<｜begin▁of▁sentence｜>### Instruction:
As a wildlife biologist specializing in the study of animal behavior and ecology, you've been tasked with analyzing the social networks within a population of 100 animals in a particular habitat. To do this, you plan to use a mathematical model called the NMFADMM, which stands for Non-Negative Matrix Factorization with the Beta-Divergence. This model, outlined in a paper presented at the ICASSP ‘14 conference, can help you extract meaningful patterns from complex networks.

Your specific task involves analyzing the social connections among the animals, which you've represented as an Erdős-Rényi graph. In this graph, each node represents an animal, and there's a connection between any pair of animals with a probability of 0.05.

Now, your goal is to employ the NMFADMM model to obtain an embedding of this animal social network. This embedding will provide a condensed representation of the network's structure, allowing you to identify key individuals, social clusters, and other relevant patterns in the animal population's social dynamics.
### Response:
import networkx as nx
from karateclub import NMFADMM

# Create a networkx graph
G = nx.erdos_renyi_graph(100, 0.05)

# Initialize NMFADMM model
model = NMFADMM(dimensions=32, iterations=100, rho=1.0, seed=42)

# Fit the model
model.fit(G)

# Get the embedding
embedding = model.get_embedding()

print(embedding)
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