, 2.0, 3.0], [4])
+    ...
+    <type 'exceptions.ValueError'>:
+    Arrays are not less-ordered
+    (shapes (3,), (1,) mismatch)
+     x: array([ 1.,  2.,  3.])
+     y: array([4])
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    assert_array_compare(operator.__lt__, x, y, err_msg=err_msg,
+                         verbose=verbose,
+                         header='Arrays are not less-ordered',
+                         equal_inf=False)
+
+
+def runstring(astr, dict):
+    exec(astr, dict)
+
+
+def assert_string_equal(actual, desired):
+    """
+    Test if two strings are equal.
+
+    If the given strings are equal, `assert_string_equal` does nothing.
+    If they are not equal, an AssertionError is raised, and the diff
+    between the strings is shown.
+
+    Parameters
+    ----------
+    actual : str
+        The string to test for equality against the expected string.
+    desired : str
+        The expected string.
+
+    Examples
+    --------
+    >>> np.testing.assert_string_equal('abc', 'abc')
+    >>> np.testing.assert_string_equal('abc', 'abcd')
+    Traceback (most recent call last):
+      File "<stdin>", line 1, in <module>
+    ...
+    AssertionError: Differences in strings:
+    - abc+ abcd?    +
+
+    """
+    # delay import of difflib to reduce startup time
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import difflib
+
+    if not isinstance(actual, str):
+        raise AssertionError(repr(type(actual)))
+    if not isinstance(desired, str):
+        raise AssertionError(repr(type(desired)))
+    if re.match(r'\A'+desired+r'\Z', actual, re.M):
+        return
+
+    diff = list(difflib.Differ().compare(actual.splitlines(1), desired.splitlines(1)))
+    diff_list = []
+    while diff:
+        d1 = diff.pop(0)
+        if d1.startswith('  '):
+            continue
+        if d1.startswith('- '):
+            l = [d1]
+            d2 = diff.pop(0)
+            if d2.startswith('? '):
+                l.append(d2)
+                d2 = diff.pop(0)
+            if not d2.startswith('+ '):
+                raise AssertionError(repr(d2))
+            l.append(d2)
+            if diff:
+                d3 = diff.pop(0)
+                if d3.startswith('? '):
+                    l.append(d3)
+                else:
+                    diff.insert(0, d3)
+            if re.match(r'\A'+d2[2:]+r'\Z', d1[2:]):
+                continue
+            diff_list.extend(l)
+            continue
+        raise AssertionError(repr(d1))
+    if not diff_list:
+        return
+    msg = 'Differences in strings:\n%s' % (''.join(diff_list)).rstrip()
+    if actual != desired:
+        raise AssertionError(msg)
+
+
+def rundocs(filename=None, raise_on_error=True):
+    """
+    Run doctests found in the given file.
+
+    By default `rundocs` raises an AssertionError on failure.
+
+    Parameters
+    ----------
+    filename : str
+        The path to the file for which the doctests are run.
+    raise_on_error : bool
+        Whether to raise an AssertionError when a doctest fails. Default is
+        True.
+
+    Notes
+    -----
+    The doctests can be run by the user/developer by adding the ``doctests``
+    argument to the ``test()`` call. For example, to run all tests (including
+    doctests) for `numpy.lib`:
+
+    >>> np.lib.test(doctests=True) #doctest: +SKIP
+    """
+    from numpy.compat import npy_load_module
+    import doctest
+    if filename is None:
+        f = sys._getframe(1)
+        filename = f.f_globals['__file__']
+    name = os.path.splitext(os.path.basename(filename))[0]
+    m = npy_load_module(name, filename)
+
+    tests = doctest.DocTestFinder().find(m)
+    runner = doctest.DocTestRunner(verbose=False)
+
+    msg = []
+    if raise_on_error:
+        out = lambda s: msg.append(s)
+    else:
+        out = None
+
+    for test in tests:
+        runner.run(test, out=out)
+
+    if runner.failures > 0 and raise_on_error:
+        raise AssertionError("Some doctests failed:\n%s" % "\n".join(msg))
+
+
+def raises(*exceptions):
+    """
+    This is actually a decorator and belongs in decorators.py.
+
+    """
+    import pytest
+
+    def raises_decorator(f):
+
+        def raiser(*args, **kwargs):
+            try:
+                f(*args, **kwargs)
+            except exceptions:
+                return
+            raise AssertionError()
+
+        return raiser
+
+    
+    return raises_decorator
+
+
+def assert_raises(exception_class, fn=None, *args, **kwargs):
+    """
+    assert_raises(exception_class, callable, *args, **kwargs)
+    assert_raises(exception_class)
+
+    Fail unless an exception of class exception_class is thrown
+    by callable when invoked with arguments args and keyword
+    arguments kwargs. If a different type of exception is
+    thrown, it will not be caught, and the test case will be
+    deemed to have suffered an error, exactly as for an
+    unexpected exception.
+
+    Alternatively, `assert_raises` can be used as a context manager:
+
+    >>> from numpy.testing import assert_raises
+    >>> with assert_raises(ZeroDivisionError):
+    ...     1 / 0
+
+    is equivalent to
+
+    >>> def div(x, y):
+    ...     return x / y
+    >>> assert_raises(ZeroDivisionError, div, 1, 0)
+
+    """
+    import pytest
+
+    __tracebackhide__ = True  # Hide traceback for py.test
+    
+    if fn is not None:
+        pytest.raises(exception_class, fn, *args,**kwargs)
+    else:
+        @contextlib.contextmanager
+        def assert_raises_context():
+            try:
+                yield
+            except BaseException as raised_exception:
+                assert isinstance(raised_exception, exception_class)
+            else:
+                raise ValueError('Function did not raise an exception')
+
+        return assert_raises_context()
+
+
+def assert_raises_regex(exception_class, expected_regexp, *args, **kwargs):
+    """
+    assert_raises_regex(exception_class, expected_regexp, callable, *args,
+                        **kwargs)
+    assert_raises_regex(exception_class, expected_regexp)
+
+    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.
+
+    Alternatively, can be used as a context manager like `assert_raises`.
+
+    Name of this function adheres to Python 3.2+ reference, but should work in
+    all versions down to 2.6.
+
+    Notes
+    -----
+    .. versionadded:: 1.9.0
+
+    """
+    import pytest
+    import unittest
+
+    class Dummy(unittest.TestCase):
+        def do_nothing(self):
+            pass
+
+    tmp = Dummy('do_nothing')
+
+    __tracebackhide__ = True  # Hide traceback for py.test
+    res = pytest.raises(exception_class, *args, **kwargs)
+
+    if sys.version_info.major >= 3:
+        funcname = tmp.assertRaisesRegex
+    else:
+        # Only present in Python 2.7, missing from unittest in 2.6
+        funcname = tmp.assertRaisesRegexp
+
+    return funcname(exception_class, expected_regexp, *args, **kwargs)
+
+
+def decorate_methods(cls, decorator, testmatch=None):
+    """
+    Apply a decorator to all methods in a class matching a regular expression.
+
+    The given decorator is applied to all public methods of `cls` that are
+    matched by the regular expression `testmatch`
+    (``testmatch.search(methodname)``). Methods that are private, i.e. start
+    with an underscore, are ignored.
+
+    Parameters
+    ----------
+    cls : class
+        Class whose methods to decorate.
+    decorator : function
+        Decorator to apply to methods
+    testmatch : compiled regexp or str, optional
+        The regular expression. Default value is None, in which case the
+        nose default (``re.compile(r'(?:^|[\\b_\\.%s-])[Tt]est' % os.sep)``)
+        is used.
+        If `testmatch` is a string, it is compiled to a regular expression
+        first.
+
+    """
+    if testmatch is None:
+        testmatch = re.compile(r'(?:^|[\\b_\\.%s-])[Tt]est' % os.sep)
+    else:
+        testmatch = re.compile(testmatch)
+    cls_attr = cls.__dict__
+
+    # delayed import to reduce startup time
+    from inspect import isfunction
+
+    methods = [_m for _m in cls_attr.values() if isfunction(_m)]
+    for function in methods:
+        try:
+            if hasattr(function, 'compat_func_name'):
+                funcname = function.compat_func_name
+            else:
+                funcname = function.__name__
+        except AttributeError:
+            # not a function
+            continue
+        if testmatch.search(funcname) and not funcname.startswith('_'):
+            setattr(cls, funcname, decorator(function))
+    return
+
+
+def measure(code_str,times=1,label=None):
+    """
+    Return elapsed time for executing code in the namespace of the caller.
+
+    The supplied code string is compiled with the Python builtin ``compile``.
+    The precision of the timing is 10 milli-seconds. If the code will execute
+    fast on this timescale, it can be executed many times to get reasonable
+    timing accuracy.
+
+    Parameters
+    ----------
+    code_str : str
+        The code to be timed.
+    times : int, optional
+        The number of times the code is executed. Default is 1. The code is
+        only compiled once.
+    label : str, optional
+        A label to identify `code_str` with. This is passed into ``compile``
+        as the second argument (for run-time error messages).
+
+    Returns
+    -------
+    elapsed : float
+        Total elapsed time in seconds for executing `code_str` `times` times.
+
+    Examples
+    --------
+    >>> etime = np.testing.measure('for i in range(1000): np.sqrt(i**2)',
+    ...                            times=times)
+    >>> print("Time for a single execution : ", etime / times, "s")
+    Time for a single execution :  0.005 s
+
+    """
+    frame = sys._getframe(1)
+    locs, globs = frame.f_locals, frame.f_globals
+
+    code = compile(code_str,
+                   'Test name: %s ' % label,
+                   'exec')
+    i = 0
+    elapsed = jiffies()
+    while i < times:
+        i += 1
+        exec(code, globs, locs)
+    elapsed = jiffies() - elapsed
+    return 0.01*elapsed
+
+
+def _assert_valid_refcount(op):
+    """
+    Check that ufuncs don't mishandle refcount of object `1`.
+    Used in a few regression tests.
+    """
+    if not HAS_REFCOUNT:
+        return True
+    import numpy as np
+
+    b = np.arange(100*100).reshape(100, 100)
+    c = b
+    i = 1
+
+    rc = sys.getrefcount(i)
+    for j in range(15):
+        d = op(b, c)
+    assert_(sys.getrefcount(i) >= rc)
+    del d  # for pyflakes
+
+
+def assert_allclose(actual, desired, rtol=1e-7, atol=0, equal_nan=True,
+                    err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two objects are not equal up to desired
+    tolerance.
+
+    The test is equivalent to ``allclose(actual, desired, rtol, atol)``.
+    It compares the difference between `actual` and `desired` to
+    ``atol + rtol * abs(desired)``.
+
+    .. versionadded:: 1.5.0
+
+    Parameters
+    ----------
+    actual : array_like
+        Array obtained.
+    desired : array_like
+        Array desired.
+    rtol : float, optional
+        Relative tolerance.
+    atol : float, optional
+        Absolute tolerance.
+    equal_nan : bool, optional.
+        If True, NaNs will compare equal.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_array_almost_equal_nulp, assert_array_max_ulp
+
+    Examples
+    --------
+    >>> x = [1e-5, 1e-3, 1e-1]
+    >>> y = np.arccos(np.cos(x))
+    >>> assert_allclose(x, y, rtol=1e-5, atol=0)
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+
+    def compare(x, y):
+        return np.core.numeric.isclose(x, y, rtol=rtol, atol=atol,
+                                       equal_nan=equal_nan)
+
+    actual, desired = np.asanyarray(actual), np.asanyarray(desired)
+    header = 'Not equal to tolerance rtol=%g, atol=%g' % (rtol, atol)
+    assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
+                         verbose=verbose, header=header, equal_nan=equal_nan)
+
+
+def assert_array_almost_equal_nulp(x, y, nulp=1):
+    """
+    Compare two arrays relatively to their spacing.
+
+    This is a relatively robust method to compare two arrays whose amplitude
+    is variable.
+
+    Parameters
+    ----------
+    x, y : array_like
+        Input arrays.
+    nulp : int, optional
+        The maximum number of unit in the last place for tolerance (see Notes).
+        Default is 1.
+
+    Returns
+    -------
+    None
+
+    Raises
+    ------
+    AssertionError
+        If the spacing between `x` and `y` for one or more elements is larger
+        than `nulp`.
+
+    See Also
+    --------
+    assert_array_max_ulp : Check that all items of arrays differ in at most
+        N Units in the Last Place.
+    spacing : Return the distance between x and the nearest adjacent number.
+
+    Notes
+    -----
+    An assertion is raised if the following condition is not met::
+
+        abs(x - y) <= nulps * spacing(maximum(abs(x), abs(y)))
+
+    Examples
+    --------
+    >>> x = np.array([1., 1e-10, 1e-20])
+    >>> eps = np.finfo(x.dtype).eps
+    >>> np.testing.assert_array_almost_equal_nulp(x, x*eps/2 + x)
+
+    >>> np.testing.assert_array_almost_equal_nulp(x, x*eps + x)
+    Traceback (most recent call last):
+      ...
+    AssertionError: X and Y are not equal to 1 ULP (max is 2)
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+    ax = np.abs(x)
+    ay = np.abs(y)
+    ref = nulp * np.spacing(np.where(ax > ay, ax, ay))
+    if not np.all(np.abs(x-y) <= ref):
+        if np.iscomplexobj(x) or np.iscomplexobj(y):
+            msg = "X and Y are not equal to %d ULP" % nulp
+        else:
+            max_nulp = np.max(nulp_diff(x, y))
+            msg = "X and Y are not equal to %d ULP (max is %g)" % (nulp, max_nulp)
+        raise AssertionError(msg)
+
+
+def assert_array_max_ulp(a, b, maxulp=1, dtype=None):
+    """
+    Check that all items of arrays differ in at most N Units in the Last Place.
+
+    Parameters
+    ----------
+    a, b : array_like
+        Input arrays to be compared.
+    maxulp : int, optional
+        The maximum number of units in the last place that elements of `a` and
+        `b` can differ. Default is 1.
+    dtype : dtype, optional
+        Data-type to convert `a` and `b` to if given. Default is None.
+
+    Returns
+    -------
+    ret : ndarray
+        Array containing number of representable floating point numbers between
+        items in `a` and `b`.
+
+    Raises
+    ------
+    AssertionError
+        If one or more elements differ by more than `maxulp`.
+
+    See Also
+    --------
+    assert_array_almost_equal_nulp : Compare two arrays relatively to their
+        spacing.
+
+    Examples
+    --------
+    >>> a = np.linspace(0., 1., 100)
+    >>> res = np.testing.assert_array_max_ulp(a, np.arcsin(np.sin(a)))
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+    ret = nulp_diff(a, b, dtype)
+    if not np.all(ret <= maxulp):
+        raise AssertionError("Arrays are not almost equal up to %g ULP" %
+                             maxulp)
+    return ret
+
+
+def nulp_diff(x, y, dtype=None):
+    """For each item in x and y, return the number of representable floating
+    points between them.
+
+    Parameters
+    ----------
+    x : array_like
+        first input array
+    y : array_like
+        second input array
+    dtype : dtype, optional
+        Data-type to convert `x` and `y` to if given. Default is None.
+
+    Returns
+    -------
+    nulp : array_like
+        number of representable floating point numbers between each item in x
+        and y.
+
+    Examples
+    --------
+    # By definition, epsilon is the smallest number such as 1 + eps != 1, so
+    # there should be exactly one ULP between 1 and 1 + eps
+    >>> nulp_diff(1, 1 + np.finfo(x.dtype).eps)
+    1.0
+    """
+    import numpy as np
+    if dtype:
+        x = np.array(x, dtype=dtype)
+        y = np.array(y, dtype=dtype)
+    else:
+        x = np.array(x)
+        y = np.array(y)
+
+    t = np.common_type(x, y)
+    if np.iscomplexobj(x) or np.iscomplexobj(y):
+        raise NotImplementedError("_nulp not implemented for complex array")
+
+    x = np.array(x, dtype=t)
+    y = np.array(y, dtype=t)
+
+    if not x.shape == y.shape:
+        raise ValueError("x and y do not have the same shape: %s - %s" %
+                         (x.shape, y.shape))
+
+    def _diff(rx, ry, vdt):
+        diff = np.array(rx-ry, dtype=vdt)
+        return np.abs(diff)
+
+    rx = integer_repr(x)
+    ry = integer_repr(y)
+    return _diff(rx, ry, t)
+
+
+def _integer_repr(x, vdt, comp):
+    # Reinterpret binary representation of the float as sign-magnitude:
+    # take into account two-complement representation
+    # See also
+    # http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm
+    rx = x.view(vdt)
+    if not (rx.size == 1):
+        rx[rx < 0] = comp - rx[rx < 0]
+    else:
+        if rx < 0:
+            rx = comp - rx
+
+    return rx
+
+
+def integer_repr(x):
+    """Return the signed-magnitude interpretation of the binary representation of
+    x."""
+    import numpy as np
+    if x.dtype == np.float32:
+        return _integer_repr(x, np.int32, np.int32(-2**31))
+    elif x.dtype == np.float64:
+        return _integer_repr(x, np.int64, np.int64(-2**63))
+    else:
+        raise ValueError("Unsupported dtype %s" % x.dtype)
+
+
+# The following two classes are copied from python 2.6 warnings module (context
+# manager)
+class WarningMessage(object):
+
+    """
+    Holds the result of a single showwarning() call.
+
+    Deprecated in 1.8.0
+
+    Notes
+    -----
+    `WarningMessage` is copied from the Python 2.6 warnings module,
+    so it can be used in NumPy with older Python versions.
+
+    """
+
+    _WARNING_DETAILS = ("message", "category", "filename", "lineno", "file",
+                        "line")
+
+    def __init__(self, message, category, filename, lineno, file=None,
+                    line=None):
+        local_values = locals()
+        for attr in self._WARNING_DETAILS:
+            setattr(self, attr, local_values[attr])
+        if category:
+            self._category_name = category.__name__
+        else:
+            self._category_name = None
+
+    def __str__(self):
+        return ("{message : %r, category : %r, filename : %r, lineno : %s, "
+                    "line : %r}" % (self.message, self._category_name,
+                                    self.filename, self.lineno, self.line))
+
+
+class WarningManager(object):
+    """
+    A context manager that copies and restores the warnings filter upon
+    exiting the context.
+
+    The 'record' argument specifies whether warnings should be captured by a
+    custom implementation of ``warnings.showwarning()`` and be appended to a
+    list returned by the context manager. Otherwise None is returned by the
+    context manager. The objects appended to the list are arguments whose
+    attributes mirror the arguments to ``showwarning()``.
+
+    The 'module' argument is to specify an alternative module to the module
+    named 'warnings' and imported under that name. This argument is only useful
+    when testing the warnings module itself.
+
+    Deprecated in 1.8.0
+
+    Notes
+    -----
+    `WarningManager` is a copy of the ``catch_warnings`` context manager
+    from the Python 2.6 warnings module, with slight modifications.
+    It is copied so it can be used in NumPy with older Python versions.
+
+    """
+
+    def __init__(self, record=False, module=None):
+        self._record = record
+        if module is None:
+            self._module = sys.modules['warnings']
+        else:
+            self._module = module
+        self._entered = False
+
+    def __enter__(self):
+        if self._entered:
+            raise RuntimeError("Cannot enter %r twice" % self)
+        self._entered = True
+        self._filters = self._module.filters
+        self._module.filters = self._filters[:]
+        self._showwarning = self._module.showwarning
+        if self._record:
+            log = []
+
+            def showwarning(*args, **kwargs):
+                log.append(WarningMessage(*args, **kwargs))
+            self._module.showwarning = showwarning
+            return log
+        else:
+            return None
+
+    def __exit__(self):
+        if not self._entered:
+            raise RuntimeError("Cannot exit %r without entering first" % self)
+        self._module.filters = self._filters
+        self._module.showwarning = self._showwarning
+
+
+@contextlib.contextmanager
+def _assert_warns_context(warning_class, name=None):
+    __tracebackhide__ = True  # Hide traceback for py.test
+    with suppress_warnings() as sup:
+        l = sup.record(warning_class)
+        yield
+        if not len(l) > 0:
+            name_str = " when calling %s" % name if name is not None else ""
+            raise AssertionError("No warning raised" + name_str)
+
+
+def assert_warns(warning_class, *args, **kwargs):
+    """
+    Fail unless the given callable throws the specified warning.
+
+    A warning of class warning_class should be thrown by the callable when
+    invoked with arguments args and keyword arguments kwargs.
+    If a different type of warning is thrown, it will not be caught.
+
+    If called with all arguments other than the warning class omitted, may be
+    used as a context manager:
+
+        with assert_warns(SomeWarning):
+            do_something()
+
+    The ability to be used as a context manager is new in NumPy v1.11.0.
+
+    .. versionadded:: 1.4.0
+
+    Parameters
+    ----------
+    warning_class : class
+        The class defining the warning that `func` is expected to throw.
+    func : callable
+        The callable to test.
+    \\*args : Arguments
+        Arguments passed to `func`.
+    \\*\\*kwargs : Kwargs
+        Keyword arguments passed to `func`.
+
+    Returns
+    -------
+    The value returned by `func`.
+
+    """
+    if not args:
+        return _assert_warns_context(warning_class)
+
+    func = args[0]
+    args = args[1:]
+    with _assert_warns_context(warning_class, name=func.__name__):
+        return func(*args, **kwargs)
+
+
+@contextlib.contextmanager
+def _assert_no_warnings_context(name=None):
+    __tracebackhide__ = True  # Hide traceback for py.test
+    with warnings.catch_warnings(record=True) as l:
+        warnings.simplefilter('always')
+        yield
+        if len(l) > 0:
+            name_str = " when calling %s" % name if name is not None else ""
+            raise AssertionError("Got warnings%s: %s" % (name_str, l))
+
+
+def assert_no_warnings(*args, **kwargs):
+    """
+    Fail if the given callable produces any warnings.
+
+    If called with all arguments omitted, may be used as a context manager:
+
+        with assert_no_warnings():
+            do_something()
+
+    The ability to be used as a context manager is new in NumPy v1.11.0.
+
+    .. versionadded:: 1.7.0
+
+    Parameters
+    ----------
+    func : callable
+        The callable to test.
+    \\*args : Arguments
+        Arguments passed to `func`.
+    \\*\\*kwargs : Kwargs
+        Keyword arguments passed to `func`.
+
+    Returns
+    -------
+    The value returned by `func`.
+
+    """
+    if not args:
+        return _assert_no_warnings_context()
+
+    func = args[0]
+    args = args[1:]
+    with _assert_no_warnings_context(name=func.__name__):
+        return func(*args, **kwargs)
+
+
+def _gen_alignment_data(dtype=float32, type='binary', max_size=24):
+    """
+    generator producing data with different alignment and offsets
+    to test simd vectorization
+
+    Parameters
+    ----------
+    dtype : dtype
+        data type to produce
+    type : string
+        'unary': create data for unary operations, creates one input
+                 and output array
+        'binary': create data for unary operations, creates two input
+                 and output array
+    max_size : integer
+        maximum size of data to produce
+
+    Returns
+    -------
+    if type is 'unary' yields one output, one input array and a message
+    containing information on the data
+    if type is 'binary' yields one output array, two input array and a message
+    containing information on the data
+
+    """
+    ufmt = 'unary offset=(%d, %d), size=%d, dtype=%r, %s'
+    bfmt = 'binary offset=(%d, %d, %d), size=%d, dtype=%r, %s'
+    for o in range(3):
+        for s in range(o + 2, max(o + 3, max_size)):
+            if type == 'unary':
+                inp = lambda: arange(s, dtype=dtype)[o:]
+                out = empty((s,), dtype=dtype)[o:]
+                yield out, inp(), ufmt % (o, o, s, dtype, 'out of place')
+                d = inp()
+                yield d, d, ufmt % (o, o, s, dtype, 'in place')
+                yield out[1:], inp()[:-1], ufmt % \
+                    (o + 1, o, s - 1, dtype, 'out of place')
+                yield out[:-1], inp()[1:], ufmt % \
+                    (o, o + 1, s - 1, dtype, 'out of place')
+                yield inp()[:-1], inp()[1:], ufmt % \
+                    (o, o + 1, s - 1, dtype, 'aliased')
+                yield inp()[1:], inp()[:-1], ufmt % \
+                    (o + 1, o, s - 1, dtype, 'aliased')
+            if type == 'binary':
+                inp1 = lambda: arange(s, dtype=dtype)[o:]
+                inp2 = lambda: arange(s, dtype=dtype)[o:]
+                out = empty((s,), dtype=dtype)[o:]
+                yield out, inp1(), inp2(),  bfmt % \
+                    (o, o, o, s, dtype, 'out of place')
+                d = inp1()
+                yield d, d, inp2(), bfmt % \
+                    (o, o, o, s, dtype, 'in place1')
+                d = inp2()
+                yield d, inp1(), d, bfmt % \
+                    (o, o, o, s, dtype, 'in place2')
+                yield out[1:], inp1()[:-1], inp2()[:-1], bfmt % \
+                    (o + 1, o, o, s - 1, dtype, 'out of place')
+                yield out[:-1], inp1()[1:], inp2()[:-1], bfmt % \
+                    (o, o + 1, o, s - 1, dtype, 'out of place')
+                yield out[:-1], inp1()[:-1], inp2()[1:], bfmt % \
+                    (o, o, o + 1, s - 1, dtype, 'out of place')
+                yield inp1()[1:], inp1()[:-1], inp2()[:-1], bfmt % \
+                    (o + 1, o, o, s - 1, dtype, 'aliased')
+                yield inp1()[:-1], inp1()[1:], inp2()[:-1], bfmt % \
+                    (o, o + 1, o, s - 1, dtype, 'aliased')
+                yield inp1()[:-1], inp1()[:-1], inp2()[1:], bfmt % \
+                    (o, o, o + 1, s - 1, dtype, 'aliased')
+
+
+
+@contextlib.contextmanager
+def tempdir(*args, **kwargs):
+    """Context manager to provide a temporary test folder.
+
+    All arguments are passed as this to the underlying tempfile.mkdtemp
+    function.
+
+    """
+    tmpdir = mkdtemp(*args, **kwargs)
+    try:
+        yield tmpdir
+    finally:
+        shutil.rmtree(tmpdir)
+
+
+@contextlib.contextmanager
+def temppath(*args, **kwargs):
+    """Context manager for temporary files.
+
+    Context manager that returns the path to a closed temporary file. Its
+    parameters are the same as for tempfile.mkstemp and are passed directly
+    to that function. The underlying file is removed when the context is
+    exited, so it should be closed at that time.
+
+    Windows does not allow a temporary file to be opened if it is already
+    open, so the underlying file must be closed after opening before it
+    can be opened again.
+
+    """
+    fd, path = mkstemp(*args, **kwargs)
+    os.close(fd)
+    try:
+        yield path
+    finally:
+        os.remove(path)
+
+
+class clear_and_catch_warnings(warnings.catch_warnings):
+    """ Context manager that resets warning registry for catching warnings
+
+    Warnings can be slippery, because, whenever a warning is triggered, Python
+    adds a ``__warningregistry__`` member to the *calling* module.  This makes
+    it impossible to retrigger the warning in this module, whatever you put in
+    the warnings filters.  This context manager accepts a sequence of `modules`
+    as a keyword argument to its constructor and:
+
+    * stores and removes any ``__warningregistry__`` entries in given `modules`
+      on entry;
+    * resets ``__warningregistry__`` to its previous state on exit.
+
+    This makes it possible to trigger any warning afresh inside the context
+    manager without disturbing the state of warnings outside.
+
+    For compatibility with Python 3.0, please consider all arguments to be
+    keyword-only.
+
+    Parameters
+    ----------
+    record : bool, optional
+        Specifies whether warnings should be captured by a custom
+        implementation of ``warnings.showwarning()`` and be appended to a list
+        returned by the context manager. Otherwise None is returned by the
+        context manager. The objects appended to the list are arguments whose
+        attributes mirror the arguments to ``showwarning()``.
+    modules : sequence, optional
+        Sequence of modules for which to reset warnings registry on entry and
+        restore on exit. To work correctly, all 'ignore' filters should
+        filter by one of these modules.
+
+    Examples
+    --------
+    >>> import warnings
+    >>> with clear_and_catch_warnings(modules=[np.core.fromnumeric]):
+    ...     warnings.simplefilter('always')
+    ...     warnings.filterwarnings('ignore', module='np.core.fromnumeric')
+    ...     # do something that raises a warning but ignore those in
+    ...     # np.core.fromnumeric
+    """
+    class_modules = ()
+
+    def __init__(self, record=False, modules=()):
+        self.modules = set(modules).union(self.class_modules)
+        self._warnreg_copies = {}
+        super(clear_and_catch_warnings, self).__init__(record=record)
+
+    def __enter__(self):
+        for mod in self.modules:
+            if hasattr(mod, '__warningregistry__'):
+                mod_reg = mod.__warningregistry__
+                self._warnreg_copies[mod] = mod_reg.copy()
+                mod_reg.clear()
+        return super(clear_and_catch_warnings, self).__enter__()
+
+    def __exit__(self, *exc_info):
+        super(clear_and_catch_warnings, self).__exit__(*exc_info)
+        for mod in self.modules:
+            if hasattr(mod, '__warningregistry__'):
+                mod.__warningregistry__.clear()
+            if mod in self._warnreg_copies:
+                mod.__warningregistry__.update(self._warnreg_copies[mod])
+
+
+class suppress_warnings(object):
+    """
+    Context manager and decorator doing much the same as
+    ``warnings.catch_warnings``.
+
+    However, it also provides a filter mechanism to work around
+    http://bugs.python.org/issue4180.
+
+    This bug causes Python before 3.4 to not reliably show warnings again
+    after they have been ignored once (even within catch_warnings). It
+    means that no "ignore" filter can be used easily, since following
+    tests might need to see the warning. Additionally it allows easier
+    specificity for testing warnings and can be nested.
+
+    Parameters
+    ----------
+    forwarding_rule : str, optional
+        One of "always", "once", "module", or "location". Analogous to
+        the usual warnings module filter mode, it is useful to reduce
+        noise mostly on the outmost level. Unsuppressed and unrecorded
+        warnings will be forwarded based on this rule. Defaults to "always".
+        "location" is equivalent to the warnings "default", match by exact
+        location the warning warning originated from.
+
+    Notes
+    -----
+    Filters added inside the context manager will be discarded again
+    when leaving it. Upon entering all filters defined outside a
+    context will be applied automatically.
+
+    When a recording filter is added, matching warnings are stored in the
+    ``log`` attribute as well as in the list returned by ``record``.
+
+    If filters are added and the ``module`` keyword is given, the
+    warning registry of this module will additionally be cleared when
+    applying it, entering the context, or exiting it. This could cause
+    warnings to appear a second time after leaving the context if they
+    were configured to be printed once (default) and were already
+    printed before the context was entered.
+
+    Nesting this context manager will work as expected when the
+    forwarding rule is "always" (default). Unfiltered and unrecorded
+    warnings will be passed out and be matched by the outer level.
+    On the outmost level they will be printed (or caught by another
+    warnings context). The forwarding rule argument can modify this
+    behaviour.
+
+    Like ``catch_warnings`` this context manager is not threadsafe.
+
+    Examples
+    --------
+    >>> with suppress_warnings() as sup:
+    ...     sup.filter(DeprecationWarning, "Some text")
+    ...     sup.filter(module=np.ma.core)
+    ...     log = sup.record(FutureWarning, "Does this occur?")
+    ...     command_giving_warnings()
+    ...     # The FutureWarning was given once, the filtered warnings were
+    ...     # ignored. All other warnings abide outside settings (may be
+    ...     # printed/error)
+    ...     assert_(len(log) == 1)
+    ...     assert_(len(sup.log) == 1)  # also stored in log attribute
+
+    Or as a decorator:
+
+    >>> sup = suppress_warnings()
+    >>> sup.filter(module=np.ma.core)  # module must match exact
+    >>> @sup
+    >>> def some_function():
+    ...     # do something which causes a warning in np.ma.core
+    ...     pass
+    """
+    def __init__(self, forwarding_rule="always"):
+        self._entered = False
+
+        # Suppressions are either instance or defined inside one with block:
+        self._suppressions = []
+
+        if forwarding_rule not in {"always", "module", "once", "location"}:
+            raise ValueError("unsupported forwarding rule.")
+        self._forwarding_rule = forwarding_rule
+
+    def _clear_registries(self):
+        if hasattr(warnings, "_filters_mutated"):
+            # clearing the registry should not be necessary on new pythons,
+            # instead the filters should be mutated.
+            warnings._filters_mutated()
+            return
+        # Simply clear the registry, this should normally be harmless,
+        # note that on new pythons it would be invalidated anyway.
+        for module in self._tmp_modules:
+            if hasattr(module, "__warningregistry__"):
+                module.__warningregistry__.clear()
+
+    def _filter(self, category=Warning, message="", module=None, record=False):
+        if record:
+            record = []  # The log where to store warnings
+        else:
+            record = None
+        if self._entered:
+            if module is None:
+                warnings.filterwarnings(
+                    "always", category=category, message=message)
+            else:
+                module_regex = module.__name__.replace('.', r'\.') + '$'
+                warnings.filterwarnings(
+                    "always", category=category, message=message,
+                    module=module_regex)
+                self._tmp_modules.add(module)
+                self._clear_registries()
+
+            self._tmp_suppressions.append(
+                (category, message, re.compile(message, re.I), module, record))
+        else:
+            self._suppressions.append(
+                (category, message, re.compile(message, re.I), module, record))
+
+        return record
+
+    def filter(self, category=Warning, message="", module=None):
+        """
+        Add a new suppressing filter or apply it if the state is entered.
+
+        Parameters
+        ----------
+        category : class, optional
+            Warning class to filter
+        message : string, optional
+            Regular expression matching the warning message.
+        module : module, optional
+            Module to filter for. Note that the module (and its file)
+            must match exactly and cannot be a submodule. This may make
+            it unreliable for external modules.
+
+        Notes
+        -----
+        When added within a context, filters are only added inside
+        the context and will be forgotten when the context is exited.
+        """
+        self._filter(category=category, message=message, module=module,
+                     record=False)
+
+    def record(self, category=Warning, message="", module=None):
+        """
+        Append a new recording filter or apply it if the state is entered.
+
+        All warnings matching will be appended to the ``log`` attribute.
+
+        Parameters
+        ----------
+        category : class, optional
+            Warning class to filter
+        message : string, optional
+            Regular expression matching the warning message.
+        module : module, optional
+            Module to filter for. Note that the module (and its file)
+            must match exactly and cannot be a submodule. This may make
+            it unreliable for external modules.
+
+        Returns
+        -------
+        log : list
+            A list which will be filled with all matched warnings.
+
+        Notes
+        -----
+        When added within a context, filters are only added inside
+        the context and will be forgotten when the context is exited.
+        """
+        return self._filter(category=category, message=message, module=module,
+                            record=True)
+
+    def __enter__(self):
+        if self._entered:
+            raise RuntimeError("cannot enter suppress_warnings twice.")
+
+        self._orig_show = warnings.showwarning
+        self._filters = warnings.filters
+        warnings.filters = self._filters[:]
+
+        self._entered = True
+        self._tmp_suppressions = []
+        self._tmp_modules = set()
+        self._forwarded = set()
+
+        self.log = []  # reset global log (no need to keep same list)
+
+        for cat, mess, _, mod, log in self._suppressions:
+            if log is not None:
+                del log[:]  # clear the log
+            if mod is None:
+                warnings.filterwarnings(
+                    "always", category=cat, message=mess)
+            else:
+                module_regex = mod.__name__.replace('.', r'\.') + '$'
+                warnings.filterwarnings(
+                    "always", category=cat, message=mess,
+                    module=module_regex)
+                self._tmp_modules.add(mod)
+        warnings.showwarning = self._showwarning
+        self._clear_registries()
+
+        return self
+
+    def __exit__(self, *exc_info):
+        warnings.showwarning = self._orig_show
+        warnings.filters = self._filters
+        self._clear_registries()
+        self._entered = False
+        del self._orig_show
+        del self._filters
+
+    def _showwarning(self, message, category, filename, lineno,
+                     *args, **kwargs):
+        use_warnmsg = kwargs.pop("use_warnmsg", None)
+        for cat, _, pattern, mod, rec in (
+                self._suppressions + self._tmp_suppressions)[::-1]:
+            if (issubclass(category, cat) and
+                    pattern.match(message.args[0]) is not None):
+                if mod is None:
+                    # Message and category match, either recorded or ignored
+                    if rec is not None:
+                        msg = WarningMessage(message, category, filename,
+                                             lineno, **kwargs)
+                        self.log.append(msg)
+                        rec.append(msg)
+                    return
+                # Use startswith, because warnings strips the c or o from
+                # .pyc/.pyo files.
+                elif mod.__file__.startswith(filename):
+                    # The message and module (filename) match
+                    if rec is not None:
+                        msg = WarningMessage(message, category, filename,
+                                             lineno, **kwargs)
+                        self.log.append(msg)
+                        rec.append(msg)
+                    return
+
+        # There is no filter in place, so pass to the outside handler
+        # unless we should only pass it once
+        if self._forwarding_rule == "always":
+            if use_warnmsg is None:
+                self._orig_show(message, category, filename, lineno,
+                                *args, **kwargs)
+            else:
+                self._orig_showmsg(use_warnmsg)
+            return
+
+        if self._forwarding_rule == "once":
+            signature = (message.args, category)
+        elif self._forwarding_rule == "module":
+            signature = (message.args, category, filename)
+        elif self._forwarding_rule == "location":
+            signature = (message.args, category, filename, lineno)
+
+        if signature in self._forwarded:
+            return
+        self._forwarded.add(signature)
+        if use_warnmsg is None:
+            self._orig_show(message, category, filename, lineno, *args,
+                            **kwargs)
+        else:
+            self._orig_showmsg(use_warnmsg)
+
+    def __call__(self, func):
+        """
+        Function decorator to apply certain suppressions to a whole
+        function.
+        """
+        @wraps(func)
+        def new_func(*args, **kwargs):
+            with self:
+                return func(*args, **kwargs)
+
+        return new_func
diff --git a/numpy/testing/setup.py b/numpy/testing/setup.py
index a5e9656a3..5a0f977d9 100755
--- a/numpy/testing/setup.py
+++ b/numpy/testing/setup.py
@@ -7,6 +7,7 @@ def configuration(parent_package='',top_path=None):
     config = Configuration('testing', parent_package, top_path)
 
     config.add_subpackage('nose_tools')
+    config.add_subpackage('pytest_tools')
     config.add_data_dir('tests')
     return config
 
diff --git a/numpy/testing/tests/test_decorators.py b/numpy/testing/tests/test_decorators.py
index 1258a9296..62329ab7d 100644
--- a/numpy/testing/tests/test_decorators.py
+++ b/numpy/testing/tests/test_decorators.py
@@ -48,7 +48,7 @@ def test_skip_functions_hardcoded():
         f1('a')
     except DidntSkipException:
         raise Exception('Failed to skip')
-    except SkipTest:
+    except SkipTest().__class__:
         pass
 
     @dec.skipif(False)
@@ -59,7 +59,7 @@ def test_skip_functions_hardcoded():
         f2('a')
     except DidntSkipException:
         pass
-    except SkipTest:
+    except SkipTest().__class__:
         raise Exception('Skipped when not expected to')
 
 
@@ -76,7 +76,7 @@ def test_skip_functions_callable():
         f1('a')
     except DidntSkipException:
         raise Exception('Failed to skip')
-    except SkipTest:
+    except SkipTest().__class__:
         pass
 
     @dec.skipif(skip_tester)
@@ -88,7 +88,7 @@ def test_skip_functions_callable():
         f2('a')
     except DidntSkipException:
         pass
-    except SkipTest:
+    except SkipTest().__class__:
         raise Exception('Skipped when not expected to')
 
 
@@ -101,7 +101,7 @@ def test_skip_generators_hardcoded():
     try:
         for j in g1(10):
             pass
-    except KnownFailureException:
+    except KnownFailureException().__class__:
         pass
     else:
         raise Exception('Failed to mark as known failure')
@@ -115,7 +115,7 @@ def test_skip_generators_hardcoded():
     try:
         for j in g2(10):
             pass
-    except KnownFailureException:
+    except KnownFailureException().__class__:
         raise Exception('Marked incorrectly as known failure')
     except DidntSkipException:
         pass
@@ -134,7 +134,7 @@ def test_skip_generators_callable():
         skip_flag = 'skip me!'
         for j in g1(10):
             pass
-    except KnownFailureException:
+    except KnownFailureException().__class__:
         pass
     else:
         raise Exception('Failed to mark as known failure')
@@ -149,7 +149,7 @@ def test_skip_generators_callable():
         skip_flag = 'do not skip'
         for j in g2(10):
             pass
-    except KnownFailureException:
+    except KnownFailureException().__class__:
         raise Exception('Marked incorrectly as known failure')
     except DidntSkipException:
         pass
diff --git a/numpy/testing/utils.py b/numpy/testing/utils.py
index 7ecb68f47..a0218c4e6 100644
--- a/numpy/testing/utils.py
+++ b/numpy/testing/utils.py
@@ -3,6 +3,10 @@ Back compatibility utils module. It will import the appropriate
 set of tools
 
 """
+import os
+
+from .nose_tools.utils import *
+
 __all__ = [
         'assert_equal', 'assert_almost_equal', 'assert_approx_equal',
         'assert_array_equal', 'assert_array_less', 'assert_string_equal',
@@ -16,5 +20,3 @@ __all__ = [
         'HAS_REFCOUNT', 'suppress_warnings', 'assert_array_compare',
         '_assert_valid_refcount', '_gen_alignment_data',
         ]
-
-from .nose_tools.utils import *