MAINT: Rearrange files in numpy/testing module.

The aim here is to separate out the nose dependent files prior to adding
pytest support. This could be done by adding new files to the general
numpy/testing directory, but I felt that it was to have the relevant
files separated out as it makes it easier to completely remove nose
dependencies when needed.

Many places were accessing submodules in numpy/testing directly, and in
some cases incorrectly. That presented a backwards compatibility
problem. The solution adapted here is to have "dummy" files whose
contents will depend on whether of not pytest is active. That way the
module looks the same as before from the outside.

In the case of numpy itself, direct accesses have been fixed. Having
proper `__all__` lists in the submodules helped in that.

5 files changed, 3385 insertions, 0 deletions

diff --git a/numpy/testing/nose_tools/__init__.py b/numpy/testing/nose_tools/__init__.py
new file mode 100644
index 000000000..e69de29bb
--- /dev/null
+++ b/numpy/testing/nose_tools/__init__.py
diff --git a/numpy/testing/nose_tools/decorators.py b/numpy/testing/nose_tools/decorators.py
new file mode 100644
index 000000000..7efd7f97e
--- /dev/null
+++ b/numpy/testing/nose_tools/decorators.py
@@ -0,0 +1,265 @@
+"""
+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
+
+import collections
+
+from .utils import SkipTest, assert_warns
+
+
+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.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.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.Callable):
+            cond = conditional()
+        else:
+            cond = conditional
+        if cond:
+            return nose.tools.make_decorator(f)(_deprecated_imp)
+        else:
+            return f
+    return deprecate_decorator
diff --git a/numpy/testing/nose_tools/noseclasses.py b/numpy/testing/nose_tools/noseclasses.py
new file mode 100644
index 000000000..2f5d05004
--- /dev/null
+++ b/numpy/testing/nose_tools/noseclasses.py
@@ -0,0 +1,340 @@
+# These classes implement a doctest runner plugin for nose, a "known failure"
+# error class, and a customized TestProgram for NumPy.
+
+# Because this module imports nose directly, it should not
+# be used except by nosetester.py to avoid a general NumPy
+# dependency on nose.
+from __future__ import division, absolute_import, print_function
+
+import os
+import doctest
+import inspect
+
+import numpy
+import 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 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
new file mode 100644
index 000000000..407653fc3
--- /dev/null
+++ b/numpy/testing/nose_tools/nosetester.py
@@ -0,0 +1,551 @@
+"""
+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):
+        # Back-compat: 'None' used to mean either "release" or "develop"
+        # depending on whether this was a release or develop version of
+        # numpy. Those semantics were fine for testing numpy, but not so
+        # helpful for downstream projects like scipy that use
+        # numpy.testing. (They want to set this based on whether *they* are a
+        # release or develop version, not whether numpy is.) So we continue to
+        # accept 'None' for back-compat, but it's now just an alias for the
+        # default "release".
+        if raise_warnings is None:
+            raise_warnings = "release"
+
+        package_name = None
+        if package is None:
+            f = sys._getframe(1 + depth)
+            package_path = f.f_locals.get('__file__', None)
+            if package_path is None:
+                raise AssertionError
+            package_path = os.path.dirname(package_path)
+            package_name = f.f_locals.get('__name__', None)
+        elif isinstance(package, type(os)):
+            package_path = os.path.dirname(package.__file__)
+            package_name = getattr(package, '__name__', None)
+        else:
+            package_path = str(package)
+
+        self.package_path = package_path
+
+        # Find the package name under test; this name is used to limit coverage
+        # reporting (if enabled).
+        if package_name is None:
+            package_name = get_package_name(package_path)
+        self.package_name = package_name
+
+        # Set to "release" in constructor in maintenance branches.
+        self.raise_warnings = raise_warnings
+
+    def _test_argv(self, label, verbose, extra_argv):
+        ''' Generate argv for 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
+        plugins = [KnownFailurePlugin()]
+        plugins += [p() for p in nose.plugins.builtin.plugins]
+        try:
+            # External plugins (like nose-timer)
+            entrypoint_manager = EntryPointPluginManager()
+            entrypoint_manager.loadPlugins()
+            plugins += [p for p in entrypoint_manager.plugins]
+        except ImportError:
+            # Relies on pkg_resources, not a hard dependency
+            pass
+
+        # add doctesting if required
+        doctest_argv = '--with-doctest' in argv
+        if doctests == False and doctest_argv:
+            doctests = True
+        plug = self._get_custom_doctester()
+        if plug is None:
+            # use standard doctesting
+            if doctests and not doctest_argv:
+                argv += ['--with-doctest']
+        else:  # custom doctesting
+            if doctest_argv:  # in fact the unplugger would take care of this
+                argv.remove('--with-doctest')
+            plugins += [Unplugger('doctest'), plug]
+            if doctests:
+                argv += ['--with-' + plug.name]
+        return argv, plugins
+
+    def test(self, label='fast', verbose=1, extra_argv=None,
+             doctests=False, coverage=False, raise_warnings=None,
+             timer=False):
+        """
+        Run tests for module using nose.
+
+        Parameters
+        ----------
+        label : {'fast', 'full', '', attribute identifier}, optional
+            Identifies the tests to run. This can be a string to pass to
+            the nosetests executable with the '-A' option, or one of several
+            special values.  Special values are:
+            * 'fast' - the default - which corresponds to the ``nosetests -A``
+              option of 'not slow'.
+            * 'full' - fast (as above) and slow tests as in the
+              'no -A' option to nosetests - this is the same as ''.
+            * None or '' - run all tests.
+            attribute_identifier - string passed directly to nosetests as '-A'.
+        verbose : int, optional
+            Verbosity value for test outputs, in the range 1-10. 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)
diff --git a/numpy/testing/nose_tools/utils.py b/numpy/testing/nose_tools/utils.py
new file mode 100644
index 000000000..302cf32ff
--- /dev/null
+++ b/numpy/testing/nose_tools/utils.py
@@ -0,0 +1,2229 @@
+"""
+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:
+        # If one of desired/actual is not finite, handle it specially here:
+        # check that both are nan if any is a nan, and test for equality
+        # otherwise
+        if not (gisfinite(desired) and gisfinite(actual)):
+            isdesnan = gisnan(desired)
+            isactnan = gisnan(actual)
+            if isdesnan or isactnan:
+                if not (isdesnan and isactnan):
+                    raise AssertionError(msg)
+            else:
+                if not desired == actual:
+                    raise AssertionError(msg)
+            return
+        elif desired == 0 and actual == 0:
+            if not signbit(desired) == signbit(actual):
+                raise AssertionError(msg)
+    # If TypeError or ValueError raised while using isnan and co, just handle
+    # as before
+    except (TypeError, ValueError, NotImplementedError):
+        pass
+
+    try:
+        # If both are NaT (and have the same dtype -- datetime or timedelta)
+        # they are considered equal.
+        if (isnat(desired) == isnat(actual) and
+                array(desired).dtype.type == array(actual).dtype.type):
+            return
+        else:
+            raise AssertionError(msg)
+
+    # If TypeError or ValueError raised while using isnan and co, just handle
+    # as before
+    except (TypeError, ValueError, NotImplementedError):
+        pass
+
+    # Explicitly use __eq__ for comparison, ticket #2552
+    if not (desired == actual):
+        raise AssertionError(msg)
+
+
+def print_assert_equal(test_string, actual, desired):
+    """
+    Test if two objects are equal, and print an error message if test fails.
+
+    The test is performed with ``actual == desired``.
+
+    Parameters
+    ----------
+    test_string : str
+        The message supplied to AssertionError.
+    actual : object
+        The object to test for equality against `desired`.
+    desired : object
+        The expected result.
+
+    Examples
+    --------
+    >>> np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 1])
+    >>> np.testing.print_assert_equal('Test XYZ of func xyz', [0, 1], [0, 2])
+    Traceback (most recent call last):
+    ...
+    AssertionError: Test XYZ of func xyz failed
+    ACTUAL:
+    [0, 1]
+    DESIRED:
+    [0, 2]
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import pprint
+
+    if not (actual == desired):
+        msg = StringIO()
+        msg.write(test_string)
+        msg.write(' failed\nACTUAL: \n')
+        pprint.pprint(actual, msg)
+        msg.write('DESIRED: \n')
+        pprint.pprint(desired, msg)
+        raise AssertionError(msg.getvalue())
+
+
+def assert_almost_equal(actual,desired,decimal=7,err_msg='',verbose=True):
+    """
+    Raises an AssertionError if two items are not equal up to desired
+    precision.
+
+    .. note:: It is recommended to use one of `assert_allclose`,
+              `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
+              instead of this function for more consistent floating point
+              comparisons.
+
+    The test verifies that the elements of ``actual`` and ``desired`` satisfy.
+
+        ``abs(desired-actual) < 1.5 * 10**(-decimal)``
+
+    That is a looser test than originally documented, but agrees with what the
+    actual implementation in `assert_array_almost_equal` did up to rounding
+    vagaries. An exception is raised at conflicting values. For ndarrays this
+    delegates to assert_array_almost_equal
+
+    Parameters
+    ----------
+    actual : array_like
+        The object to check.
+    desired : array_like
+        The expected object.
+    decimal : int, optional
+        Desired precision, default is 7.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+      If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    >>> import numpy.testing as npt
+    >>> npt.assert_almost_equal(2.3333333333333, 2.33333334)
+    >>> npt.assert_almost_equal(2.3333333333333, 2.33333334, decimal=10)
+    ...
+    <type 'exceptions.AssertionError'>:
+    Items are not equal:
+     ACTUAL: 2.3333333333333002
+     DESIRED: 2.3333333399999998
+
+    >>> npt.assert_almost_equal(np.array([1.0,2.3333333333333]),
+    ...                         np.array([1.0,2.33333334]), decimal=9)
+    ...
+    <type 'exceptions.AssertionError'>:
+    Arrays are not almost equal
+    <BLANKLINE>
+    (mismatch 50.0%)
+     x: array([ 1.        ,  2.33333333])
+     y: array([ 1.        ,  2.33333334])
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    from numpy.core import ndarray
+    from numpy.lib import iscomplexobj, real, imag
+
+    # Handle complex numbers: separate into real/imag to handle
+    # nan/inf/negative zero correctly
+    # XXX: catch ValueError for subclasses of ndarray where iscomplex fail
+    try:
+        usecomplex = iscomplexobj(actual) or iscomplexobj(desired)
+    except ValueError:
+        usecomplex = False
+
+    def _build_err_msg():
+        header = ('Arrays are not almost equal to %d decimals' % decimal)
+        return build_err_msg([actual, desired], err_msg, verbose=verbose,
+                             header=header)
+
+    if usecomplex:
+        if iscomplexobj(actual):
+            actualr = real(actual)
+            actuali = imag(actual)
+        else:
+            actualr = actual
+            actuali = 0
+        if iscomplexobj(desired):
+            desiredr = real(desired)
+            desiredi = imag(desired)
+        else:
+            desiredr = desired
+            desiredi = 0
+        try:
+            assert_almost_equal(actualr, desiredr, decimal=decimal)
+            assert_almost_equal(actuali, desiredi, decimal=decimal)
+        except AssertionError:
+            raise AssertionError(_build_err_msg())
+
+    if isinstance(actual, (ndarray, tuple, list)) \
+            or isinstance(desired, (ndarray, tuple, list)):
+        return assert_array_almost_equal(actual, desired, decimal, err_msg)
+    try:
+        # If one of desired/actual is not finite, handle it specially here:
+        # check that both are nan if any is a nan, and test for equality
+        # otherwise
+        if not (gisfinite(desired) and gisfinite(actual)):
+            if gisnan(desired) or gisnan(actual):
+                if not (gisnan(desired) and gisnan(actual)):
+                    raise AssertionError(_build_err_msg())
+            else:
+                if not desired == actual:
+                    raise AssertionError(_build_err_msg())
+            return
+    except (NotImplementedError, TypeError):
+        pass
+    if abs(desired - actual) >= 1.5 * 10.0**(-decimal):
+        raise AssertionError(_build_err_msg())
+
+
+def assert_approx_equal(actual,desired,significant=7,err_msg='',verbose=True):
+    """
+    Raises an AssertionError if two items are not equal up to significant
+    digits.
+
+    .. note:: It is recommended to use one of `assert_allclose`,
+              `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
+              instead of this function for more consistent floating point
+              comparisons.
+
+    Given two numbers, check that they are approximately equal.
+    Approximately equal is defined as the number of significant digits
+    that agree.
+
+    Parameters
+    ----------
+    actual : scalar
+        The object to check.
+    desired : scalar
+        The expected object.
+    significant : int, optional
+        Desired precision, default is 7.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+      If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    >>> np.testing.assert_approx_equal(0.12345677777777e-20, 0.1234567e-20)
+    >>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345671e-20,
+                                       significant=8)
+    >>> np.testing.assert_approx_equal(0.12345670e-20, 0.12345672e-20,
+                                       significant=8)
+    ...
+    <type 'exceptions.AssertionError'>:
+    Items are not equal to 8 significant digits:
+     ACTUAL: 1.234567e-021
+     DESIRED: 1.2345672000000001e-021
+
+    the evaluated condition that raises the exception is
+
+    >>> abs(0.12345670e-20/1e-21 - 0.12345672e-20/1e-21) >= 10**-(8-1)
+    True
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+
+    (actual, desired) = map(float, (actual, desired))
+    if desired == actual:
+        return
+    # Normalized the numbers to be in range (-10.0,10.0)
+    # scale = float(pow(10,math.floor(math.log10(0.5*(abs(desired)+abs(actual))))))
+    with np.errstate(invalid='ignore'):
+        scale = 0.5*(np.abs(desired) + np.abs(actual))
+        scale = np.power(10, np.floor(np.log10(scale)))
+    try:
+        sc_desired = desired/scale
+    except ZeroDivisionError:
+        sc_desired = 0.0
+    try:
+        sc_actual = actual/scale
+    except ZeroDivisionError:
+        sc_actual = 0.0
+    msg = build_err_msg([actual, desired], err_msg,
+                header='Items are not equal to %d significant digits:' %
+                                 significant,
+                verbose=verbose)
+    try:
+        # If one of desired/actual is not finite, handle it specially here:
+        # check that both are nan if any is a nan, and test for equality
+        # otherwise
+        if not (gisfinite(desired) and gisfinite(actual)):
+            if gisnan(desired) or gisnan(actual):
+                if not (gisnan(desired) and gisnan(actual)):
+                    raise AssertionError(msg)
+            else:
+                if not desired == actual:
+                    raise AssertionError(msg)
+            return
+    except (TypeError, NotImplementedError):
+        pass
+    if np.abs(sc_desired - sc_actual) >= np.power(10., -(significant-1)):
+        raise AssertionError(msg)
+
+
+def assert_array_compare(comparison, x, y, err_msg='', verbose=True,
+                         header='', precision=6, equal_nan=True,
+                         equal_inf=True):
+    __tracebackhide__ = True  # Hide traceback for py.test
+    from numpy.core import array, isnan, isinf, any, inf
+    x = array(x, copy=False, subok=True)
+    y = array(y, copy=False, subok=True)
+
+    def isnumber(x):
+        return x.dtype.char in '?bhilqpBHILQPefdgFDG'
+
+    def istime(x):
+        return x.dtype.char in "Mm"
+
+    def chk_same_position(x_id, y_id, hasval='nan'):
+        """Handling nan/inf: check that x and y have the nan/inf at the same
+        locations."""
+        try:
+            assert_array_equal(x_id, y_id)
+        except AssertionError:
+            msg = build_err_msg([x, y],
+                                err_msg + '\nx and y %s location mismatch:'
+                                % (hasval), verbose=verbose, header=header,
+                                names=('x', 'y'), precision=precision)
+            raise AssertionError(msg)
+
+    try:
+        cond = (x.shape == () or y.shape == ()) or x.shape == y.shape
+        if not cond:
+            msg = build_err_msg([x, y],
+                                err_msg
+                                + '\n(shapes %s, %s mismatch)' % (x.shape,
+                                                                  y.shape),
+                                verbose=verbose, header=header,
+                                names=('x', 'y'), precision=precision)
+            raise AssertionError(msg)
+
+        if isnumber(x) and isnumber(y):
+            has_nan = has_inf = False
+            if equal_nan:
+                x_isnan, y_isnan = isnan(x), isnan(y)
+                # Validate that NaNs are in the same place
+                has_nan = any(x_isnan) or any(y_isnan)
+                if has_nan:
+                    chk_same_position(x_isnan, y_isnan, hasval='nan')
+
+            if equal_inf:
+                x_isinf, y_isinf = isinf(x), isinf(y)
+                # Validate that infinite values are in the same place
+                has_inf = any(x_isinf) or any(y_isinf)
+                if has_inf:
+                    # Check +inf and -inf separately, since they are different
+                    chk_same_position(x == +inf, y == +inf, hasval='+inf')
+                    chk_same_position(x == -inf, y == -inf, hasval='-inf')
+
+            if has_nan and has_inf:
+                x = x[~(x_isnan | x_isinf)]
+                y = y[~(y_isnan | y_isinf)]
+            elif has_nan:
+                x = x[~x_isnan]
+                y = y[~y_isnan]
+            elif has_inf:
+                x = x[~x_isinf]
+                y = y[~y_isinf]
+
+            # Only do the comparison if actual values are left
+            if x.size == 0:
+                return
+
+        elif istime(x) and istime(y):
+            # If one is datetime64 and the other timedelta64 there is no point
+            if equal_nan and x.dtype.type == y.dtype.type:
+                x_isnat, y_isnat = isnat(x), isnat(y)
+
+                if any(x_isnat) or any(y_isnat):
+                    chk_same_position(x_isnat, y_isnat, hasval="NaT")
+
+                if any(x_isnat) or any(y_isnat):
+                    x = x[~x_isnat]
+                    y = y[~y_isnat]
+
+        val = comparison(x, y)
+
+        if isinstance(val, bool):
+            cond = val
+            reduced = [0]
+        else:
+            reduced = val.ravel()
+            cond = reduced.all()
+            reduced = reduced.tolist()
+        if not cond:
+            match = 100-100.0*reduced.count(1)/len(reduced)
+            msg = build_err_msg([x, y],
+                                err_msg
+                                + '\n(mismatch %s%%)' % (match,),
+                                verbose=verbose, header=header,
+                                names=('x', 'y'), precision=precision)
+            if not cond:
+                raise AssertionError(msg)
+    except ValueError:
+        import traceback
+        efmt = traceback.format_exc()
+        header = 'error during assertion:\n\n%s\n\n%s' % (efmt, header)
+
+        msg = build_err_msg([x, y], err_msg, verbose=verbose, header=header,
+                            names=('x', 'y'), precision=precision)
+        raise ValueError(msg)
+
+
+def assert_array_equal(x, y, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two array_like objects are not equal.
+
+    Given two array_like objects, check that the shape is equal and all
+    elements of these objects are equal. An exception is raised at
+    shape mismatch or conflicting values. In contrast to the standard usage
+    in numpy, NaNs are compared like numbers, no assertion is raised if
+    both objects have NaNs in the same positions.
+
+    The usual caution for verifying equality with floating point numbers is
+    advised.
+
+    Parameters
+    ----------
+    x : array_like
+        The actual object to check.
+    y : array_like
+        The desired, expected object.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired objects are not equal.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    The first assert does not raise an exception:
+
+    >>> np.testing.assert_array_equal([1.0,2.33333,np.nan],
+    ...                               [np.exp(0),2.33333, np.nan])
+
+    Assert fails with numerical inprecision with floats:
+
+    >>> np.testing.assert_array_equal([1.0,np.pi,np.nan],
+    ...                               [1, np.sqrt(np.pi)**2, np.nan])
+    ...
+    <type 'exceptions.ValueError'>:
+    AssertionError:
+    Arrays are not equal
+    <BLANKLINE>
+    (mismatch 50.0%)
+     x: array([ 1.        ,  3.14159265,         NaN])
+     y: array([ 1.        ,  3.14159265,         NaN])
+
+    Use `assert_allclose` or one of the nulp (number of floating point values)
+    functions for these cases instead:
+
+    >>> np.testing.assert_allclose([1.0,np.pi,np.nan],
+    ...                            [1, np.sqrt(np.pi)**2, np.nan],
+    ...                            rtol=1e-10, atol=0)
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    assert_array_compare(operator.__eq__, x, y, err_msg=err_msg,
+                         verbose=verbose, header='Arrays are not equal')
+
+
+def assert_array_almost_equal(x, y, decimal=6, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two objects are not equal up to desired
+    precision.
+
+    .. note:: It is recommended to use one of `assert_allclose`,
+              `assert_array_almost_equal_nulp` or `assert_array_max_ulp`
+              instead of this function for more consistent floating point
+              comparisons.
+
+    The test verifies identical shapes and that the elements of ``actual`` and
+    ``desired`` satisfy.
+
+        ``abs(desired-actual) < 1.5 * 10**(-decimal)``
+
+    That is a looser test than originally documented, but agrees with what the
+    actual implementation did up to rounding vagaries. An exception is raised
+    at shape mismatch or conflicting values. In contrast to the standard usage
+    in numpy, NaNs are compared like numbers, no assertion is raised if both
+    objects have NaNs in the same positions.
+
+    Parameters
+    ----------
+    x : array_like
+        The actual object to check.
+    y : array_like
+        The desired, expected object.
+    decimal : int, optional
+        Desired precision, default is 6.
+    err_msg : str, optional
+      The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_allclose: Compare two array_like objects for equality with desired
+                     relative and/or absolute precision.
+    assert_array_almost_equal_nulp, assert_array_max_ulp, assert_equal
+
+    Examples
+    --------
+    the first assert does not raise an exception
+
+    >>> np.testing.assert_array_almost_equal([1.0,2.333,np.nan],
+                                             [1.0,2.333,np.nan])
+
+    >>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
+    ...                                      [1.0,2.33339,np.nan], decimal=5)
+    ...
+    <type 'exceptions.AssertionError'>:
+    AssertionError:
+    Arrays are not almost equal
+    <BLANKLINE>
+    (mismatch 50.0%)
+     x: array([ 1.     ,  2.33333,      NaN])
+     y: array([ 1.     ,  2.33339,      NaN])
+
+    >>> np.testing.assert_array_almost_equal([1.0,2.33333,np.nan],
+    ...                                      [1.0,2.33333, 5], decimal=5)
+    <type 'exceptions.ValueError'>:
+    ValueError:
+    Arrays are not almost equal
+     x: array([ 1.     ,  2.33333,      NaN])
+     y: array([ 1.     ,  2.33333,  5.     ])
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    from numpy.core import around, number, float_, result_type, array
+    from numpy.core.numerictypes import issubdtype
+    from numpy.core.fromnumeric import any as npany
+
+    def compare(x, y):
+        try:
+            if npany(gisinf(x)) or npany( gisinf(y)):
+                xinfid = gisinf(x)
+                yinfid = gisinf(y)
+                if not (xinfid == yinfid).all():
+                    return False
+                # if one item, x and y is +- inf
+                if x.size == y.size == 1:
+                    return x == y
+                x = x[~xinfid]
+                y = y[~yinfid]
+        except (TypeError, NotImplementedError):
+            pass
+
+        # make sure y is an inexact type to avoid abs(MIN_INT); will cause
+        # casting of x later.
+        dtype = result_type(y, 1.)
+        y = array(y, dtype=dtype, copy=False, subok=True)
+        z = abs(x - y)
+
+        if not issubdtype(z.dtype, number):
+            z = z.astype(float_)  # handle object arrays
+
+        return z < 1.5 * 10.0**(-decimal)
+
+    assert_array_compare(compare, x, y, err_msg=err_msg, verbose=verbose,
+             header=('Arrays are not almost equal to %d decimals' % decimal),
+             precision=decimal)
+
+
+def assert_array_less(x, y, err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two array_like objects are not ordered by less
+    than.
+
+    Given two array_like objects, check that the shape is equal and all
+    elements of the first object are strictly smaller than those of the
+    second object. An exception is raised at shape mismatch or incorrectly
+    ordered values. Shape mismatch does not raise if an object has zero
+    dimension. In contrast to the standard usage in numpy, NaNs are
+    compared, no assertion is raised if both objects have NaNs in the same
+    positions.
+
+
+
+    Parameters
+    ----------
+    x : array_like
+      The smaller object to check.
+    y : array_like
+      The larger object to compare.
+    err_msg : string
+      The error message to be printed in case of failure.
+    verbose : bool
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+      If actual and desired objects are not equal.
+
+    See Also
+    --------
+    assert_array_equal: tests objects for equality
+    assert_array_almost_equal: test objects for equality up to precision
+
+
+
+    Examples
+    --------
+    >>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1.1, 2.0, np.nan])
+    >>> np.testing.assert_array_less([1.0, 1.0, np.nan], [1, 2.0, np.nan])
+    ...
+    <type 'exceptions.ValueError'>:
+    Arrays are not less-ordered
+    (mismatch 50.0%)
+     x: array([  1.,   1.,  NaN])
+     y: array([  1.,   2.,  NaN])
+
+    >>> np.testing.assert_array_less([1.0, 4.0], 3)
+    ...
+    <type 'exceptions.ValueError'>:
+    Arrays are not less-ordered
+    (mismatch 50.0%)
+     x: array([ 1.,  4.])
+     y: array(3)
+
+    >>> np.testing.assert_array_less([1.0, 2.0, 3.0], [4])
+    ...
+    <type 'exceptions.ValueError'>:
+    Arrays are not less-ordered
+    (shapes (3,), (1,) mismatch)
+     x: array([ 1.,  2.,  3.])
+     y: array([4])
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    assert_array_compare(operator.__lt__, x, y, err_msg=err_msg,
+                         verbose=verbose,
+                         header='Arrays are not less-ordered',
+                         equal_inf=False)
+
+
+def runstring(astr, dict):
+    exec(astr, dict)
+
+
+def assert_string_equal(actual, desired):
+    """
+    Test if two strings are equal.
+
+    If the given strings are equal, `assert_string_equal` does nothing.
+    If they are not equal, an AssertionError is raised, and the diff
+    between the strings is shown.
+
+    Parameters
+    ----------
+    actual : str
+        The string to test for equality against the expected string.
+    desired : str
+        The expected string.
+
+    Examples
+    --------
+    >>> np.testing.assert_string_equal('abc', 'abc')
+    >>> np.testing.assert_string_equal('abc', 'abcd')
+    Traceback (most recent call last):
+      File "<stdin>", line 1, in <module>
+    ...
+    AssertionError: Differences in strings:
+    - abc+ abcd?    +
+
+    """
+    # delay import of difflib to reduce startup time
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import difflib
+
+    if not isinstance(actual, str):
+        raise AssertionError(repr(type(actual)))
+    if not isinstance(desired, str):
+        raise AssertionError(repr(type(desired)))
+    if re.match(r'\A'+desired+r'\Z', actual, re.M):
+        return
+
+    diff = list(difflib.Differ().compare(actual.splitlines(1), desired.splitlines(1)))
+    diff_list = []
+    while diff:
+        d1 = diff.pop(0)
+        if d1.startswith('  '):
+            continue
+        if d1.startswith('- '):
+            l = [d1]
+            d2 = diff.pop(0)
+            if d2.startswith('? '):
+                l.append(d2)
+                d2 = diff.pop(0)
+            if not d2.startswith('+ '):
+                raise AssertionError(repr(d2))
+            l.append(d2)
+            if diff:
+                d3 = diff.pop(0)
+                if d3.startswith('? '):
+                    l.append(d3)
+                else:
+                    diff.insert(0, d3)
+            if re.match(r'\A'+d2[2:]+r'\Z', d1[2:]):
+                continue
+            diff_list.extend(l)
+            continue
+        raise AssertionError(repr(d1))
+    if not diff_list:
+        return
+    msg = 'Differences in strings:\n%s' % (''.join(diff_list)).rstrip()
+    if actual != desired:
+        raise AssertionError(msg)
+
+
+def rundocs(filename=None, raise_on_error=True):
+    """
+    Run doctests found in the given file.
+
+    By default `rundocs` raises an AssertionError on failure.
+
+    Parameters
+    ----------
+    filename : str
+        The path to the file for which the doctests are run.
+    raise_on_error : bool
+        Whether to raise an AssertionError when a doctest fails. Default is
+        True.
+
+    Notes
+    -----
+    The doctests can be run by the user/developer by adding the ``doctests``
+    argument to the ``test()`` call. For example, to run all tests (including
+    doctests) for `numpy.lib`:
+
+    >>> np.lib.test(doctests=True) #doctest: +SKIP
+    """
+    from numpy.compat import npy_load_module
+    import doctest
+    if filename is None:
+        f = sys._getframe(1)
+        filename = f.f_globals['__file__']
+    name = os.path.splitext(os.path.basename(filename))[0]
+    m = npy_load_module(name, filename)
+
+    tests = doctest.DocTestFinder().find(m)
+    runner = doctest.DocTestRunner(verbose=False)
+
+    msg = []
+    if raise_on_error:
+        out = lambda s: msg.append(s)
+    else:
+        out = None
+
+    for test in tests:
+        runner.run(test, out=out)
+
+    if runner.failures > 0 and raise_on_error:
+        raise AssertionError("Some doctests failed:\n%s" % "\n".join(msg))
+
+
+def raises(*args,**kwargs):
+    nose = import_nose()
+    return nose.tools.raises(*args,**kwargs)
+
+
+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
+    nose = import_nose()
+    return nose.tools.assert_raises(*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
+    nose = import_nose()
+
+    if sys.version_info.major >= 3:
+        funcname = nose.tools.assert_raises_regex
+    else:
+        # Only present in Python 2.7, missing from unittest in 2.6
+        funcname = nose.tools.assert_raises_regexp
+
+    return funcname(exception_class, expected_regexp, *args, **kwargs)
+
+
+def decorate_methods(cls, decorator, testmatch=None):
+    """
+    Apply a decorator to all methods in a class matching a regular expression.
+
+    The given decorator is applied to all public methods of `cls` that are
+    matched by the regular expression `testmatch`
+    (``testmatch.search(methodname)``). Methods that are private, i.e. start
+    with an underscore, are ignored.
+
+    Parameters
+    ----------
+    cls : class
+        Class whose methods to decorate.
+    decorator : function
+        Decorator to apply to methods
+    testmatch : compiled regexp or str, optional
+        The regular expression. Default value is None, in which case the
+        nose default (``re.compile(r'(?:^|[\\b_\\.%s-])[Tt]est' % os.sep)``)
+        is used.
+        If `testmatch` is a string, it is compiled to a regular expression
+        first.
+
+    """
+    if testmatch is None:
+        testmatch = re.compile(r'(?:^|[\\b_\\.%s-])[Tt]est' % os.sep)
+    else:
+        testmatch = re.compile(testmatch)
+    cls_attr = cls.__dict__
+
+    # delayed import to reduce startup time
+    from inspect import isfunction
+
+    methods = [_m for _m in cls_attr.values() if isfunction(_m)]
+    for function in methods:
+        try:
+            if hasattr(function, 'compat_func_name'):
+                funcname = function.compat_func_name
+            else:
+                funcname = function.__name__
+        except AttributeError:
+            # not a function
+            continue
+        if testmatch.search(funcname) and not funcname.startswith('_'):
+            setattr(cls, funcname, decorator(function))
+    return
+
+
+def measure(code_str,times=1,label=None):
+    """
+    Return elapsed time for executing code in the namespace of the caller.
+
+    The supplied code string is compiled with the Python builtin ``compile``.
+    The precision of the timing is 10 milli-seconds. If the code will execute
+    fast on this timescale, it can be executed many times to get reasonable
+    timing accuracy.
+
+    Parameters
+    ----------
+    code_str : str
+        The code to be timed.
+    times : int, optional
+        The number of times the code is executed. Default is 1. The code is
+        only compiled once.
+    label : str, optional
+        A label to identify `code_str` with. This is passed into ``compile``
+        as the second argument (for run-time error messages).
+
+    Returns
+    -------
+    elapsed : float
+        Total elapsed time in seconds for executing `code_str` `times` times.
+
+    Examples
+    --------
+    >>> etime = np.testing.measure('for i in range(1000): np.sqrt(i**2)',
+    ...                            times=times)
+    >>> print("Time for a single execution : ", etime / times, "s")
+    Time for a single execution :  0.005 s
+
+    """
+    frame = sys._getframe(1)
+    locs, globs = frame.f_locals, frame.f_globals
+
+    code = compile(code_str,
+                   'Test name: %s ' % label,
+                   'exec')
+    i = 0
+    elapsed = jiffies()
+    while i < times:
+        i += 1
+        exec(code, globs, locs)
+    elapsed = jiffies() - elapsed
+    return 0.01*elapsed
+
+
+def _assert_valid_refcount(op):
+    """
+    Check that ufuncs don't mishandle refcount of object `1`.
+    Used in a few regression tests.
+    """
+    if not HAS_REFCOUNT:
+        return True
+    import numpy as np
+
+    b = np.arange(100*100).reshape(100, 100)
+    c = b
+    i = 1
+
+    rc = sys.getrefcount(i)
+    for j in range(15):
+        d = op(b, c)
+    assert_(sys.getrefcount(i) >= rc)
+    del d  # for pyflakes
+
+
+def assert_allclose(actual, desired, rtol=1e-7, atol=0, equal_nan=True,
+                    err_msg='', verbose=True):
+    """
+    Raises an AssertionError if two objects are not equal up to desired
+    tolerance.
+
+    The test is equivalent to ``allclose(actual, desired, rtol, atol)``.
+    It compares the difference between `actual` and `desired` to
+    ``atol + rtol * abs(desired)``.
+
+    .. versionadded:: 1.5.0
+
+    Parameters
+    ----------
+    actual : array_like
+        Array obtained.
+    desired : array_like
+        Array desired.
+    rtol : float, optional
+        Relative tolerance.
+    atol : float, optional
+        Absolute tolerance.
+    equal_nan : bool, optional.
+        If True, NaNs will compare equal.
+    err_msg : str, optional
+        The error message to be printed in case of failure.
+    verbose : bool, optional
+        If True, the conflicting values are appended to the error message.
+
+    Raises
+    ------
+    AssertionError
+        If actual and desired are not equal up to specified precision.
+
+    See Also
+    --------
+    assert_array_almost_equal_nulp, assert_array_max_ulp
+
+    Examples
+    --------
+    >>> x = [1e-5, 1e-3, 1e-1]
+    >>> y = np.arccos(np.cos(x))
+    >>> assert_allclose(x, y, rtol=1e-5, atol=0)
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+
+    def compare(x, y):
+        return np.core.numeric.isclose(x, y, rtol=rtol, atol=atol,
+                                       equal_nan=equal_nan)
+
+    actual, desired = np.asanyarray(actual), np.asanyarray(desired)
+    header = 'Not equal to tolerance rtol=%g, atol=%g' % (rtol, atol)
+    assert_array_compare(compare, actual, desired, err_msg=str(err_msg),
+                         verbose=verbose, header=header, equal_nan=equal_nan)
+
+
+def assert_array_almost_equal_nulp(x, y, nulp=1):
+    """
+    Compare two arrays relatively to their spacing.
+
+    This is a relatively robust method to compare two arrays whose amplitude
+    is variable.
+
+    Parameters
+    ----------
+    x, y : array_like
+        Input arrays.
+    nulp : int, optional
+        The maximum number of unit in the last place for tolerance (see Notes).
+        Default is 1.
+
+    Returns
+    -------
+    None
+
+    Raises
+    ------
+    AssertionError
+        If the spacing between `x` and `y` for one or more elements is larger
+        than `nulp`.
+
+    See Also
+    --------
+    assert_array_max_ulp : Check that all items of arrays differ in at most
+        N Units in the Last Place.
+    spacing : Return the distance between x and the nearest adjacent number.
+
+    Notes
+    -----
+    An assertion is raised if the following condition is not met::
+
+        abs(x - y) <= nulps * spacing(maximum(abs(x), abs(y)))
+
+    Examples
+    --------
+    >>> x = np.array([1., 1e-10, 1e-20])
+    >>> eps = np.finfo(x.dtype).eps
+    >>> np.testing.assert_array_almost_equal_nulp(x, x*eps/2 + x)
+
+    >>> np.testing.assert_array_almost_equal_nulp(x, x*eps + x)
+    Traceback (most recent call last):
+      ...
+    AssertionError: X and Y are not equal to 1 ULP (max is 2)
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+    ax = np.abs(x)
+    ay = np.abs(y)
+    ref = nulp * np.spacing(np.where(ax > ay, ax, ay))
+    if not np.all(np.abs(x-y) <= ref):
+        if np.iscomplexobj(x) or np.iscomplexobj(y):
+            msg = "X and Y are not equal to %d ULP" % nulp
+        else:
+            max_nulp = np.max(nulp_diff(x, y))
+            msg = "X and Y are not equal to %d ULP (max is %g)" % (nulp, max_nulp)
+        raise AssertionError(msg)
+
+
+def assert_array_max_ulp(a, b, maxulp=1, dtype=None):
+    """
+    Check that all items of arrays differ in at most N Units in the Last Place.
+
+    Parameters
+    ----------
+    a, b : array_like
+        Input arrays to be compared.
+    maxulp : int, optional
+        The maximum number of units in the last place that elements of `a` and
+        `b` can differ. Default is 1.
+    dtype : dtype, optional
+        Data-type to convert `a` and `b` to if given. Default is None.
+
+    Returns
+    -------
+    ret : ndarray
+        Array containing number of representable floating point numbers between
+        items in `a` and `b`.
+
+    Raises
+    ------
+    AssertionError
+        If one or more elements differ by more than `maxulp`.
+
+    See Also
+    --------
+    assert_array_almost_equal_nulp : Compare two arrays relatively to their
+        spacing.
+
+    Examples
+    --------
+    >>> a = np.linspace(0., 1., 100)
+    >>> res = np.testing.assert_array_max_ulp(a, np.arcsin(np.sin(a)))
+
+    """
+    __tracebackhide__ = True  # Hide traceback for py.test
+    import numpy as np
+    ret = nulp_diff(a, b, dtype)
+    if not np.all(ret <= maxulp):
+        raise AssertionError("Arrays are not almost equal up to %g ULP" %
+                             maxulp)
+    return ret
+
+
+def nulp_diff(x, y, dtype=None):
+    """For each item in x and y, return the number of representable floating
+    points between them.
+
+    Parameters
+    ----------
+    x : array_like
+        first input array
+    y : array_like
+        second input array
+    dtype : dtype, optional
+        Data-type to convert `x` and `y` to if given. Default is None.
+
+    Returns
+    -------
+    nulp : array_like
+        number of representable floating point numbers between each item in x
+        and y.
+
+    Examples
+    --------
+    # By definition, epsilon is the smallest number such as 1 + eps != 1, so
+    # there should be exactly one ULP between 1 and 1 + eps
+    >>> nulp_diff(1, 1 + np.finfo(x.dtype).eps)
+    1.0
+    """
+    import numpy as np
+    if dtype:
+        x = np.array(x, dtype=dtype)
+        y = np.array(y, dtype=dtype)
+    else:
+        x = np.array(x)
+        y = np.array(y)
+
+    t = np.common_type(x, y)
+    if np.iscomplexobj(x) or np.iscomplexobj(y):
+        raise NotImplementedError("_nulp not implemented for complex array")
+
+    x = np.array(x, dtype=t)
+    y = np.array(y, dtype=t)
+
+    if not x.shape == y.shape:
+        raise ValueError("x and y do not have the same shape: %s - %s" %
+                         (x.shape, y.shape))
+
+    def _diff(rx, ry, vdt):
+        diff = np.array(rx-ry, dtype=vdt)
+        return np.abs(diff)
+
+    rx = integer_repr(x)
+    ry = integer_repr(y)
+    return _diff(rx, ry, t)
+
+
+def _integer_repr(x, vdt, comp):
+    # Reinterpret binary representation of the float as sign-magnitude:
+    # take into account two-complement representation
+    # See also
+    # http://www.cygnus-software.com/papers/comparingfloats/comparingfloats.htm
+    rx = x.view(vdt)
+    if not (rx.size == 1):
+        rx[rx < 0] = comp - rx[rx < 0]
+    else:
+        if rx < 0:
+            rx = comp - rx
+
+    return rx
+
+
+def integer_repr(x):
+    """Return the signed-magnitude interpretation of the binary representation of
+    x."""
+    import numpy as np
+    if x.dtype == np.float32:
+        return _integer_repr(x, np.int32, np.int32(-2**31))
+    elif x.dtype == np.float64:
+        return _integer_repr(x, np.int64, np.int64(-2**63))
+    else:
+        raise ValueError("Unsupported dtype %s" % x.dtype)
+
+
+# The following two classes are copied from python 2.6 warnings module (context
+# manager)
+class WarningMessage(object):
+
+    """
+    Holds the result of a single showwarning() call.
+
+    Deprecated in 1.8.0
+
+    Notes
+    -----
+    `WarningMessage` is copied from the Python 2.6 warnings module,
+    so it can be used in NumPy with older Python versions.
+
+    """
+
+    _WARNING_DETAILS = ("message", "category", "filename", "lineno", "file",
+                        "line")
+
+    def __init__(self, message, category, filename, lineno, file=None,
+                    line=None):
+        local_values = locals()
+        for attr in self._WARNING_DETAILS:
+            setattr(self, attr, local_values[attr])
+        if category:
+            self._category_name = category.__name__
+        else:
+            self._category_name = None
+
+    def __str__(self):
+        return ("{message : %r, category : %r, filename : %r, lineno : %s, "
+                    "line : %r}" % (self.message, self._category_name,
+                                    self.filename, self.lineno, self.line))
+
+
+class WarningManager(object):
+    """
+    A context manager that copies and restores the warnings filter upon
+    exiting the context.
+
+    The 'record' argument specifies whether warnings should be captured by a
+    custom implementation of ``warnings.showwarning()`` and be appended to a
+    list returned by the context manager. Otherwise None is returned by the
+    context manager. The objects appended to the list are arguments whose
+    attributes mirror the arguments to ``showwarning()``.
+
+    The 'module' argument is to specify an alternative module to the module
+    named 'warnings' and imported under that name. This argument is only useful
+    when testing the warnings module itself.
+
+    Deprecated in 1.8.0
+
+    Notes
+    -----
+    `WarningManager` is a copy of the ``catch_warnings`` context manager
+    from the Python 2.6 warnings module, with slight modifications.
+    It is copied so it can be used in NumPy with older Python versions.
+
+    """
+
+    def __init__(self, record=False, module=None):
+        self._record = record
+        if module is None:
+            self._module = sys.modules['warnings']
+        else:
+            self._module = module
+        self._entered = False
+
+    def __enter__(self):
+        if self._entered:
+            raise RuntimeError("Cannot enter %r twice" % self)
+        self._entered = True
+        self._filters = self._module.filters
+        self._module.filters = self._filters[:]
+        self._showwarning = self._module.showwarning
+        if self._record:
+            log = []
+
+            def showwarning(*args, **kwargs):
+                log.append(WarningMessage(*args, **kwargs))
+            self._module.showwarning = showwarning
+            return log
+        else:
+            return None
+
+    def __exit__(self):
+        if not self._entered:
+            raise RuntimeError("Cannot exit %r without entering first" % self)
+        self._module.filters = self._filters
+        self._module.showwarning = self._showwarning
+
+
+@contextlib.contextmanager
+def _assert_warns_context(warning_class, name=None):
+    __tracebackhide__ = True  # Hide traceback for py.test
+    with suppress_warnings() as sup:
+        l = sup.record(warning_class)
+        yield
+        if not len(l) > 0:
+            name_str = " when calling %s" % name if name is not None else ""
+            raise AssertionError("No warning raised" + name_str)
+
+
+def assert_warns(warning_class, *args, **kwargs):
+    """
+    Fail unless the given callable throws the specified warning.
+
+    A warning of class warning_class should be thrown by the callable when
+    invoked with arguments args and keyword arguments kwargs.
+    If a different type of warning is thrown, it will not be caught.
+
+    If called with all arguments other than the warning class omitted, may be
+    used as a context manager:
+
+        with assert_warns(SomeWarning):
+            do_something()
+
+    The ability to be used as a context manager is new in NumPy v1.11.0.
+
+    .. versionadded:: 1.4.0
+
+    Parameters
+    ----------
+    warning_class : class
+        The class defining the warning that `func` is expected to throw.
+    func : callable
+        The callable to test.
+    \\*args : Arguments
+        Arguments passed to `func`.
+    \\*\\*kwargs : Kwargs
+        Keyword arguments passed to `func`.
+
+    Returns
+    -------
+    The value returned by `func`.
+
+    """
+    if not args:
+        return _assert_warns_context(warning_class)
+
+    func = args[0]
+    args = args[1:]
+    with _assert_warns_context(warning_class, name=func.__name__):
+        return func(*args, **kwargs)
+
+
+@contextlib.contextmanager
+def _assert_no_warnings_context(name=None):
+    __tracebackhide__ = True  # Hide traceback for py.test
+    with warnings.catch_warnings(record=True) as l:
+        warnings.simplefilter('always')
+        yield
+        if len(l) > 0:
+            name_str = " when calling %s" % name if name is not None else ""
+            raise AssertionError("Got warnings%s: %s" % (name_str, l))
+
+
+def assert_no_warnings(*args, **kwargs):
+    """
+    Fail if the given callable produces any warnings.
+
+    If called with all arguments omitted, may be used as a context manager:
+
+        with assert_no_warnings():
+            do_something()
+
+    The ability to be used as a context manager is new in NumPy v1.11.0.
+
+    .. versionadded:: 1.7.0
+
+    Parameters
+    ----------
+    func : callable
+        The callable to test.
+    \\*args : Arguments
+        Arguments passed to `func`.
+    \\*\\*kwargs : Kwargs
+        Keyword arguments passed to `func`.
+
+    Returns
+    -------
+    The value returned by `func`.
+
+    """
+    if not args:
+        return _assert_no_warnings_context()
+
+    func = args[0]
+    args = args[1:]
+    with _assert_no_warnings_context(name=func.__name__):
+        return func(*args, **kwargs)
+
+
+def _gen_alignment_data(dtype=float32, type='binary', max_size=24):
+    """
+    generator producing data with different alignment and offsets
+    to test simd vectorization
+
+    Parameters
+    ----------
+    dtype : dtype
+        data type to produce
+    type : string
+        'unary': create data for unary operations, creates one input
+                 and output array
+        'binary': create data for unary operations, creates two input
+                 and output array
+    max_size : integer
+        maximum size of data to produce
+
+    Returns
+    -------
+    if type is 'unary' yields one output, one input array and a message
+    containing information on the data
+    if type is 'binary' yields one output array, two input array and a message
+    containing information on the data
+
+    """
+    ufmt = 'unary offset=(%d, %d), size=%d, dtype=%r, %s'
+    bfmt = 'binary offset=(%d, %d, %d), size=%d, dtype=%r, %s'
+    for o in range(3):
+        for s in range(o + 2, max(o + 3, max_size)):
+            if type == 'unary':
+                inp = lambda: arange(s, dtype=dtype)[o:]
+                out = empty((s,), dtype=dtype)[o:]
+                yield out, inp(), ufmt % (o, o, s, dtype, 'out of place')
+                d = inp()
+                yield d, d, ufmt % (o, o, s, dtype, 'in place')
+                yield out[1:], inp()[:-1], ufmt % \
+                    (o + 1, o, s - 1, dtype, 'out of place')
+                yield out[:-1], inp()[1:], ufmt % \
+                    (o, o + 1, s - 1, dtype, 'out of place')
+                yield inp()[:-1], inp()[1:], ufmt % \
+                    (o, o + 1, s - 1, dtype, 'aliased')
+                yield inp()[1:], inp()[:-1], ufmt % \
+                    (o + 1, o, s - 1, dtype, 'aliased')
+            if type == 'binary':
+                inp1 = lambda: arange(s, dtype=dtype)[o:]
+                inp2 = lambda: arange(s, dtype=dtype)[o:]
+                out = empty((s,), dtype=dtype)[o:]
+                yield out, inp1(), inp2(),  bfmt % \
+                    (o, o, o, s, dtype, 'out of place')
+                d = inp1()
+                yield d, d, inp2(), bfmt % \
+                    (o, o, o, s, dtype, 'in place1')
+                d = inp2()
+                yield d, inp1(), d, bfmt % \
+                    (o, o, o, s, dtype, 'in place2')
+                yield out[1:], inp1()[:-1], inp2()[:-1], bfmt % \
+                    (o + 1, o, o, s - 1, dtype, 'out of place')
+                yield out[:-1], inp1()[1:], inp2()[:-1], bfmt % \
+                    (o, o + 1, o, s - 1, dtype, 'out of place')
+                yield out[:-1], inp1()[:-1], inp2()[1:], bfmt % \
+                    (o, o, o + 1, s - 1, dtype, 'out of place')
+                yield inp1()[1:], inp1()[:-1], inp2()[:-1], bfmt % \
+                    (o + 1, o, o, s - 1, dtype, 'aliased')
+                yield inp1()[:-1], inp1()[1:], inp2()[:-1], bfmt % \
+                    (o, o + 1, o, s - 1, dtype, 'aliased')
+                yield inp1()[:-1], inp1()[:-1], inp2()[1:], bfmt % \
+                    (o, o, o + 1, s - 1, dtype, 'aliased')
+
+
+class IgnoreException(Exception):
+    "Ignoring this exception due to disabled feature"
+
+
+@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