def test_bivariate_colorbar(self):
bivariate = Bivariate(([3, 2, 1], [0, 1, 2]))\
bivariate.opts(colorbar=True)
state = self._get_plot_state(bivariate)
trace = state['data'][0]
self.assertTrue(trace['showscale'])
bivariate.opts(colorbar=False)
state = self._get_plot_state(bivariate)
trace = state['data'][0]
self.assertFalse(trace['showscale'])
def test_bivariate_dframe_constructor(self):
dist = Bivariate(
pd.DataFrame({
'x': [0, 1, 2],
'y': [0, 1, 2]
}, columns=['x', 'y']))
self.assertEqual(dist.kdims, [Dimension('x'), Dimension('y')])
self.assertEqual(dist.vdims, [Dimension('Density')])
def bivariate(self, x, y, data=None):
data = self.data if data is None else data
if not x: x = data.columns[0]
if not y: y = data.columns[1]
opts = dict(plot=self._plot_opts,
norm=self._norm_opts,
style=self._style_opts)
return Bivariate(data, [x, y]).redim(**self._redim).opts(**opts)
def test_bivariate_state(self):
bivariate = Bivariate(([3, 2, 1], [0, 1, 2]))
state = self._get_plot_state(bivariate)
self.assertEqual(state['data'][0]['type'], 'histogram2dcontour')
self.assertEqual(state['data'][0]['x'], np.array([3, 2, 1]))
self.assertEqual(state['data'][0]['y'], np.array([0, 1, 2]))
self.assertEqual(state['layout']['xaxis']['range'], [1, 3])
self.assertEqual(state['layout']['yaxis']['range'], [0, 2])
self.assertEqual(state['data'][0]['contours']['coloring'], 'lines')
def test_bivariate_dframe_constructor(self):
if pd is None:
raise SkipTest("Test requires pandas, skipping.")
dist = Bivariate(
pd.DataFrame({
'x': [0, 1, 2],
'y': [0, 1, 2]
}, columns=['x', 'y']))
self.assertEqual(dist.kdims, [Dimension('x'), Dimension('y')])
self.assertEqual(dist.vdims, [Dimension('Density')])
def test_bivariate_colorbar(self):
bivariate = Bivariate(([3, 2, 1], [0, 1, 2]))\
bivariate.opts(colorbar=True)
state = self._get_plot_state(bivariate)
trace = state['data'][0]
self.assertTrue(trace['showscale'])
bivariate.opts(colorbar=False)
state = self._get_plot_state(bivariate)
trace = state['data'][0]
self.assertFalse(trace['showscale'])
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_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_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_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_array_range_vdims(self):
dist = Bivariate(np.array([[0, 1, 2], [0, 1, 3]]))
dmin, dmax = dist.range(2)
self.assertFalse(np.isfinite(dmin))
self.assertFalse(np.isfinite(dmax))
def test_bivariate_ncontours(self):
bivariate = Bivariate(([3, 2, 1], [0, 1, 2])).options(ncontours=5)
state = self._get_plot_state(bivariate)
self.assertEqual(state['data'][0]['ncontours'], 5)
self.assertEqual(state['data'][0]['autocontour'], False)
def test_visible(self):
element = Bivariate(([3, 2, 1], [0, 1, 2])).options(visible=False)
state = self._get_plot_state(element)
self.assertEqual(state['data'][0]['visible'], False)
def test_bivariate_array_constructor_custom_vdim(self):
dist = Bivariate(np.array([[0, 1, 2], [0, 1, 2]]), vdims=['Test'])
self.assertEqual(dist.kdims, [Dimension('x'), Dimension('y')])
self.assertEqual(dist.vdims, [Dimension('Test')])
def test_bivariate_array_kdim_type(self):
dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
self.assertTrue(np.issubdtype(dist.get_dimension_type(0), np.int_))
self.assertTrue(np.issubdtype(dist.get_dimension_type(1), np.int_))
def test_bivariate_array_vdim_type(self):
dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
self.assertEqual(dist.get_dimension_type(2), np.float64)
def test_bivariate_array_range_vdims(self):
dist = Bivariate(np.array([[0, 1, 2], [0, 1, 3]]))
dmin, dmax = dist.range(2)
self.assertFalse(np.isfinite(dmin))
self.assertFalse(np.isfinite(dmax))
def test_bivariate_array_range_kdims(self):
dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
self.assertEqual(dist.range(0), (0, 2))
self.assertEqual(dist.range(1), (1, 3))
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_array_constructor(self):
dist = Bivariate(np.array([[0, 1, 2], [0, 1, 2]]))
self.assertEqual(dist.kdims, [Dimension('x'), Dimension('y')])
self.assertEqual(dist.vdims, [Dimension('Density')])
def test_bivariate_array_kdim_type(self):
dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
self.assertTrue(np.issubdtype(dist.get_dimension_type(0), np.int_))
self.assertTrue(np.issubdtype(dist.get_dimension_type(1), np.int_))
def test_bivariate_dict_constructor(self):
dist = Bivariate({'x': [0, 1, 2], 'y': [0, 1, 2]}, ['x', 'y'])
self.assertEqual(dist.kdims, [Dimension('x'), Dimension('y')])
self.assertEqual(dist.vdims, [Dimension('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_array_range_kdims(self):
dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
self.assertEqual(dist.range(0), (0, 2))
self.assertEqual(dist.range(1), (1, 3))
def test_bivariate_from_points(self):
points = Points(np.array([[0, 1], [1, 2], [2, 3]]))
dist = Bivariate(points)
self.assertEqual(dist.kdims, points.kdims)
def test_bivariate_array_vdim_type(self):
dist = Bivariate(np.array([[0, 1], [1, 2], [2, 3]]))
self.assertEqual(dist.get_dimension_type(2), np.float64)
def test_bivariate_filled(self):
bivariate = Bivariate(([3, 2, 1], [0, 1, 2])).options(filled=True)
state = self._get_plot_state(bivariate)
self.assertEqual(state['data'][0]['contours']['coloring'], 'fill')
