DotMotif is a library that identifies subgraphs or motifs in a large graph. It looks like this:

# Look for all motifs of the form,

# Neuron A excites B:
A -> B [type = "excitatory"]
# ...and B inhibits C:
B -> C [type = "inhibitory"]

Or like this:

TwitterInfluencer(person) {
    # An influencer has more than a million
    # followers and is verified.
    person.followers > 1000000
    person.verified = true

InfluencerAwkward(person1, person2) {
    # Two people who are both influencers...
    # ...where one follows the other, but...
    person1 -> person2
    # ...the other doesn't follow back
    person2 !> person1

# Search for all awkward twitter influencer
# relationships in the dataset:
InfluencerAwkward(X, Y)

Get Started

To follow along in an interactive Binder without installing anything, launch a Jupyter Notebook here:


If you have DotMotif, a NetworkX graph, and a curious mind, you already have everything you need to start using DotMotif:

from dotmotif import Motif, GrandIsoExecutor

executor = GrandIsoExecutor(graph=my_networkx_graph)

triangle = Motif("""
A -> B
B -> C
C -> A

results = executor.find(triangle)


You can also pass optional parameters into the constructor for the dotmotif object. Those arguments are:

Argument Type, Default Behavior
ignore_direction bool: False Whether to disregard direction when generating the database query
limit int: None A limit (if any) to impose on the query results
enforce_inequality bool: False Whether to enforce inequality; in other words, whether two nodes should be permitted to be aliases for the same node. For example, in A->B->C; if A!=C, then set to True
exclude_automorphisms bool: False Whether to return only a single example for each detected automorphism. See more in the documentation

For more details on how to write a query, see Getting Started.