File: C:/Users/fred/anaconda3/Lib/site-packages/holoviews/tests/plotting/bokeh/test_barplot.py
import numpy as np
import pandas as pd
from bokeh.models import CategoricalColorMapper, LinearAxis, LinearColorMapper
from holoviews.core.overlay import NdOverlay, Overlay
from holoviews.element import Bars
from holoviews.plotting.bokeh.util import property_to_dict
from ..utils import ParamLogStream
from .test_plot import TestBokehPlot, bokeh_renderer
class TestBarPlot(TestBokehPlot):
def test_bars_hover_ensure_kdims_sanitized(self):
obj = Bars(np.random.rand(10,2), kdims=['Dim with spaces'])
obj = obj.opts(tools=['hover'])
self._test_hover_info(obj, [('Dim with spaces', '@{Dim_with_spaces}'), ('y', '@{y}')])
def test_bars_hover_ensure_vdims_sanitized(self):
obj = Bars(np.random.rand(10,2), vdims=['Dim with spaces'])
obj = obj.opts(tools=['hover'])
self._test_hover_info(obj, [('x', '@{x}'), ('Dim with spaces', '@{Dim_with_spaces}')])
def test_bars_suppress_legend(self):
bars = Bars([('A', 1), ('B', 2)]).opts(show_legend=False)
plot = bokeh_renderer.get_plot(bars)
plot.initialize_plot()
fig = plot.state
self.assertEqual(len(fig.legend), 0)
def test_empty_bars(self):
bars = Bars([], kdims=['x', 'y'], vdims=['z'])
plot = bokeh_renderer.get_plot(bars)
plot.initialize_plot()
source = plot.handles['source']
for v in source.data.values():
self.assertEqual(len(v), 0)
def test_bars_single_value(self):
df = pd.DataFrame({"time": [1], "value": [-1]})
bars = Bars(df)
plot = bokeh_renderer.get_plot(bars)
source = plot.handles['source']
assert source.data['time'], np.array([1])
assert source.data['value'], np.array([-1])
def test_bars_grouped_categories(self):
bars = Bars([('A', 0, 1), ('A', 1, -1), ('B', 0, 2)],
kdims=['Index', 'Category'], vdims=['Value'])
plot = bokeh_renderer.get_plot(bars)
source = plot.handles['source']
self.assertEqual([tuple(x) for x in source.data['xoffsets']],
[('A', '0'), ('B', '0'), ('A', '1')])
self.assertEqual(list(source.data['Category']), ['0', '0', '1'])
self.assertEqual(source.data['Value'], np.array([1, 2, -1]))
x_range = plot.handles['x_range']
self.assertEqual(x_range.factors, [('A', '0'), ('A', '1'), ('B', '0'), ('B', '1')])
def test_bars_multi_level_sorted(self):
box= Bars((['A', 'B']*15, [3, 10, 1]*10, np.random.randn(30)),
['Group', 'Category'], 'Value').aggregate(function=np.mean)
plot = bokeh_renderer.get_plot(box)
x_range = plot.handles['x_range']
self.assertEqual(x_range.factors, [
('A', '1'), ('A', '3'), ('A', '10'), ('B', '1'), ('B', '3'), ('B', '10')])
def test_box_whisker_multi_level_sorted_alphanumerically(self):
box= Bars(([3, 10, 1]*10, ['A', 'B']*15, np.random.randn(30)),
['Group', 'Category'], 'Value').aggregate(function=np.mean)
plot = bokeh_renderer.get_plot(box)
x_range = plot.handles['x_range']
self.assertEqual(x_range.factors, [
('1', 'A'), ('1', 'B'), ('3', 'A'), ('3', 'B'), ('10', 'A'), ('10', 'B')])
def test_bars_multi_level_two_factors_in_overlay(self):
# See: https://github.com/holoviz/holoviews/pull/5850
box= Bars((["1", "2", "3"]*10, ['A', 'B']*15, np.random.randn(30)),
['Group', 'Category'], 'Value').aggregate(function=np.mean)
overlay = Overlay([box])
plot = bokeh_renderer.get_plot(overlay)
left_axis = plot.handles["plot"].left[0]
assert isinstance(left_axis, LinearAxis)
def test_bars_positive_negative_mixed(self):
bars = Bars([('A', 0, 1), ('A', 1, -1), ('B', 0, 2)],
kdims=['Index', 'Category'], vdims=['Value'])
plot = bokeh_renderer.get_plot(bars.opts(stacked=True))
source = plot.handles['source']
self.assertEqual(list(source.data['Category']), ['1', '0', '0'])
self.assertEqual(list(source.data['Index']), ['A', 'A', 'B'])
self.assertEqual(source.data['top'], np.array([0, 1, 2]))
self.assertEqual(source.data['bottom'], np.array([-1, 0, 0]))
def test_bars_logy(self):
bars = Bars([('A', 1), ('B', 2), ('C', 3)],
kdims=['Index'], vdims=['Value'])
plot = bokeh_renderer.get_plot(bars.opts(logy=True))
source = plot.handles['source']
glyph = plot.handles['glyph']
y_range = plot.handles['y_range']
self.assertEqual(list(source.data['Index']), ['A', 'B', 'C'])
self.assertEqual(source.data['Value'], np.array([1, 2, 3]))
self.assertEqual(glyph.bottom, 0.01)
self.assertEqual(y_range.start, 0.01)
self.assertEqual(y_range.end, 3.348369522101713)
def test_bars_logy_explicit_range(self):
bars = Bars([('A', 1), ('B', 2), ('C', 3)],
kdims=['Index'], vdims=['Value']).redim.range(Value=(0.001, 3))
plot = bokeh_renderer.get_plot(bars.opts(logy=True))
source = plot.handles['source']
glyph = plot.handles['glyph']
y_range = plot.handles['y_range']
self.assertEqual(list(source.data['Index']), ['A', 'B', 'C'])
self.assertEqual(source.data['Value'], np.array([1, 2, 3]))
self.assertEqual(glyph.bottom, 0.001)
self.assertEqual(y_range.start, 0.001)
self.assertEqual(y_range.end, 3)
def test_bars_ylim(self):
bars = Bars([1, 2, 3]).opts(ylim=(0, 200))
plot = bokeh_renderer.get_plot(bars)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, 0)
self.assertEqual(y_range.end, 200)
def test_bars_padding_square(self):
points = Bars([(1, 2), (2, -1), (3, 3)]).opts(padding=0.1)
plot = bokeh_renderer.get_plot(points)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, -1.4)
self.assertEqual(y_range.end, 3.4)
def test_bars_padding_square_positive(self):
points = Bars([(1, 2), (2, 1), (3, 3)]).opts(padding=0.1)
plot = bokeh_renderer.get_plot(points)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, 0)
self.assertEqual(y_range.end, 3.2)
def test_bars_padding_square_negative(self):
points = Bars([(1, -2), (2, -1), (3, -3)]).opts(padding=0.1)
plot = bokeh_renderer.get_plot(points)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, -3.2)
self.assertEqual(y_range.end, 0)
def test_bars_padding_nonsquare(self):
bars = Bars([(1, 2), (2, 1), (3, 3)]).opts(padding=0.1, width=600)
plot = bokeh_renderer.get_plot(bars)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, 0)
self.assertEqual(y_range.end, 3.2)
def test_bars_padding_logx(self):
bars = Bars([(1, 1), (2, 2), (3,3)]).opts(padding=0.1, logx=True)
plot = bokeh_renderer.get_plot(bars)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, 0)
self.assertEqual(y_range.end, 3.2)
def test_bars_padding_logy(self):
bars = Bars([(1, 2), (2, 1), (3, 3)]).opts(padding=0.1, logy=True)
plot = bokeh_renderer.get_plot(bars)
y_range = plot.handles['y_range']
self.assertEqual(y_range.start, 0.01)
self.assertEqual(y_range.end, 3.3483695221017129)
def test_bars_boolean_kdims(self):
data = pd.DataFrame({"x1": [1, 1, 2, 2], "x2": [False, True, False, True], "y": [3, 1, 2, 2]})
bars = Bars(data, kdims=["x1", "x2"])
plot = bokeh_renderer.get_plot(bars)
x_range = plot.handles['x_range']
assert x_range.factors == [('1', 'False'), ('1', 'True'), ('2', 'False'), ('2', 'True')]
###########################
# Styling mapping #
###########################
def test_bars_color_op(self):
bars = Bars([(0, 0, '#000'), (0, 1, '#F00'), (0, 2, '#0F0')],
vdims=['y', 'color']).opts(color='color')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['color'], np.array(['#000', '#F00', '#0F0']))
self.assertEqual(property_to_dict(glyph.fill_color), {'field': 'color'})
self.assertEqual(property_to_dict(glyph.line_color), 'black')
def test_bars_linear_color_op(self):
bars = Bars([(0, 0, 0), (0, 1, 1), (0, 2, 2)],
vdims=['y', 'color']).opts(color='color')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
cmapper = plot.handles['color_color_mapper']
self.assertTrue(cmapper, LinearColorMapper)
self.assertEqual(cmapper.low, 0)
self.assertEqual(cmapper.high, 2)
self.assertEqual(cds.data['color'], np.array([0, 1, 2]))
self.assertEqual(property_to_dict(glyph.fill_color), {'field': 'color', 'transform': cmapper})
self.assertEqual(property_to_dict(glyph.line_color), 'black')
def test_bars_categorical_color_op(self):
bars = Bars([(0, 0, 'A'), (0, 1, 'B'), (0, 2, 'C')],
vdims=['y', 'color']).opts(color='color')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
cmapper = plot.handles['color_color_mapper']
self.assertTrue(cmapper, CategoricalColorMapper)
self.assertEqual(cmapper.factors, ['A', 'B', 'C'])
self.assertEqual(cds.data['color'], np.array(['A', 'B', 'C']))
self.assertEqual(property_to_dict(glyph.fill_color), {'field': 'color', 'transform': cmapper})
self.assertEqual(property_to_dict(glyph.line_color), 'black')
def test_bars_line_color_op(self):
bars = Bars([(0, 0, '#000'), (0, 1, '#F00'), (0, 2, '#0F0')],
vdims=['y', 'color']).opts(line_color='color')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['line_color'], np.array(['#000', '#F00', '#0F0']))
self.assertNotEqual(property_to_dict(glyph.fill_color), {'field': 'line_color'})
self.assertEqual(property_to_dict(glyph.line_color), {'field': 'line_color'})
def test_bars_fill_color_op(self):
bars = Bars([(0, 0, '#000'), (0, 1, '#F00'), (0, 2, '#0F0')],
vdims=['y', 'color']).opts(fill_color='color')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['fill_color'], np.array(['#000', '#F00', '#0F0']))
self.assertEqual(property_to_dict(glyph.fill_color), {'field': 'fill_color'})
self.assertNotEqual(property_to_dict(glyph.line_color), {'field': 'fill_color'})
def test_bars_alpha_op(self):
bars = Bars([(0, 0, 0), (0, 1, 0.2), (0, 2, 0.7)],
vdims=['y', 'alpha']).opts(alpha='alpha')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['alpha'], np.array([0, 0.2, 0.7]))
self.assertEqual(property_to_dict(glyph.fill_alpha), {'field': 'alpha'})
def test_bars_line_alpha_op(self):
bars = Bars([(0, 0, 0), (0, 1, 0.2), (0, 2, 0.7)],
vdims=['y', 'alpha']).opts(line_alpha='alpha')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['line_alpha'], np.array([0, 0.2, 0.7]))
self.assertEqual(property_to_dict(glyph.line_alpha), {'field': 'line_alpha'})
self.assertNotEqual(property_to_dict(glyph.fill_alpha), {'field': 'line_alpha'})
def test_bars_fill_alpha_op(self):
bars = Bars([(0, 0, 0), (0, 1, 0.2), (0, 2, 0.7)],
vdims=['y', 'alpha']).opts(fill_alpha='alpha')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['fill_alpha'], np.array([0, 0.2, 0.7]))
self.assertNotEqual(property_to_dict(glyph.line_alpha), {'field': 'fill_alpha'})
self.assertEqual(property_to_dict(glyph.fill_alpha), {'field': 'fill_alpha'})
def test_bars_line_width_op(self):
bars = Bars([(0, 0, 1), (0, 1, 4), (0, 2, 8)],
vdims=['y', 'line_width']).opts(line_width='line_width')
plot = bokeh_renderer.get_plot(bars)
cds = plot.handles['cds']
glyph = plot.handles['glyph']
self.assertEqual(cds.data['line_width'], np.array([1, 4, 8]))
self.assertEqual(property_to_dict(glyph.line_width), {'field': 'line_width'})
def test_op_ndoverlay_value(self):
colors = ['blue', 'red']
overlay = NdOverlay({color: Bars(np.arange(i+2)) for i, color in enumerate(colors)}, 'Color').opts('Bars', fill_color='Color')
plot = bokeh_renderer.get_plot(overlay)
for subplot, color in zip(plot.subplots.values(), colors):
self.assertEqual(subplot.handles['glyph'].fill_color, color)
def test_bars_color_index_color_clash(self):
bars = Bars([(0, 0, 0), (0, 1, 1), (0, 2, 2)],
vdims=['y', 'color']).opts(color='color', color_index='color')
with ParamLogStream() as log:
bokeh_renderer.get_plot(bars)
log_msg = log.stream.read()
warning = (
"The `color_index` parameter is deprecated in favor of color style mapping, "
"e.g. `color=dim('color')` or `line_color=dim('color')`\nCannot declare style "
"mapping for 'color' option and declare a color_index; ignoring the color_index.\n"
)
self.assertEqual(log_msg, warning)
def test_bars_continuous_data_list_same_interval(self):
bars = Bars(([0, 1, 2], [10, 20, 30]))
plot = bokeh_renderer.get_plot(bars)
np.testing.assert_almost_equal(plot.handles["glyph"].width, 0.8)
def test_bars_continuous_data_list_same_interval_custom_width(self):
bars = Bars(([0, 1, 2], [10, 20, 30])).opts(bar_width=0.5)
plot = bokeh_renderer.get_plot(bars)
assert plot.handles["glyph"].width == 0.5
def test_bars_continuous_data_list_diff_interval(self):
bars = Bars(([0, 3, 10], [10, 20, 30]))
plot = bokeh_renderer.get_plot(bars)
np.testing.assert_almost_equal(plot.handles["glyph"].width, 0.11428571)
def test_bars_continuous_datetime(self):
bars = Bars((pd.date_range("1/1/2000", periods=10), np.random.rand(10)))
plot = bokeh_renderer.get_plot(bars)
np.testing.assert_almost_equal(plot.handles["glyph"].width, 69120000.0)
def test_bars_not_continuous_data_list(self):
bars = Bars([("A", 1), ("B", 2), ("C", 3)])
plot = bokeh_renderer.get_plot(bars)
assert plot.handles["glyph"].width == 0.8
def test_bars_not_continuous_data_list_custom_width(self):
bars = Bars([("A", 1), ("B", 2), ("C", 3)]).opts(bar_width=1)
plot = bokeh_renderer.get_plot(bars)
assert plot.handles["glyph"].width == 1
def test_bars_group(self):
samples = 100
pets = ["Cat", "Dog", "Hamster", "Rabbit"]
genders = ["Female", "Male", "N/A"]
np.random.seed(100)
pets_sample = np.random.choice(pets, samples)
gender_sample = np.random.choice(genders, samples)
bars = Bars(
(pets_sample, gender_sample, np.ones(samples)), ["Pets", "Gender"]
).aggregate(function=np.sum)
plot = bokeh_renderer.get_plot(bars)
assert plot.handles["glyph"].width == 0.8
def test_bar_group_stacked(self):
samples = 100
pets = ["Cat", "Dog", "Hamster", "Rabbit"]
genders = ["Female", "Male", "N/A"]
np.random.seed(100)
pets_sample = np.random.choice(pets, samples)
gender_sample = np.random.choice(genders, samples)
bars = (
Bars((pets_sample, gender_sample, np.ones(samples)), ["Pets", "Gender"])
.aggregate(function=np.sum)
.opts(stacked=True)
)
plot = bokeh_renderer.get_plot(bars)
assert plot.handles["glyph"].width == 0.8