def test_curve_style_mapping_constant_value_dimensions(self):
vdims = ['y', 'num', 'cat']
ndoverlay = NdOverlay({
0: Curve([(0, 1, 0, 'A'), (1, 0, 0, 'A')], vdims=vdims),
1: Curve([(0, 1, 0, 'B'), (1, 1, 0, 'B')], vdims=vdims),
2: Curve([(0, 1, 1, 'A'), (1, 2, 1, 'A')], vdims=vdims),
3: Curve([(0, 1, 1, 'B'), (1, 3, 1, 'B')], vdims=vdims)}
).opts({
'Curve': dict(
color=dim('num').categorize({0: 'red', 1: 'blue'}),
linestyle=dim('cat').categorize({'A': '-.', 'B': '-'})
)
})
plot = mpl_renderer.get_plot(ndoverlay)
for k, sp in plot.subplots.items():
artist = sp.handles['artist']
color = artist.get_color()
if ndoverlay[k].iloc[0, 2] == 0:
self.assertEqual(color, 'red')
else:
self.assertEqual(color, 'blue')
linestyle = artist.get_linestyle()
if ndoverlay[k].iloc[0, 3] == 'A':
self.assertEqual(linestyle, '-.')
else:
self.assertEqual(linestyle, '-')
def test_curve_style_mapping_constant_value_dimensions(self):
vdims = ['y', 'num', 'cat']
ndoverlay = NdOverlay({
0: Curve([(0, 1, 0, 'A'), (1, 0, 0, 'A')], vdims=vdims),
1: Curve([(0, 1, 0, 'B'), (1, 1, 0, 'B')], vdims=vdims),
2: Curve([(0, 1, 1, 'A'), (1, 2, 1, 'A')], vdims=vdims),
3: Curve([(0, 1, 1, 'B'), (1, 3, 1, 'B')], vdims=vdims)}
).opts({
'Curve': dict(
color=dim('num').categorize({0: 'red', 1: 'blue'}),
line_dash=dim('cat').categorize({'A': 'solid', 'B': 'dashed'})
)
})
plot = bokeh_renderer.get_plot(ndoverlay)
for k, sp in plot.subplots.items():
glyph = sp.handles['glyph']
color = glyph.line_color
if ndoverlay[k].iloc[0, 2] == 0:
self.assertEqual(color, 'red')
else:
self.assertEqual(color, 'blue')
linestyle = glyph.line_dash
if ndoverlay[k].iloc[0, 3] == 'A':
self.assertEqual(linestyle, [])
else:
self.assertEqual(linestyle, [6])
def test_chord_edge_color_style_mapping(self):
g = self.chord.opts(style=dict(edge_color=dim('start').astype(str), edge_cmap=['#FFFFFF', '#000000']))
plot = bokeh_renderer.get_plot(g)
cmapper = plot.handles['edge_color_color_mapper']
edge_source = plot.handles['multi_line_1_source']
glyph = plot.handles['multi_line_1_glyph']
self.assertIsInstance(cmapper, CategoricalColorMapper)
self.assertEqual(cmapper.palette, ['#FFFFFF', '#000000', '#FFFFFF'])
self.assertEqual(cmapper.factors, ['0', '1', '2'])
self.assertEqual(edge_source.data['edge_color'], np.array(['0', '0', '1']))
self.assertEqual(glyph.line_color, {'field': 'edge_color', 'transform': cmapper})
def test_chord_edge_color_style_mapping_update(self):
hmap = HoloMap({0: self.make_chord(0), 1: self.make_chord(1)}).options(
edge_color=dim('weight').categorize({1: 'red', 2: 'green', 3: 'blue', 4: 'black'})
)
plot = mpl_renderer.get_plot(hmap)
edges = plot.handles['edges']
self.assertEqual(edges.get_edgecolors(), np.array([
[1, 0, 0, 1], [0, 0.501961, 0, 1], [0, 0, 1, 1]
]))
plot.update((1,))
self.assertEqual(edges.get_edgecolors(), np.array([
[0, 0.501961, 0, 1], [0, 0, 1, 1], [0, 0, 0, 1]
]))
def test_curve_style_mapping_ndoverlay_dimensions(self):
ndoverlay = NdOverlay({
(0, 'A'): Curve([1, 2, 0]), (0, 'B'): Curve([1, 2, 1]),
(1, 'A'): Curve([1, 2, 2]), (1, 'B'): Curve([1, 2, 3])},
['num', 'cat']
).opts({
'Curve': dict(
color=dim('num').categorize({0: 'red', 1: 'blue'}),
linestyle=dim('cat').categorize({'A': '-.', 'B': '-'})
)
})
plot = mpl_renderer.get_plot(ndoverlay)
for (num, cat), sp in plot.subplots.items():
artist = sp.handles['artist']
color = artist.get_color()
if num == 0:
self.assertEqual(color, 'red')
else:
self.assertEqual(color, 'blue')
linestyle = artist.get_linestyle()
if cat == 'A':
self.assertEqual(linestyle, '-.')
else:
self.assertEqual(linestyle, '-')
def test_curve_style_mapping_ndoverlay_dimensions(self):
ndoverlay = NdOverlay({
(0, 'A'): Curve([1, 2, 0]), (0, 'B'): Curve([1, 2, 1]),
(1, 'A'): Curve([1, 2, 2]), (1, 'B'): Curve([1, 2, 3])},
['num', 'cat']
).opts({
'Curve': dict(
color=dim('num').categorize({0: 'red', 1: 'blue'}),
line_dash=dim('cat').categorize({'A': 'solid', 'B': 'dashed'})
)
})
plot = bokeh_renderer.get_plot(ndoverlay)
for (num, cat), sp in plot.subplots.items():
glyph = sp.handles['glyph']
color = glyph.line_color
if num == 0:
self.assertEqual(color, 'red')
else:
self.assertEqual(color, 'blue')
linestyle = glyph.line_dash
if cat == 'A':
self.assertEqual(linestyle, [])
else:
self.assertEqual(linestyle, [6])
def test_chord_node_color_style_mapping_update(self):
hmap = HoloMap({0: self.make_chord(0), 1: self.make_chord(1)}).options(
node_color=dim('Label').categorize({0: 'red', 1: 'green', 2: 'blue', 3: 'black'})
)
plot = mpl_renderer.get_plot(hmap)
arcs = plot.handles['arcs']
nodes = plot.handles['nodes']
colors = np.array([
[1, 0, 0, 1], [0, 0.501961, 0, 1], [0, 0, 1, 1]
])
self.assertEqual(arcs.get_edgecolors(), colors)
self.assertEqual(nodes.get_facecolors(), colors)
plot.update((1,))
colors = np.array([
[0, 0.501961, 0, 1], [0, 0, 1, 1], [0, 0, 0, 1]
])
self.assertEqual(arcs.get_edgecolors(), colors)
self.assertEqual(nodes.get_facecolors(), colors)
def test_multi_dim_expression_not_applies(self):
self.assertEqual((dim('foo')-dim('bar')).applies(self.dataset),
False)
def test_sub_transform(self):
self.assertEqual((dim('int')-10).apply(self.dataset), self.linear_ints-10)
def test_min_transform(self):
self.assertEqual(dim('float').min().apply(self.dataset),
self.linear_floats.min())
def test_rsub_transform(self):
self.assertEqual((10-dim('int')).apply(self.dataset), 10-self.linear_ints)
def test_rdiv_transform(self):
self.assertEqual((10./dim('int')).apply(self.dataset), 10./self.linear_ints)
def test_mod_transform(self):
self.assertEqual((dim('int')%2).apply(self.dataset), self.linear_ints%2)
def test_rsub_transform(self):
self.assertEqual((10-dim('int')).apply(self.dataset), 10-self.linear_ints)
def test_rmul_transform(self):
self.assertEqual((10.*dim('float')).apply(self.dataset), self.linear_ints)
def test_rmod_transform(self):
self.assertEqual((2%dim('int')).apply(self.dataset), 2%self.linear_ints)
def test_rfloor_div_transform(self):
self.assertEqual((2//dim('int')).apply(self.dataset), 2//self.linear_ints)
def test_rdiv_transform(self):
self.assertEqual((10./dim('int')).apply(self.dataset), 10./self.linear_ints)
def test_radd_transform(self):
self.assertEqual((1+dim('float')).apply(self.dataset), 1+self.linear_floats)
def test_neg_transform(self):
self.assertEqual(-dim('negative').apply(self.dataset), self.linear_floats)
def test_div_transform(self):
self.assertEqual((dim('int')/10.).apply(self.dataset), self.linear_floats)
def test_ufunc_transform(self):
self.assertEqual(np.sin(dim('float')).apply(self.dataset), np.sin(self.linear_floats))
def test_sub_transform(self):
self.assertEqual((dim('int')-10).apply(self.dataset), self.linear_ints-10)
def test_astype_transform(self):
self.assertEqual(dim('int').astype(str).apply(self.dataset),
self.linear_ints.astype(str))
def test_rmod_transform(self):
self.assertEqual((2%dim('int')).apply(self.dataset), 2%self.linear_ints)
def test_cumsum_transform(self):
self.assertEqual(dim('float').cumsum().apply(self.dataset),
self.linear_floats.cumsum())
def test_astype_transform(self):
self.assertEqual(dim('int').astype(str).apply(self.dataset),
self.linear_ints.astype(str))
def test_min_transform(self):
self.assertEqual(dim('float').min().apply(self.dataset),
self.linear_floats.min())
def test_chord_edge_color_style_mapping(self):
g = self.chord.opts(style=dict(edge_color=dim('start').astype(str), edge_cmap=['#FFFFFF', '#000000']))
plot = mpl_renderer.get_plot(g)
edges = plot.handles['edges']
self.assertEqual(edges.get_array(), np.array([0, 0, 1]))
self.assertEqual(edges.get_clim(), (0, 2))
def test_round_transform(self):
self.assertEqual(dim('float').round().apply(self.dataset),
self.linear_floats.round())
def test_abs_transform(self):
expr = abs(dim('negative'))
self.check_apply(expr, self.linear_floats)
def test_neg_transform(self):
expr = -dim('negative')
self.check_apply(expr, self.linear_floats)
def test_multi_dim_expression_applies(self):
self.assertEqual((dim('int')-dim('float')).applies(self.dataset),
True)
def test_add_transform(self):
expr = dim('float') + 1
self.check_apply(expr, self.linear_floats+1)
def test_multi_dim_expression_partial_applies(self):
self.assertEqual((dim('int')-dim('bar')).applies(self.dataset),
False)
def test_div_transform(self):
expr = dim('int') / 10.
self.check_apply(expr, self.linear_floats)
def test_add_transform(self):
self.assertEqual((dim('float')+1).apply(self.dataset), self.linear_floats+1)
def test_floor_div_transform(self):
expr = dim('int') // 2
self.check_apply(expr, self.linear_ints//2)
def test_floor_div_transform(self):
self.assertEqual((dim('int')//2).apply(self.dataset), self.linear_ints//2)
def test_mod_transform(self):
expr = dim('int') % 2
self.check_apply(expr, self.linear_ints % 2)
def test_pow_transform(self):
self.assertEqual((dim('int')**2).apply(self.dataset), self.linear_ints**2)
def test_mul_transform(self):
expr = dim('float') * 10.
self.check_apply(expr, self.linear_ints.astype('float64'))
def test_radd_transform(self):
self.assertEqual((1+dim('float')).apply(self.dataset), 1+self.linear_floats)
def test_pow_transform(self):
expr = dim('int') ** 2
self.check_apply(expr, self.linear_ints ** 2)
def test_rfloor_div_transform(self):
self.assertEqual((2//dim('int')).apply(self.dataset), 2//self.linear_ints)
def test_sub_transform(self):
expr = dim('int') - 10
self.check_apply(expr, self.linear_ints - 10)
def test_rmul_transform(self):
self.assertEqual((10.*dim('float')).apply(self.dataset), self.linear_ints)
def test_radd_transform(self):
expr = 1 + dim('float')
self.check_apply(expr, 1 + self.linear_floats)
def test_ufunc_transform(self):
self.assertEqual(np.sin(dim('float')).apply(self.dataset), np.sin(self.linear_floats))
def test_rdiv_transform(self):
expr = 10. / dim('int')
self.check_apply(expr, 10. / self.linear_ints)
def test_cumsum_transform(self):
self.assertEqual(dim('float').cumsum().apply(self.dataset),
self.linear_floats.cumsum())
def test_rfloor_div_transform(self):
expr = 2 // dim('int')
self.check_apply(expr, 2 // self.linear_ints)
def test_round_transform(self):
self.assertEqual(dim('float').round().apply(self.dataset),
self.linear_floats.round())
def test_add_transform(self):
self.assertEqual((dim('float')+1).apply(self.dataset), self.linear_floats+1)
def test_floor_div_transform(self):
self.assertEqual((dim('int')//2).apply(self.dataset), self.linear_ints//2)
def test_mod_transform(self):
self.assertEqual((dim('int')%2).apply(self.dataset), self.linear_ints%2)
def test_div_transform(self):
self.assertEqual((dim('int')/10.).apply(self.dataset), self.linear_floats)
def test_multi_operator_expression_repr(self):
self.assertEqual(repr(((dim('float')-2)*3)**2),
"((dim('float')-2)*3)**2")
def test_neg_transform(self):
self.assertEqual(-dim('negative').apply(self.dataset), self.linear_floats)
def test_pow_transform(self):
self.assertEqual((dim('int')**2).apply(self.dataset), self.linear_ints**2)
