MAINT: Rearrange numpy/testing files.

This is to prepare for the switch to pytest.

* Rename `numpy/testing/nose_tools` to `numpy/testing/_private`.
* Redirect imports as needed.
* Copy `_testutils.py` from scipy to `numpy/testing/_private`.
* Rename `_testutils.py` to `_pytester.py` and remove unneeded bits.

6 files changed, 0 insertions, 3982 deletions

diff --git a/numpy/testing/nose_tools/__init__.py b/numpy/testing/nose_tools/__init__.py
deleted file mode 100644
index e69de29bb..000000000
--- a/numpy/testing/nose_tools/__init__.py
+++ /dev/null
diff --git a/numpy/testing/nose_tools/decorators.py b/numpy/testing/nose_tools/decorators.py
deleted file mode 100644
index dee832404..000000000
--- a/numpy/testing/nose_tools/decorators.py
+++ /dev/null
@@ -1,292 +0,0 @@
-"""
-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 object need to use
-::
-
-  nose.tools.make_decorator(original_function)(decorator)
-
-in returning the decorator, in order to preserve meta-data such as
-function name, setup and teardown functions and so on - see
-``nose.tools`` for more information.
-
-"""
-from __future__ import division, absolute_import, print_function
-
-try:
-    # Accessing collections abstact classes from collections
-    # has been deprecated since Python 3.3
-    import collections.abc as collections_abc
-except ImportError:
-    import collections as collections_abc
-
-from .utils import SkipTest, assert_warns, HAS_REFCOUNT
-
-__all__ = ['slow', 'setastest', 'skipif', 'knownfailureif', 'deprecated',
-           'parametrize', '_needs_refcount',]
-
-
-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 label 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')
-
-    """
-
-    t.slow = True
-    return 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.
-
-    Notes
-    -----
-    This decorator can't use the nose namespace, because it can be
-    called from a non-test module. See also ``istest`` and ``nottest`` in
-    ``nose.tools``.
-
-    Examples
-    --------
-    `setastest` can be used in the following way::
-
-      from numpy.testing import dec
-
-      @dec.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
-    -----
-    The decorator itself is decorated with the ``nose.tools.make_decorator``
-    function in order to transmit function name, and various other metadata.
-
-    """
-
-    def skip_decorator(f):
-        # Local import to avoid a hard nose dependency and only incur the
-        # import time overhead at actual test-time.
-        import nose
-
-        # Allow for both boolean or callable skip conditions.
-        if isinstance(skip_condition, collections_abc.Callable):
-            skip_val = lambda: skip_condition()
-        else:
-            skip_val = lambda: skip_condition
-
-        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)
-
-        # We need to define *two* skippers because Python doesn't allow both
-        # return with value and yield inside the same function.
-        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 nose.util.isgenerator(f):
-            skipper = skipper_gen
-        else:
-            skipper = skipper_func
-
-        return nose.tools.make_decorator(f)(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 decorated with the ``nose.tools.make_decorator``
-    function in order to transmit function name, and various other metadata.
-
-    """
-    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_abc.Callable):
-        fail_val = lambda: fail_condition()
-    else:
-        fail_val = lambda: fail_condition
-
-    def knownfail_decorator(f):
-        # Local import to avoid a hard nose dependency and only incur the
-        # import time overhead at actual test-time.
-        import nose
-        from .noseclasses import KnownFailureException
-
-        def knownfailer(*args, **kwargs):
-            if fail_val():
-                raise KnownFailureException(msg)
-            else:
-                return f(*args, **kwargs)
-        return nose.tools.make_decorator(f)(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):
-        # Local import to avoid a hard nose dependency and only incur the
-        # import time overhead at actual test-time.
-        import nose
-
-        def _deprecated_imp(*args, **kwargs):
-            # Poor man's replacement for the with statement
-            with assert_warns(DeprecationWarning):
-                f(*args, **kwargs)
-
-        if isinstance(conditional, collections_abc.Callable):
-            cond = conditional()
-        else:
-            cond = conditional
-        if cond:
-            return nose.tools.make_decorator(f)(_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.
-
-    .. versionadded:: 1.14.0
-
-    """
-    from .parameterized import parameterized
-
-    return parameterized(input)
-
-_needs_refcount = skipif(not HAS_REFCOUNT, "python has no sys.getrefcount")
diff --git a/numpy/testing/nose_tools/noseclasses.py b/numpy/testing/nose_tools/noseclasses.py
deleted file mode 100644
index 08dec0ca9..000000000
--- a/numpy/testing/nose_tools/noseclasses.py
+++ /dev/null
@@ -1,366 +0,0 @@
-# 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 sys
-import doctest
-import inspect
-
-import numpy
-import nose
-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
-from .utils import KnownFailureException, KnownFailureTest
-
-
-# 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 KnownFailurePlugin(ErrorClassPlugin):
-    '''Plugin that installs a KNOWNFAIL error class for the
-    KnownFailureClass exception.  When KnownFailure is raised,
-    the exception will be logged in the knownfail attribute of the
-    result, 'K' or 'KNOWNFAIL' (verbose) will be output, and the
-    exception will not be counted as an error or failure.'''
-    enabled = True
-    knownfail = ErrorClass(KnownFailureException,
-                           label='KNOWNFAIL',
-                           isfailure=False)
-
-    def options(self, parser, env=os.environ):
-        env_opt = 'NOSE_WITHOUT_KNOWNFAIL'
-        parser.add_option('--no-knownfail', action='store_true',
-                          dest='noKnownFail', default=env.get(env_opt, False),
-                          help='Disable special handling of KnownFailure '
-                               'exceptions')
-
-    def configure(self, options, conf):
-        if not self.can_configure:
-            return
-        self.conf = conf
-        disable = getattr(options, 'noKnownFail', False)
-        if disable:
-            self.enabled = False
-
-KnownFailure = KnownFailurePlugin   # backwards compat
-
-
-class FPUModeCheckPlugin(Plugin):
-    """
-    Plugin that checks the FPU mode before and after each test,
-    raising failures if the test changed the mode.
-    """
-
-    def prepareTestCase(self, test):
-        from numpy.core._multiarray_tests import get_fpu_mode
-
-        def run(result):
-            old_mode = get_fpu_mode()
-            test.test(result)
-            new_mode = get_fpu_mode()
-
-            if old_mode != new_mode:
-                try:
-                    raise AssertionError(
-                        "FPU mode changed from {0:#x} to {1:#x} during the "
-                        "test".format(old_mode, new_mode))
-                except AssertionError:
-                    result.addFailure(test, sys.exc_info())
-
-        return run
-
-
-# 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/nose_tools/nosetester.py b/numpy/testing/nose_tools/nosetester.py
deleted file mode 100644
index c2cf58377..000000000
--- a/numpy/testing/nose_tools/nosetester.py
+++ /dev/null
@@ -1,560 +0,0 @@
-"""
-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
-
-    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 nose test runner. ``argv[0]`` is
-        ignored. All command line arguments accepted by ``nosetests``
-        will work. If it is the default value None, sys.argv is used.
-
-        .. versionadded:: 1.9.0
-
-    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'.
-    """
-    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 + [file_to_run]
-    else:
-        argv = argv + [file_to_run]
-
-    nose = import_nose()
-    from .noseclasses import KnownFailurePlugin
-    nose.run(argv=argv, addplugins=[KnownFailurePlugin()])
-
-
-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,
-                 check_fpu_mode=False):
-        # 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
-
-        # Whether to check for FPU mode changes
-        self.check_fpu_mode = check_fpu_mode
-
-    def _test_argv(self, label, verbose, extra_argv):
-        ''' Generate argv for nosetest command
-
-        Parameters
-        ----------
-        label : {'fast', 'full', '', attribute identifier}, optional
-            see ``test`` docstring
-        verbose : int, optional
-            Verbosity value for test outputs, in the range 1-10. Default is 1.
-        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 += ['--verbosity', str(verbose)]
-
-        # 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):
-        nose = import_nose()
-
-        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("nose version %d.%d.%d" % nose.__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,
-                                  FPUModeCheckPlugin)
-        plugins = [KnownFailurePlugin()]
-        plugins += [p() for p in nose.plugins.builtin.plugins]
-        if self.check_fpu_mode:
-            plugins += [FPUModeCheckPlugin()]
-            argv += ["--with-fpumodecheckplugin"]
-        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 1-10. 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
-            Verbosity value for benchmark outputs, in the range 1-10. Default is 1.
-        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)
-
-
-def _numpy_tester():
-    if hasattr(np, "__version__") and ".dev0" in np.__version__:
-        mode = "develop"
-    else:
-        mode = "release"
-    return NoseTester(raise_warnings=mode, depth=1,
-                      check_fpu_mode=True)
diff --git a/numpy/testing/nose_tools/parameterized.py b/numpy/testing/nose_tools/parameterized.py
deleted file mode 100644
index 53e67517d..000000000
--- a/numpy/testing/nose_tools/parameterized.py
+++ /dev/null
@@ -1,490 +0,0 @@
-"""
-tl;dr: all code code is licensed under simplified BSD, unless stated otherwise.
-
-Unless stated otherwise in the source files, all code is copyright 2010 David
-Wolever <david@wolever.net>. All rights reserved.
-
-Redistribution and use in source and binary forms, with or without
-modification, are permitted provided that the following conditions are met:
-
-   1. Redistributions of source code must retain the above copyright notice,
-   this list of conditions and the following disclaimer.
-
-   2. Redistributions in binary form must reproduce the above copyright notice,
-   this list of conditions and the following disclaimer in the documentation
-   and/or other materials provided with the distribution.
-
-THIS SOFTWARE IS PROVIDED BY <COPYRIGHT HOLDER> ``AS IS'' AND ANY EXPRESS OR
-IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF
-MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO
-EVENT SHALL <COPYRIGHT HOLDER> OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,
-INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
-BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,
-DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
-LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE
-OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
-ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-The views and conclusions contained in the software and documentation are those
-of the authors and should not be interpreted as representing official policies,
-either expressed or implied, of David Wolever.
-
-"""
-import re
-import sys
-import inspect
-import warnings
-from functools import wraps
-from types import MethodType as MethodType
-from collections import namedtuple
-
-try:
-    from collections import OrderedDict as MaybeOrderedDict
-except ImportError:
-    MaybeOrderedDict = dict
-
-from unittest import TestCase
-
-PY3 = sys.version_info[0] == 3
-PY2 = sys.version_info[0] == 2
-
-
-if PY3:
-    # Python 3 doesn't have an InstanceType, so just use a dummy type.
-    class InstanceType():
-        pass
-    lzip = lambda *a: list(zip(*a))
-    text_type = str
-    string_types = str,
-    bytes_type = bytes
-    def make_method(func, instance, type):
-        if instance is None:
-            return func
-        return MethodType(func, instance)
-else:
-    from types import InstanceType
-    lzip = zip
-    text_type = unicode
-    bytes_type = str
-    string_types = basestring,
-    def make_method(func, instance, type):
-        return MethodType(func, instance, type)
-
-_param = namedtuple("param", "args kwargs")
-
-class param(_param):
-    """ Represents a single parameter to a test case.
-
-        For example::
-
-            >>> p = param("foo", bar=16)
-            >>> p
-            param("foo", bar=16)
-            >>> p.args
-            ('foo', )
-            >>> p.kwargs
-            {'bar': 16}
-
-        Intended to be used as an argument to ``@parameterized``::
-
-            @parameterized([
-                param("foo", bar=16),
-            ])
-            def test_stuff(foo, bar=16):
-                pass
-        """
-
-    def __new__(cls, *args , **kwargs):
-        return _param.__new__(cls, args, kwargs)
-
-    @classmethod
-    def explicit(cls, args=None, kwargs=None):
-        """ Creates a ``param`` by explicitly specifying ``args`` and
-            ``kwargs``::
-
-                >>> param.explicit([1,2,3])
-                param(*(1, 2, 3))
-                >>> param.explicit(kwargs={"foo": 42})
-                param(*(), **{"foo": "42"})
-            """
-        args = args or ()
-        kwargs = kwargs or {}
-        return cls(*args, **kwargs)
-
-    @classmethod
-    def from_decorator(cls, args):
-        """ Returns an instance of ``param()`` for ``@parameterized`` argument
-            ``args``::
-
-                >>> param.from_decorator((42, ))
-                param(args=(42, ), kwargs={})
-                >>> param.from_decorator("foo")
-                param(args=("foo", ), kwargs={})
-            """
-        if isinstance(args, param):
-            return args
-        elif isinstance(args, string_types):
-            args = (args, )
-        try:
-            return cls(*args)
-        except TypeError as e:
-            if "after * must be" not in str(e):
-                raise
-            raise TypeError(
-                "Parameters must be tuples, but %r is not (hint: use '(%r, )')"
-                %(args, args),
-            )
-
-    def __repr__(self):
-        return "param(*%r, **%r)" %self
-
-
-class QuietOrderedDict(MaybeOrderedDict):
-    """ When OrderedDict is available, use it to make sure that the kwargs in
-        doc strings are consistently ordered. """
-    __str__ = dict.__str__
-    __repr__ = dict.__repr__
-
-
-def parameterized_argument_value_pairs(func, p):
-    """Return tuples of parameterized arguments and their values.
-
-        This is useful if you are writing your own doc_func
-        function and need to know the values for each parameter name::
-
-            >>> def func(a, foo=None, bar=42, **kwargs): pass
-            >>> p = param(1, foo=7, extra=99)
-            >>> parameterized_argument_value_pairs(func, p)
-            [("a", 1), ("foo", 7), ("bar", 42), ("**kwargs", {"extra": 99})]
-
-        If the function's first argument is named ``self`` then it will be
-        ignored::
-
-            >>> def func(self, a): pass
-            >>> p = param(1)
-            >>> parameterized_argument_value_pairs(func, p)
-            [("a", 1)]
-
-        Additionally, empty ``*args`` or ``**kwargs`` will be ignored::
-
-            >>> def func(foo, *args): pass
-            >>> p = param(1)
-            >>> parameterized_argument_value_pairs(func, p)
-            [("foo", 1)]
-            >>> p = param(1, 16)
-            >>> parameterized_argument_value_pairs(func, p)
-            [("foo", 1), ("*args", (16, ))]
-    """
-    argspec = inspect.getargspec(func)
-    arg_offset = 1 if argspec.args[:1] == ["self"] else 0
-
-    named_args = argspec.args[arg_offset:]
-
-    result = lzip(named_args, p.args)
-    named_args = argspec.args[len(result) + arg_offset:]
-    varargs = p.args[len(result):]
-
-    result.extend([
-        (name, p.kwargs.get(name, default))
-        for (name, default)
-        in zip(named_args, argspec.defaults or [])
-    ])
-
-    seen_arg_names = set([ n for (n, _) in result ])
-    keywords = QuietOrderedDict(sorted([
-        (name, p.kwargs[name])
-        for name in p.kwargs
-        if name not in seen_arg_names
-    ]))
-
-    if varargs:
-        result.append(("*%s" %(argspec.varargs, ), tuple(varargs)))
-
-    if keywords:
-        result.append(("**%s" %(argspec.keywords, ), keywords))
-
-    return result
-
-def short_repr(x, n=64):
-    """ A shortened repr of ``x`` which is guaranteed to be ``unicode``::
-
-            >>> short_repr("foo")
-            u"foo"
-            >>> short_repr("123456789", n=4)
-            u"12...89"
-    """
-
-    x_repr = repr(x)
-    if isinstance(x_repr, bytes_type):
-        try:
-            x_repr = text_type(x_repr, "utf-8")
-        except UnicodeDecodeError:
-            x_repr = text_type(x_repr, "latin1")
-    if len(x_repr) > n:
-        x_repr = x_repr[:n//2] + "..." + x_repr[len(x_repr) - n//2:]
-    return x_repr
-
-def default_doc_func(func, num, p):
-    if func.__doc__ is None:
-        return None
-
-    all_args_with_values = parameterized_argument_value_pairs(func, p)
-
-    # Assumes that the function passed is a bound method.
-    descs = ["%s=%s" %(n, short_repr(v)) for n, v in all_args_with_values]
-
-    # The documentation might be a multiline string, so split it
-    # and just work with the first string, ignoring the period
-    # at the end if there is one.
-    first, nl, rest = func.__doc__.lstrip().partition("\n")
-    suffix = ""
-    if first.endswith("."):
-        suffix = "."
-        first = first[:-1]
-    args = "%s[with %s]" %(len(first) and " " or "", ", ".join(descs))
-    return "".join([first.rstrip(), args, suffix, nl, rest])
-
-def default_name_func(func, num, p):
-    base_name = func.__name__
-    name_suffix = "_%s" %(num, )
-    if len(p.args) > 0 and isinstance(p.args[0], string_types):
-        name_suffix += "_" + parameterized.to_safe_name(p.args[0])
-    return base_name + name_suffix
-
-
-# force nose for numpy purposes.
-_test_runner_override = 'nose'
-_test_runner_guess = False
-_test_runners = set(["unittest", "unittest2", "nose", "nose2", "pytest"])
-_test_runner_aliases = {
-    "_pytest": "pytest",
-}
-
-def set_test_runner(name):
-    global _test_runner_override
-    if name not in _test_runners:
-        raise TypeError(
-            "Invalid test runner: %r (must be one of: %s)"
-            %(name, ", ".join(_test_runners)),
-        )
-    _test_runner_override = name
-
-def detect_runner():
-    """ Guess which test runner we're using by traversing the stack and looking
-        for the first matching module. This *should* be reasonably safe, as
-        it's done during test disocvery where the test runner should be the
-        stack frame immediately outside. """
-    if _test_runner_override is not None:
-        return _test_runner_override
-    global _test_runner_guess
-    if _test_runner_guess is False:
-        stack = inspect.stack()
-        for record in reversed(stack):
-            frame = record[0]
-            module = frame.f_globals.get("__name__").partition(".")[0]
-            if module in _test_runner_aliases:
-                module = _test_runner_aliases[module]
-            if module in _test_runners:
-                _test_runner_guess = module
-                break
-            if record[1].endswith("python2.6/unittest.py"):
-                _test_runner_guess = "unittest"
-                break
-        else:
-            _test_runner_guess = None
-    return _test_runner_guess
-
-class parameterized(object):
-    """ Parameterize a test case::
-
-            class TestInt(object):
-                @parameterized([
-                    ("A", 10),
-                    ("F", 15),
-                    param("10", 42, base=42)
-                ])
-                def test_int(self, input, expected, base=16):
-                    actual = int(input, base=base)
-                    assert_equal(actual, expected)
-
-            @parameterized([
-                (2, 3, 5)
-                (3, 5, 8),
-            ])
-            def test_add(a, b, expected):
-                assert_equal(a + b, expected)
-        """
-
-    def __init__(self, input, doc_func=None):
-        self.get_input = self.input_as_callable(input)
-        self.doc_func = doc_func or default_doc_func
-
-    def __call__(self, test_func):
-        self.assert_not_in_testcase_subclass()
-
-        @wraps(test_func)
-        def wrapper(test_self=None):
-            test_cls = test_self and type(test_self)
-            if test_self is not None:
-                if issubclass(test_cls, InstanceType):
-                    raise TypeError((
-                        "@parameterized can't be used with old-style classes, but "
-                        "%r has an old-style class. Consider using a new-style "
-                        "class, or '@parameterized.expand' "
-                        "(see http://stackoverflow.com/q/54867/71522 for more "
-                        "information on old-style classes)."
-                    ) %(test_self, ))
-
-            original_doc = wrapper.__doc__
-            for num, args in enumerate(wrapper.parameterized_input):
-                p = param.from_decorator(args)
-                unbound_func, nose_tuple = self.param_as_nose_tuple(test_self, test_func, num, p)
-                try:
-                    wrapper.__doc__ = nose_tuple[0].__doc__
-                    # Nose uses `getattr(instance, test_func.__name__)` to get
-                    # a method bound to the test instance (as opposed to a
-                    # method bound to the instance of the class created when
-                    # tests were being enumerated). Set a value here to make
-                    # sure nose can get the correct test method.
-                    if test_self is not None:
-                        setattr(test_cls, test_func.__name__, unbound_func)
-                    yield nose_tuple
-                finally:
-                    if test_self is not None:
-                        delattr(test_cls, test_func.__name__)
-                    wrapper.__doc__ = original_doc
-        wrapper.parameterized_input = self.get_input()
-        wrapper.parameterized_func = test_func
-        test_func.__name__ = "_parameterized_original_%s" %(test_func.__name__, )
-        return wrapper
-
-    def param_as_nose_tuple(self, test_self, func, num, p):
-        nose_func = wraps(func)(lambda *args: func(*args[:-1], **args[-1]))
-        nose_func.__doc__ = self.doc_func(func, num, p)
-        # Track the unbound function because we need to setattr the unbound
-        # function onto the class for nose to work (see comments above), and
-        # Python 3 doesn't let us pull the function out of a bound method.
-        unbound_func = nose_func
-        if test_self is not None:
-            # Under nose on Py2 we need to return an unbound method to make
-            # sure that the `self` in the method is properly shared with the
-            # `self` used in `setUp` and `tearDown`. But only there. Everyone
-            # else needs a bound method.
-            func_self = (
-                None if PY2 and detect_runner() == "nose" else
-                test_self
-            )
-            nose_func = make_method(nose_func, func_self, type(test_self))
-        return unbound_func, (nose_func, ) + p.args + (p.kwargs or {}, )
-
-    def assert_not_in_testcase_subclass(self):
-        parent_classes = self._terrible_magic_get_defining_classes()
-        if any(issubclass(cls, TestCase) for cls in parent_classes):
-            raise Exception("Warning: '@parameterized' tests won't work "
-                            "inside subclasses of 'TestCase' - use "
-                            "'@parameterized.expand' instead.")
-
-    def _terrible_magic_get_defining_classes(self):
-        """ Returns the set of parent classes of the class currently being defined.
-            Will likely only work if called from the ``parameterized`` decorator.
-            This function is entirely @brandon_rhodes's fault, as he suggested
-            the implementation: http://stackoverflow.com/a/8793684/71522
-            """
-        stack = inspect.stack()
-        if len(stack) <= 4:
-            return []
-        frame = stack[4]
-        code_context = frame[4] and frame[4][0].strip()
-        if not (code_context and code_context.startswith("class ")):
-            return []
-        _, _, parents = code_context.partition("(")
-        parents, _, _ = parents.partition(")")
-        return eval("[" + parents + "]", frame[0].f_globals, frame[0].f_locals)
-
-    @classmethod
-    def input_as_callable(cls, input):
-        if callable(input):
-            return lambda: cls.check_input_values(input())
-        input_values = cls.check_input_values(input)
-        return lambda: input_values
-
-    @classmethod
-    def check_input_values(cls, input_values):
-        # Explicitly convert non-list inputs to a list so that:
-        # 1. A helpful exception will be raised if they aren't iterable, and
-        # 2. Generators are unwrapped exactly once (otherwise `nosetests
-        #    --processes=n` has issues; see:
-        #    https://github.com/wolever/nose-parameterized/pull/31)
-        if not isinstance(input_values, list):
-            input_values = list(input_values)
-        return [ param.from_decorator(p) for p in input_values ]
-
-    @classmethod
-    def expand(cls, input, name_func=None, doc_func=None, **legacy):
-        """ A "brute force" method of parameterizing test cases. Creates new
-            test cases and injects them into the namespace that the wrapped
-            function is being defined in. Useful for parameterizing tests in
-            subclasses of 'UnitTest', where Nose test generators don't work.
-
-            >>> @parameterized.expand([("foo", 1, 2)])
-            ... def test_add1(name, input, expected):
-            ...     actual = add1(input)
-            ...     assert_equal(actual, expected)
-            ...
-            >>> locals()
-            ... 'test_add1_foo_0': <function ...> ...
-            >>>
-            """
-
-        if "testcase_func_name" in legacy:
-            warnings.warn("testcase_func_name= is deprecated; use name_func=",
-                          DeprecationWarning, stacklevel=2)
-            if not name_func:
-                name_func = legacy["testcase_func_name"]
-
-        if "testcase_func_doc" in legacy:
-            warnings.warn("testcase_func_doc= is deprecated; use doc_func=",
-                          DeprecationWarning, stacklevel=2)
-            if not doc_func:
-                doc_func = legacy["testcase_func_doc"]
-
-        doc_func = doc_func or default_doc_func
-        name_func = name_func or default_name_func
-
-        def parameterized_expand_wrapper(f, instance=None):
-            stack = inspect.stack()
-            frame = stack[1]
-            frame_locals = frame[0].f_locals
-
-            parameters = cls.input_as_callable(input)()
-            for num, p in enumerate(parameters):
-                name = name_func(f, num, p)
-                frame_locals[name] = cls.param_as_standalone_func(p, f, name)
-                frame_locals[name].__doc__ = doc_func(f, num, p)
-
-            f.__test__ = False
-        return parameterized_expand_wrapper
-
-    @classmethod
-    def param_as_standalone_func(cls, p, func, name):
-        @wraps(func)
-        def standalone_func(*a):
-            return func(*(a + p.args), **p.kwargs)
-        standalone_func.__name__ = name
-
-        # place_as is used by py.test to determine what source file should be
-        # used for this test.
-        standalone_func.place_as = func
-
-        # Remove __wrapped__ because py.test will try to look at __wrapped__
-        # to determine which parameters should be used with this test case,
-        # and obviously we don't need it to do any parameterization.
-        try:
-            del standalone_func.__wrapped__
-        except AttributeError:
-            pass
-        return standalone_func
-
-    @classmethod
-    def to_safe_name(cls, s):
-        return str(re.sub("[^a-zA-Z0-9_]+", "_", s))
diff --git a/numpy/testing/nose_tools/utils.py b/numpy/testing/nose_tools/utils.py
deleted file mode 100644
index 507ecb1e2..000000000
--- a/numpy/testing/nose_tools/utils.py
+++ /dev/null
@@ -1,2274 +0,0 @@
-"""
-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 unittest.case import SkipTest
-
-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.'''
-    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():
-    """ Import nose only when needed.
-    """
-    nose_is_good = True
-    minimum_nose_version = (1, 0, 0)
-    try:
-        import nose
-    except ImportError:
-        nose_is_good = False
-    else:
-        if nose.__versioninfo__ < minimum_nose_version:
-            nose_is_good = False
-
-    if not nose_is_good:
-        msg = ('Need nose >= %d.%d.%d for tests - see '
-               'http://nose.readthedocs.io' %
-               minimum_nose_version)
-        raise ImportError(msg)
-
-    return nose
-
-
-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:
-        isdesnan = gisnan(desired)
-        isactnan = gisnan(actual)
-        if isdesnan and isactnan:
-            return  # both nan, so equal
-
-        # handle signed zero specially for floats
-        if desired == 0 and actual == 0:
-            if not signbit(desired) == signbit(actual):
-                raise AssertionError(msg)
-
-    except (TypeError, ValueError, NotImplementedError):
-        pass
-
-    try:
-        isdesnat = isnat(desired)
-        isactnat = isnat(actual)
-        dtypes_match = array(desired).dtype.type == array(actual).dtype.type
-        if isdesnat and isactnat:
-            # If both are NaT (and have the same dtype -- datetime or
-            # timedelta) they are considered equal.
-            if dtypes_match:
-                return
-            else:
-                raise AssertionError(msg)
-
-    except (TypeError, ValueError, NotImplementedError):
-        pass
-
-    try:
-        # Explicitly use __eq__ for comparison, gh-2552
-        if not (desired == actual):
-            raise AssertionError(msg)
-
-    except (DeprecationWarning, FutureWarning) as e:
-        # this handles the case when the two types are not even comparable
-        if 'elementwise == comparison' in e.args[0]:
-            raise AssertionError(msg)
-        else:
-            raise
-
-
-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)
-            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(*args):
-    """Decorator to check for raised exceptions.
-
-    The decorated test function must raise one of the passed exceptions to
-    pass.  If you want to test many assertions about exceptions in a single
-    test, you may want to use `assert_raises` instead.
-
-    .. warning::
-       This decorator is nose specific, do not use it if you are using a
-       different test framework.
-
-    Parameters
-    ----------
-    args : exceptions
-        The test passes if any of the passed exceptions is raised.
-
-    Raises
-    ------
-    AssertionError
-
-    Examples
-    --------
-
-    Usage::
-
-        @raises(TypeError, ValueError)
-        def test_raises_type_error():
-            raise TypeError("This test passes")
-
-        @raises(Exception)
-        def test_that_fails_by_passing():
-            pass
-
-    """
-    nose = import_nose()
-    return nose.tools.raises(*args)
-
-#
-# assert_raises and assert_raises_regex are taken from unittest.
-#
-import unittest
-
-
-class _Dummy(unittest.TestCase):
-    def nop(self):
-        pass
-
-_d = _Dummy('nop')
-
-def assert_raises(*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)
-
-    """
-    __tracebackhide__ = True  # Hide traceback for py.test
-    return _d.assertRaises(*args,**kwargs)
-
-
-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
-
-    """
-    __tracebackhide__ = True  # Hide traceback for py.test
-
-    if sys.version_info.major >= 3:
-        funcname = _d.assertRaisesRegex
-    else:
-        # Only present in Python 2.7, missing from unittest in 2.6
-        funcname = _d.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.float16:
-        return _integer_repr(x, np.int16, np.int16(-2**15))
-    elif 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')
-
-
-class IgnoreException(Exception):
-    "Ignoring this exception due to disabled feature"
-    pass
-
-
-@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