How to use the yellowbrick.target.FeatureCorrelation function in yellowbrick

def test_feature_correlation_select_feature_by_index(self):
        """
        Test selecting feature by index
        """
        viz = FeatureCorrelation(feature_index=[0, 2, 3])
        viz.fit(self.X, self.y)

        assert viz.scores_.shape[0] == 3

def test_feature_correlation_labels_from_index(self):
        """
        Test getting feature labels from index
        """
        viz = FeatureCorrelation()
        viz.fit(self.X, self.y)

        npt.assert_array_equal(viz.features_, np.arange(self.X.shape[1]))

def test_feature_correlation_select_feature_by_index_and_name(self):
        """
        Test selecting feature warning when both index and names are provided
        """
        feature_index = [0, 2, 3]
        feature_names = ['age']

        e = ('Both feature_index and feature_names are specified. '
             'feature_names is ignored')
        with pytest.raises(YellowbrickWarning, match=e):
            viz = FeatureCorrelation(feature_index=feature_index,
                                     feature_names=feature_names)
            viz.fit(self.X, self.y)
            assert viz.scores_.shape[0] == 3

def test_feature_correlation_select_feature_by_index_out_of_range(self):
        """
        Test selecting feature by feature index but index is out of range
        """
        e = 'Feature index is out of range'
        with pytest.raises(YellowbrickValueError, match=e):
            viz = FeatureCorrelation(feature_index=[0, 2, 10])
            viz.fit(self.X, self.y)

def test_feature_correlation_select_feature_by_name(self):
        """
        Test selecting feature by feature names
        """
        feature_names = ['age', 'sex', 'bp', 's5']

        viz = FeatureCorrelation(labels=self.labels,
                                 feature_names=feature_names)
        viz.fit(self.X, self.y)

        npt.assert_array_equal(viz.features_, feature_names)

def test_feature_correlation_labels(self):
        """
        Test labels as feature labels
        """
        viz = FeatureCorrelation(labels=self.labels)
        viz.fit(self.X, self.y)

        npt.assert_array_equal(viz.features_, self.labels)

def test_feature_correlation_sort(self):
        """
        Test sorting of correlation
        """
        viz = FeatureCorrelation(sort=True)
        viz.fit(self.X, self.y)

        assert np.all(viz.scores_[:-1] <= viz.scores_[1:])

def test_feature_correlation_integrated_mutual_info_regression(self):
        """
        Test FeatureCorrelation visualizer with mutual information regression
        """
        viz = FeatureCorrelation(method='mutual_info-regression')
        viz.fit(self.X, self.y, random_state=23456)
        viz.finalize()

        self.assert_images_similar(viz)

def test_feature_correlation_method_not_implemented(self):
        """
        Test FeatureCorrelation visualizer with unknown method
        """
        method = 'foo'
        e = ('Method foo not implement; choose from *')
        with pytest.raises(YellowbrickValueError, match=e):
            FeatureCorrelation(method=method)

def featcorr():
    data = load_diabetes()

    oz = FeatureCorrelation(ax=newfig())
    oz.fit(data.data, data.target)
    savefig(oz, "feature_correlation")