import time
import logging

from graphit import Graph
from graphit.graph_combinatorial.graph_setlike_operations import *

logging.basicConfig(level=logging.WARN)

# Build tutorial graph

graph1 = Graph(auto_nid=False)
graph1.add_nodes(range(1, 11), graph='one')
graph1.add_edges([(1, 2), (2, 3), (3, 4), (3, 5), (5, 6), (4, 7), (6, 8), (7, 8), (8, 9), (9, 10)])

graph2 = Graph(auto_nid=False)
graph2.add_nodes(range(6, 16), graph='two')
graph2.add_edges([(6, 8), (7, 8), (8, 9), (9, 10), (10, 11), (10, 12), (12, 13), (11, 14), (13, 15), (14, 15)])

print('Tutorial example graphs 1 and 2:', graph1, graph2)

Tutorial 5: Compairing, mergin and appending graphs

In this tutorial you will take a closer look at graphit function for operations on multiple grpahs such as compairing two graphs, joining or merging them.

5.1 Compairing subgraphs

graphit offers a number of set-like comparison methods to compare subgraphs based on topology defined by node IDs and edges. This means that the graphs at least need to share nodes with the same ID or derived from a common ancestor (origin graph).

These functions aim to return a view-based result graph whenever possible. The principles and benefits of ‘views’ are discussed in more detail in the the moderate1_graph_orm.ipynb tutorial. If returning a view is not possible a new (deep copy) will be returned.

Note: These functions do not update node and/or edge attributes in the resulting graph as might be required in for instance a union or intersection operation.

print('intersection: {0}'.format(graph_intersection(graph1, graph2)))
print('difference: {0}'.format(graph_difference(graph1, graph2)))
print('symmetric_difference: {0}'.format(graph_symmetric_difference(graph1, graph2)))
print('union: {0}'.format(graph_union(graph1, graph2)))

print('\nissubset: {0}'.format(graph_issubset(graph1.getnodes([3, 4, 5]), graph1)))
print('issuperset: {0}'.format(graph_issuperset(graph1, graph_union(graph1, graph2))))

The set-like operations demonstrated above are also used in Graph magic methods where they are often combined with attribute update functions to for instance return a true union between two graphs.

# Graph addition, attributes of first updated with second
new = graph1 + graph2
print(new.items('_id', 'graph'))

# Is graph 1 contained in the previous graph
print('Graph 1 contained in new:', graph1 in new)
print('Graph 1 not contained in graph 2:', graph1 in graph2)

# Equality
print('Graph 1 does not equal graph 2:', graph1 == graph2)
print('A copy of graph 1 equals graph 1:', graph1.copy() == graph1)

# Logical less-then/greater-then
print(graph1 <= new)