http://bokeh.pydata.org/en/latest/docs/user_guide/annotations.html
Titles（标题）
添加标题
from bokeh.plotting import figure, show, output_file
p = figure(title=
"Basic Title", plot_width=
300, plot_height=
300)
p.circle([
1,
2], [
3,
4])
output_file("title.html")
show(p)
设置标题属性
from bokeh
.plotting import figure, show, output_file
p = figure(plot_width=
300, plot_height=
300)
p
.circle([
1,
2], [
3,
4])
# configure visual properties on a plot's title attribute
p
.title.text =
"Title With Options"
p
.title.align =
"right"
p
.title.text_color =
"orange"
p
.title.text_font_size =
"25px"
p
.title.background_fill_color =
"#aaaaee"
output_file(
"title.html")
show(p)
Legends
import numpy as np
from bokeh
.plotting import output_file, show, figure
x = np
.linspace(
0,
4*np
.pi,
100)
y = np
.sin(
x)
output_file(
"legend.html")
p = figure()
p
.circle(
x,
y, legend=
"sin(x)")
p
.line(
x,
y, legend=
"sin(x)")
p
.line(
x,
2*
y, legend=
"2*sin(x)",
line_dash=[
4,
4], line_color=
"orange", line_width=
2)
p
.square(
x,
3*
y, legend=
"3*sin(x)", fill_color=None, line_color=
"green")
p
.line(
x,
3*
y, legend=
"3*sin(x)", line_color=
"green")
show(p)
Color Bars（颜色条）
import numpy
as np
from matplotlib.mlab
import bivariate_normal
from bokeh.plotting
import figure, output_file, show
from bokeh.models
import LogColorMapper, LogTicker, ColorBar
output_file(
'color_bar.html')
N =
100
X, Y = np.mgrid[-
3:
3:complex(
0, N), -
2:
2:complex(
0, N)]
Z1 = bivariate_normal(X, Y,
0.1,
0.2,
1.0,
1.0) + \
0.1 * bivariate_normal(X, Y,
1.0,
1.0,
0.0,
0.0)
image = Z1 *
1e6
color_mapper = LogColorMapper(palette=
"Viridis256", low=
1, high=
1e7)
plot = figure(x_range=(
0,
1), y_range=(
0,
1), toolbar_location=
None)
plot.image(image=[image], color_mapper=color_mapper,
dh=[
1.0], dw=[
1.0], x=[
0], y=[
0])
color_bar = ColorBar(color_mapper=color_mapper, ticker=LogTicker(),
label_standoff=
12, border_line_color=
None, location=(
0,
0))
plot.add_layout(color_bar,
'right')
show(plot)
Arrows（箭头）
from bokeh.plotting import figure, output_file,
show
from bokeh.models import Arrow, OpenHead, NormalHead, VeeHead
output_file("arrow.html", title="arrow.py example")
p = figure(plot_width=600, plot_height=600)
p.circle(x=[0, 1, 0.5], y=[0, 0, 0.7], radius=0.1,
color=["navy", "yellow", "red"], fill_alpha=0.1)
p.add_layout(Arrow(end=OpenHead(line_color="firebrick", line_width=4),
x_start=0, y_start=0, x_end=1, y_end=0))
p.add_layout(Arrow(end=NormalHead(fill_color="orange"),
x_start=1, y_start=0, x_end=0.5, y_end=0.7))
p.add_layout(Arrow(end=VeeHead(size=35), line_color="red",
x_start=0.5, y_start=0.7, x_end=0, y_end=0))
show(p)
Bands
A Band will create a dimensionally-linked “stripe”, either located in data or screen coordinates.
Box Annotations
A BoxAnnotation can be linked to either data or screen coordinates in order to emphasize specific plot regions.
Labels
Labels are text elements that can be used to annotate either glyphs or plot regions.
Spans
Span annotations are lines that have a single dimension (width or height) and extend to the edge of the plot area.
Whiskers
A Whisker will create a dimensionally-linked “stem”, either located in data or screen coordinates.
