Compare the chord diagram of two similar matrix inputs

[TomHsiung]

import openchord as ocd import numpy as np matrix = [ [2, 1, 0, 1, 1], [0, 29, 3, 18, 15], [0, 100, 0, 1, 0], [3, 22, 0, 15, 10], [7, 15, 1, 5, 9] ] labels = ['Danger', 'Optimal', 'Over', 'Suboptimal', 'Under'] fig = ocd.Chord(matrix, labels) fig.gradient_style = "default" fig.arc_thickness = 0.05 fig.gap_size = 0.05 fig.ribbon_stiffness = 0.6 fig.radius = 300 fig.plot_area = {"x": -750, "y": -500, "w": 2000, "h": 2000}

fig.colormap = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880']

fig.save_svg("/Users/tomhsiung/chord_diagram.svg")`

This makes a chord diagram of,

Notice the relationship between category 'Over' and 'Optimal'. Next, lets change the cell number of column 3 row 2 from 3 to 0.

import openchord as ocd import numpy as np matrix = [ [2, 1, 0, 1, 1], [0, 29, 0, 18, 15], [0, 100, 0, 1, 0], [3, 22, 0, 15, 10], [7, 15, 1, 5, 9] ] labels = ['Danger', 'Optimal', 'Over', 'Suboptimal', 'Under'] fig = ocd.Chord(matrix, labels) fig.gradient_style = "default" fig.arc_thickness = 0.05 fig.gap_size = 0.05 fig.ribbon_stiffness = 0.6 fig.radius = 300 fig.plot_area = {"x": -750, "y": -500, "w": 2000, "h": 2000}

fig.colormap = ['#636EFA', '#EF553B', '#00CC96', '#AB63FA', '#FFA15A', '#19D3F3', '#FF6692', '#B6E880']

fig.save_svg("/Users/tomhsiung/chord_diagram.svg")

Then, we have this new chord diagram with a large portion of blank.

The difference between the two matrices is that the first matrix has a bilateral flow between category 'Over' and 'Optimal'. The second matrix, in contrast, only has unilateral flow from 'Optimal' to 'Over'. This blank is difficult to interpret for those who are not familiar with chord diagram.