Python Bokeh – Plotting Inverted Triangles on a Graph

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Bokeh is a Python interactive data visualization. It renders its plots using HTML and JavaScript. It targets modern web browsers for presentation providing elegant, concise construction of novel graphics with high-performance interactivity.

Bokeh can be used to plot inverted triangles on a graph. Plotting inverted triangles on a graph can be done using the inverted_triangle() method of the plotting module.

plotting.figure.inverted_triangle()

Syntax : inverted_triangle(parameters)

Parameters :

x : x-coordinates of the center of the inverted triangle markers

y : y-coordinates of the center of the inverted triangle markers

size : diameter of the inverted triangle markers, default is 4

angle : angle of rotation of the inverted triangle markers, default is 0

angle_units : unit of the angle, default is rad

fill_alpha : fill alpha value of the inverted triangle markers

fill_color : fill color value of the inverted triangle markers

line_alpha : percentage value of line alpha, default is 1

line_cap : value of line cap for the line, default is butt

line_color : color of the line, default is black

line_dash : value of line dash such as :

solid

dashed

dotted

dotdash

dashdot

default is solid

line_dash_offset : value of line dash offset, default is 0

line_join : value of line join, default in bevel

line_width : value of the width of the line, default is 1

name : user-supplied name for the model

tags : user-supplied values for the model

Other Parameters :

alpha : sets all alpha keyword arguments at once

color : sets all color keyword arguments at once

legend_field : name of a column in the data source that should be used

legend_group : name of a column in the data source that should be used

legend_label : labels the legend entry

muted : determines whether the glyph should be rendered as muted or not, default is False

name : optional user-supplied name to attach to the renderer

source : user-supplied data source

view : view for filtering the data source

visible : determines whether the glyph should be rendered or not, default is True

x_range_name : name of an extra range to use for mapping x-coordinates

y_range_name : name of an extra range to use for mapping y-coordinates

level : specifies the render level order for this glyph

Returns : an object of class GlyphRenderer

Example 1 : In this example we will be using the default values for plotting the graph.

# importing the modules  
from bokeh.plotting import figure, output_file, show  
       
# file to save the model  
output_file("gfg.html")  
       
# instantiating the figure object  
graph = figure(title = "Bokeh Inverted Triangle Graph")  
     
# the points to be plotted  
x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]  
y = [i ** 2 for i in x]  
    
# plotting the graph  
graph.inverted_triangle(x, y)  
     
# displaying the model  
show(graph)  

Output :

Example 2 : In this example we will be plotting the inverted triangles where the sizes are in proportion to their values and various other parameters

# importing the modules  
from bokeh.plotting import figure, output_file, show  
       
# file to save the model  
output_file("gfg.html")  
       
# instantiating the figure object  
graph = figure(title = "Bokeh Inverted Triangle Graph")  
     
# name of the x-axis  
graph.xaxis.axis_label = "x-axis"
      
# name of the y-axis  
graph.yaxis.axis_label = "y-axis"
     
# the points to be plotted  
x = [-5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5]  
y = [i ** 2 for i in x]  
     
# size of the diamonds  
size = [i * 2 for i in y]  
     
# angle of the diamonds  
angle = 10
    
# fill color value  
fill_color = "yellow"
    
# color of the line  
line_color = "red"
    
# name of the legend  
legend_label = "Sample Triangles"
      
# plotting the graph  
graph.inverted_triangle(x, y, 
                        size = size,  
                        angle = angle,  
                        fill_color = fill_color,  
                        line_color = line_color,  
                        legend_label = legend_label)  
       
# displaying the model  
show(graph) 