Hasse Diagram

This small package helps with plotting Hasse Diagrams and is very useful when presenting results for the MCDA methods.

Installation

pip install hasse-diagram

Example usage

Networkx

import numpy as np
from hassediagram import plot_hasse

data = np.array([
    [0, 1, 1, 1, 1],
    [0, 0, 1, 0, 1],
    [0, 1, 0, 0, 1],
    [0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0]
])
labels = ["node a", "node b", "node c", "node d", "node e"]
plot_hasse(data, labels)

Result:

• Graphviz dotstring

import numpy as np
from hassediagram import hasse_graphviz

data = np.array([
    [0, 1, 1, 1, 1],
    [0, 0, 1, 0, 1],
    [0, 1, 0, 0, 1],
    [0, 0, 0, 0, 0],
    [0, 0, 0, 0, 0]
])
labels = ["node a", "node b", "node c", "node d", "node e"]
print(hasse_graphviz(data, labels))

Result:

digraph {
    graph [bgcolor="#FFFFFF"]
    node [color="#E2E8F0" fontname="Segoe UI" fontsize="15 pt" style=filled]
    edge [arrowhead=vee color=black]
    compound=true
    node1 [label="node a"]
    node2 [label="node b, node c"]
    node3 [label="node d"]
    node4 [label="node e"]
    node1 -> node2
    node1 -> node3
    node2 -> node4
    subgraph cluster_1 {
        rank=same
        peripheries=0
    }
    subgraph cluster_2 {
        rank=same
        node1
        peripheries=0
    }
    subgraph cluster_3 {
        rank=same
        node2
        node3
        peripheries=0
    }
    subgraph cluster_4 {
        rank=same
        node4
        peripheries=0
    }
}

You can optionally turn off the transitive reduction and change the color of nodes and edges.

Testing

pytest --cov=src --cov-report=term-missing

This package is inspired by a similar one for R: hasseDiagram