def test_distribution_composite_not_filled(self): dist = Distribution(np.array([0, 1, 2]), ).opts(plot=dict(filled=False)) curve = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(curve, Curve) self.assertEqual(curve.vdims, [Dimension(('Value_density', 'Value Density'))])
def test_distribution_composite(self): dist = Distribution(np.array([0, 1, 2])) area = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(area, Area) self.assertEqual(area.vdims, [Dimension(('Value_density', 'Value Density'))])
def test_bivariate_composite_empty_not_filled(self): dist = Bivariate([]).opts(plot=dict(filled=True)) contours = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(contours, Contours) self.assertEqual(contours.vdims, [Dimension('Density')]) self.assertEqual(len(contours), 0)
def test_bivariate_composite(self): dist = Bivariate(np.random.rand(10, 2)) contours = Compositor.collapse_element(dist) self.assertIsInstance(contours, Contours) self.assertEqual(contours.vdims, [Dimension('Density')])
def test_bivariate_composite_filled(self): dist = Bivariate(np.random.rand(10, 2)).opts(plot=dict(filled=True)) contours = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(contours, Polygons) self.assertEqual(contours.vdims[0].name, 'Density')
def test_bivariate_composite_transfer_opts_with_group(self): dist = Bivariate(np.random.rand(10, 2), group='Test').opts(style=dict(cmap='Blues')) contours = Compositor.collapse_element(dist) opts = Store.lookup_options('matplotlib', contours, 'style').kwargs self.assertEqual(opts.get('cmap', None), 'Blues')
def test_bivariate_composite_filled(self): dist = Bivariate(np.random.rand(10, 2)).opts(plot=dict(filled=True)) contours = Compositor.collapse_element(dist) self.assertIsInstance(contours, Polygons) self.assertEqual(contours.vdims, [Dimension('Density')])
def test_distribution_composite_transfer_opts_with_group(self): dist = Distribution(np.array([0, 1, 2]), group='Test').opts(style=dict(color='red')) area = Compositor.collapse_element(dist, backend='matplotlib') opts = Store.lookup_options('matplotlib', area, 'style').kwargs self.assertEqual(opts.get('color', None), 'red')
def test_distribution_composite_custom_vdim(self): dist = Distribution(np.array([0, 1, 2]), vdims=['Test']) area = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(area, Area) self.assertEqual(area.vdims, [Dimension('Test')])
def test_distribution_composite_empty_not_filled(self): dist = Distribution([]).opts(plot=dict(filled=False)) curve = Compositor.collapse_element(dist) self.assertIsInstance(curve, Curve) self.assertEqual(curve.vdims, [Dimension(('Value_density', 'Value Density'))])
def test_distribution_composite(self): dist = Distribution(np.array([0, 1, 2])) area = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(area, Area) self.assertEqual(area.vdims, [Dimension(('Value_density', 'Density'))])
def test_bivariate_composite_filled(self): dist = Bivariate(np.random.rand(10, 2)).opts(plot=dict(filled=True)) contours = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(contours, Polygons) self.assertEqual(contours.vdims[0].name, 'Density')
def test_bivariate_composite(self): dist = Bivariate(np.random.rand(10, 2)) contours = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(contours, Contours) self.assertEqual(contours.vdims, [Dimension('Density')])
def test_bivariate_composite_filled(self): dist = Bivariate(np.random.rand(10, 2)).opts(plot=dict(filled=True)) contours = Compositor.collapse_element(dist) self.assertIsInstance(contours, Polygons) self.assertEqual(contours.vdims, [Dimension('Density')])
def test_distribution_composite_transfer_opts_with_group(self): dist = Distribution(np.array([0, 1, 2]), group='Test').opts(style=dict(color='red')) area = Compositor.collapse_element(dist, backend='matplotlib') opts = Store.lookup_options('matplotlib', area, 'style').kwargs self.assertEqual(opts.get('color', None), 'red')
def test_distribution_composite_empty_not_filled(self): dist = Distribution([]).opts(plot=dict(filled=False)) curve = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(curve, Curve) self.assertEqual(curve.vdims, [Dimension(('Value_density', 'Density'))])
def test_distribution_composite_custom_vdim(self): dist = Distribution(np.array([0, 1, 2]), vdims=['Test']) area = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(area, Area) self.assertEqual(area.vdims, [Dimension('Test')])
def test_bivariate_composite_transfer_opts_with_group(self): dist = Bivariate(np.random.rand(10, 2), group='Test').opts(style=dict(cmap='Blues')) contours = Compositor.collapse_element(dist, backend='matplotlib') opts = Store.lookup_options('matplotlib', contours, 'style').kwargs self.assertEqual(opts.get('cmap', None), 'Blues')
def test_bivariate_composite_custom_vdim(self): dist = Bivariate(np.random.rand(10, 2), vdims=['Test']) contours = Compositor.collapse_element(dist) self.assertIsInstance(contours, Contours) self.assertEqual(contours.vdims, [Dimension('Test')])
def test_bivariate_composite_custom_vdim(self): dist = Bivariate(np.random.rand(10, 2), vdims=['Test']) contours = Compositor.collapse_element(dist, backend='matplotlib') self.assertIsInstance(contours, Contours) self.assertEqual(contours.vdims, [Dimension('Test')])
def test_bivariate_composite_empty_not_filled(self): dist = Bivariate([]).opts(plot=dict(filled=True)) contours = Compositor.collapse_element(dist) self.assertIsInstance(contours, Contours) self.assertEqual(contours.vdims, [Dimension('Density')]) self.assertEqual(len(contours), 0)
def test_distribution_composite_not_filled(self): dist = Distribution(np.array([0, 1, 2])).opts(plot=dict(filled=False)) curve = Compositor.collapse_element(dist) self.assertIsInstance(curve, Curve) self.assertEqual(curve.vdims, [Dimension(('Value_density', 'Value Density'))])