Python中的 bokeh.plotting.figure.bezier()函数

Bokeh是Python中的数据可视化库，提供高性能的交互式图表和绘图，输出可以在笔记本、html 和服务器等各种媒体中获得。 Figure 类创建一个用于绘图的新 Figure。它是 Plot 的子类，使用默认轴、网格、工具等简化绘图创建。

bokeh.plotting.figure.bezier()函数

bokeh 库的绘图模块中的bezier()函数用于配置和添加 Bezier 字形到这个图中。

Syntax: bezier(x0, y0, x1, y1, cx0, cy0, cx1, cy1, *, line_alpha=1.0, line_cap=’butt’, line_color=’black’, line_dash=[], line_dash_offset=0, line_join=’bevel’, line_width=1, name=None, tags=[], **kwargs)

Parameters: This method accept the following parameters that are described below:

x0: This parameter is the x-coordinates of the starting points.
y0: This parameter is the y-coordinates of the starting points.
x1: This parameter is the x-coordinates of the ending points.
y1: This parameter is the y-coordinates of the ending points.
cx0: This parameter is the x-coordinates of the first control points.
cy0: This parameter is the y-coordinates of the first control points.
cx1: This parameter is the x-coordinates of the second control points.
cy1: This parameter is the y-coordinates of the second control points.
line_alpha: This parameter is the line alpha values for the steps with default value of 1.0 .
line_cap: This parameter is the line cap values for the steps with default value of butt.
line_color: This parameter is the line color values for the steps with default value of black.
line_dash: This parameter is the line dash values for the steps with default value of [].
line_dash_offset: This parameter is the line dash offset values for the steps with default value of 0.
line_join: This parameter is the line join values for the steps with default value of bevel.
line_width: This parameter is the line width values for the steps with default value of 1.
mode: This parameter can be one of three values : [“before”, “after”, “center”].
name: This parameter is the user-supplied name for this model.
tags: This parameter is the user-supplied values for this model.

Other Parameters: These parameters are **kwargs that are described below:

alpha: This parameter is used to set all alpha keyword arguments at once.
color: This parameter is used to to set all color keyword arguments at once.
legend_field: This parameter is the name of a column in the data source that should be used or the grouping.
legend_group: This parameter is the name of a column in the data source that should be used or the grouping.
legend_label: This parameter is the legend entry is labeled with exactly the text supplied here.
muted: This parameter contains the bool value.
name: This parameter is the optional user-supplied name to attach to the renderer.
source: This parameter is the user-supplied data source.
view: This parameter is the view for filtering the data source.
visible: This parameter contains the bool value.
x_range_name: This parameter is the name of an extra range to use for mapping x-coordinates.
y_range_name: This parameter is the name of an extra range to use for mapping y-coordinates.
level: This parameter specify the render level order for this glyph.

Return: This method return the GlyphRenderer value.

编程需要懂一点英语

下面的示例说明了 bokeh.plotting 中的 bokeh.plotting.figure.bezier()函数：
示例 1：

# Implementation of bokeh function
   
import numpy as np 
from bokeh.plotting import figure, output_file, show
  
plot = figure(plot_width = 300, plot_height = 300)
  
plot.bezier(x0 =[1, 2, 3], y0 =[3, 2, 1], 
            x1 =[1.4, 2.3, 3.5], y1 =[3.4, 2.3, 1.5], 
            cx0 =[1.4, 2.3, 3.5], cy0 =[3.4, 2.3, 1.5],
            cx1 =[.4, 1.3, 2.5], cy1 =[2.4, 1.3, .5],
            color ="green", alpha = 0.6, line_width = 3)
   
show(plot)

输出：

示例 2：

# Implementation of bokeh function
   
import numpy as np 
from bokeh.plotting import figure, output_file, show
   
N = 9
x = np.linspace(-2, 2, N)
y = x**2
  
xp02 = x + 0.4
xp01 = x + 0.1
xm01 = x-0.1
yp01 = y + 0.2
ym01 = y-0.2
  
plot = figure(plot_width = 300, plot_height = 300)
  
plot.bezier(x0 = x, y0 = y,
            x1 = xp02, y1 = y,
            cx0 = xp01, cy0 = yp01,
            cx1 = xm01, cy1 = ym01, 
            color ="green", alpha = 0.6,
            line_width = 3)
   
show(plot)

输出：