Python warnings.simplefilter函数代码示例

 def test_parseable_output_deprecated(self):
     with warnings.catch_warnings(record=True) as cm:
         warnings.simplefilter("always")
         ParseableTextReporter()
     
     self.assertEqual(len(cm), 1)
     self.assertIsInstance(cm[0].message, DeprecationWarning)

 def test_idlever(self):
     with warnings.catch_warnings(record=True) as w:
         warnings.simplefilter("always")
         import idlelib.idlever
         self.assertEqual(len(w), 1)
         self.assertTrue(issubclass(w[-1].category, DeprecationWarning))
         self.assertIn("version", str(w[-1].message))

    def test_op(self):
        # motor.Op is deprecated in Motor 0.2, superseded by Tornado 3 Futures.
        # Just make sure it still works.

        collection = self.cx.pymongo_test.test_collection
        doc = {'_id': 'jesse'}

        with warnings.catch_warnings(record=True) as w:
            warnings.simplefilter("always")

            # Op works.
            _id = yield motor.Op(collection.insert, doc)
            self.assertEqual('jesse', _id)

            # Raised a DeprecationWarning.
            self.assertEqual(1, len(w))
            warning = w[-1]
            self.assertTrue(issubclass(warning.category, DeprecationWarning))
            message = str(warning.message)
            self.assertTrue("deprecated" in message)
            self.assertTrue("insert" in message)

        result = yield motor.Op(collection.find_one, doc)
        self.assertEqual(doc, result)

        # Make sure it works with no args.
        result = yield motor.Op(collection.find_one)
        self.assertTrue(isinstance(result, dict))

        with assert_raises(pymongo.errors.DuplicateKeyError):
            yield motor.Op(collection.insert, doc)

def _lasso_stability_path(X, y, mask, weights, eps):
    "Inner loop of lasso_stability_path"
    X = X * weights[np.newaxis, :]
    X = X[safe_mask(X, mask), :]
    y = y[mask]

    alpha_max = np.max(np.abs(np.dot(X.T, y))) / X.shape[0]
    alpha_min = eps * alpha_max  # set for early stopping in path
    with warnings.catch_warnings():
        warnings.simplefilter('ignore', ConvergenceWarning)
        alphas, _, coefs = lars_path(X, y, method='lasso', verbose=False,
                                     alpha_min=alpha_min)
    # Scale alpha by alpha_max
    alphas /= alphas[0]
    # Sort alphas in assending order
    alphas = alphas[::-1]
    coefs = coefs[:, ::-1]
    # Get rid of the alphas that are too small
    mask = alphas >= eps
    # We also want to keep the first one: it should be close to the OLS
    # solution
    mask[0] = True
    alphas = alphas[mask]
    coefs = coefs[:, mask]
    return alphas, coefs

def __unit_test_onset_function(metric):
    with warnings.catch_warnings(record=True) as w:
        warnings.simplefilter('always')
        # First, test for a warning on empty onsets
        metric(np.array([]), np.arange(10))
        assert len(w) == 1
        assert issubclass(w[-1].category, UserWarning)
        assert str(w[-1].message) == "Reference onsets are empty."
        metric(np.arange(10), np.array([]))
        assert len(w) == 2
        assert issubclass(w[-1].category, UserWarning)
        assert str(w[-1].message) == "Estimated onsets are empty."
        # And that the metric is 0
        assert np.allclose(metric(np.array([]), np.array([])), 0)

    # Now test validation function - onsets must be 1d ndarray
    onsets = np.array([[1., 2.]])
    nose.tools.assert_raises(ValueError, metric, onsets, onsets)
    # onsets must be in seconds (so not huge)
    onsets = np.array([1e10, 1e11])
    nose.tools.assert_raises(ValueError, metric, onsets, onsets)
    # onsets must be sorted
    onsets = np.array([2., 1.])
    nose.tools.assert_raises(ValueError, metric, onsets, onsets)

    # Valid onsets which are the same produce a score of 1 for all metrics
    onsets = np.arange(10, dtype=np.float)
    assert np.allclose(metric(onsets, onsets), 1)

    def test_get_default_base_name_deprecation(self):
        msg = "`CustomRouter.get_default_base_name` method should be renamed `get_default_basename`."

        # Class definition should raise a warning
        with pytest.warns(RemovedInDRF311Warning) as w:
            warnings.simplefilter('always')

            class CustomRouter(SimpleRouter):
                def get_default_base_name(self, viewset):
                    return 'foo'

        assert len(w) == 1
        assert str(w[0].message) == msg

        # Deprecated method implementation should still be called
        with warnings.catch_warnings(record=True) as w:
            warnings.simplefilter('always')

            router = CustomRouter()
            router.register('mock', MockViewSet)

        assert len(w) == 0
        assert router.registry == [
            ('mock', MockViewSet, 'foo'),
        ]

 def test_usgs_eventype(self):
     filename = os.path.join(self.path, 'usgs_event.xml')
     with warnings.catch_warnings(record=True):
         warnings.simplefilter("ignore")
         catalog = _read_quakeml(filename)
     self.assertEqual(len(catalog), 1)
     self.assertEqual(catalog[0].event_type, 'quarry blast')

 def test_decorator_attrs(self):
     def fxn(module): pass
     with warnings.catch_warnings():
         warnings.simplefilter('ignore', DeprecationWarning)
         wrapped = self.util.set_package(fxn)
     self.assertEqual(wrapped.__name__, fxn.__name__)
     self.assertEqual(wrapped.__qualname__, fxn.__qualname__)

 def test_attribute_is_None(self):
     loader = self.DummyLoader()
     loader.module = types.ModuleType('blah')
     loader.module.__loader__ = None
     with warnings.catch_warnings():
         warnings.simplefilter('ignore', DeprecationWarning)
         self.assertEqual(loader, loader.load_module('blah').__loader__)

 def setUp(self):
     super(converterTestsCDF, self).setUp()
     self.SDobj = dm.SpaceData(attrs={'global': 'test'})
     self.SDobj['var'] = dm.dmarray([1, 2, 3], attrs={'a': 'a'})
     self.testdir = tempfile.mkdtemp()
     self.testfile = os.path.join(self.testdir, 'test.cdf')
     warnings.simplefilter('error', dm.DMWarning)

 def tearDown(self):
     super(converterTestsCDF, self).tearDown()
     del self.SDobj
     if os.path.exists(self.testfile):
         os.remove(self.testfile)
     os.rmdir(self.testdir)
     warnings.simplefilter('default', dm.DMWarning)

    def properties(self):
        """
        return a dictionary mapping property name -> value
        """
        o = self.oorig
        getters = [name for name in dir(o)
                   if name.startswith('get_')
                   and six.callable(getattr(o, name))]
        getters.sort()
        d = dict()
        for name in getters:
            func = getattr(o, name)
            if self.is_alias(func):
                continue

            try:
                with warnings.catch_warnings():
                    warnings.simplefilter('ignore')
                    val = func()
            except:
                continue
            else:
                d[name[4:]] = val

        return d

    def _evaluate_projection(self, x, y):
        """
        kNNEvaluate - evaluate class separation in the given projection using a k-NN method
        Parameters
        ----------
        x - variables to evaluate
        y - class

        Returns
        -------
        scores
        """
        if self.percent_data_used != 100:
            rand = np.random.choice(len(x), int(len(x) * self.percent_data_used / 100),
                                    replace=False)
            x = x[rand]
            y = y[rand]
        neigh = KNeighborsClassifier(n_neighbors=3) if self.attr_color.is_discrete else \
            KNeighborsRegressor(n_neighbors=3)
        assert ~(np.isnan(x).any(axis=None) | np.isnan(x).any(axis=None))
        neigh.fit(x, y)
        with warnings.catch_warnings():
            warnings.simplefilter("ignore", category=UserWarning)
            scores = cross_val_score(neigh, x, y, cv=3)
        return scores.mean()

def test_ica_rank_reduction():
    """Test recovery of full data when no source is rejected"""
    # Most basic recovery
    raw = Raw(raw_fname).crop(0.5, stop, False)
    raw.load_data()
    picks = pick_types(raw.info, meg=True, stim=False, ecg=False,
                       eog=False, exclude='bads')[:10]
    n_components = 5
    max_pca_components = len(picks)
    for n_pca_components in [6, 10]:
        with warnings.catch_warnings(record=True):  # non-convergence
            warnings.simplefilter('always')
            ica = ICA(n_components=n_components,
                      max_pca_components=max_pca_components,
                      n_pca_components=n_pca_components,
                      method='fastica', max_iter=1).fit(raw, picks=picks)

        rank_before = raw.estimate_rank(picks=picks)
        assert_equal(rank_before, len(picks))
        raw_clean = ica.apply(raw, copy=True)
        rank_after = raw_clean.estimate_rank(picks=picks)
        # interaction between ICA rejection and PCA components difficult
        # to preduct. Rank_after often seems to be 1 higher then
        # n_pca_components
        assert_true(n_components < n_pca_components <= rank_after <=
                    rank_before)

def test_unicode_decode_error():
    # decode_error default to strict, so this should fail
    # First, encode (as bytes) a unicode string.
    text = "J'ai mang\xe9 du kangourou  ce midi, c'\xe9tait pas tr\xeas bon."
    text_bytes = text.encode('utf-8')

    # Then let the Analyzer try to decode it as ascii. It should fail,
    # because we have given it an incorrect encoding.
    wa = CountVectorizer(ngram_range=(1, 2), encoding='ascii').build_analyzer()
    assert_raises(UnicodeDecodeError, wa, text_bytes)

    ca = CountVectorizer(analyzer='char', ngram_range=(3, 6),
                         encoding='ascii').build_analyzer()
    assert_raises(UnicodeDecodeError, ca, text_bytes)

    # Check the old interface
    with warnings.catch_warnings(record=True) as w:
        warnings.simplefilter("always")

        ca = CountVectorizer(analyzer='char', ngram_range=(3, 6),
                             charset='ascii').build_analyzer()
        assert_raises(UnicodeDecodeError, ca, text_bytes)

        assert_equal(len(w), 1)
        assert_true(issubclass(w[0].category, DeprecationWarning))
        assert_true("charset" in str(w[0].message).lower())