Python Bokeh – Plotting Hexagon Tiles 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 hexagon tiles on a graph. Plotting hexagon tiles on a graph can be done using the hex_tile() method of the plotting module.

plotting.figure.hex_tile()

Syntax : hex_tile(parameters)

Parameters :

q : column axial coordinates of the center of the hexagon tiles

r : row axial coordinates of the center of the hexagon tiles

aspect_scale : aspect scale value, default is 1

fill_alpha : fill alpha value of the hexagon tile markers

fill_color : fill color value of the hexagon tile 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

orientation : orientation value, default is pointytop

scale : scale factor of individual tiles, default is 1

size : radius of the hexagonal tiles, default is 1

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. We have provided the size and fill_color attributes to make the glyph visible.

# 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 Hexagon Tiles Graph", 
               match_aspect = True)  
     
# the points to be plotted  
r = [0, 0, 1]  
q = [1, 2, 2]  
    
# plotting the graph  
graph.hex_tile(r, q)  
     
# displaying the model  
show(graph)  

Output :

Example 2 : In this example we will be plotting the hexagon tiles with various 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 Hexagon Tiles Graph", 
               match_aspect = True)  
  
# 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  
r = [0, -1,  0,  1, -1, 0, 1] 
q = [0,  0, -1, -1,  1, 1, 0]  
  
# fill color values 
fill_color = ["yellow", "blue", "pink", "green", "orange", "red", "purple"] 
  
# line color values 
line_color = ["yellow", "blue", "pink", "green", "orange", "red", "purple"] 
  
# plotting the graph  
graph.hex_tile(r, q, 
               fill_color = fill_color, 
               line_color = line_color)  
     
# displaying the model  
show(graph)  