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'))])