<｜begin▁of▁sentence｜>### Instruction:
Given a graph where nodes have a 'color' attribute with values 'red', 'green', or 'blue', and edges have a 'weight' attribute representing their weight, how can you construct an attribute matrix that represents the sum of edge weights between nodes of specific colors? Assuming the edge set of the graph is [('red', 'blue', 2), ('red', 'green', 1), ('green', 'blue', 3), ('red', 'red', 4)], what would be the resulting attribute matrix and the color order?
### Response:
import networkx as nx

# Create a graph
G = nx.Graph()
G.add_edge('red', 'blue', weight=2)
G.add_edge('red', 'green', weight=1)
G.add_edge('green', 'blue', weight=3)
G.add_edge('red', 'red', weight=4)

# Define node colors
nx.set_node_attributes(G, {'red': 'red', 'green': 'green', 'blue': 'blue'}, 'color')

# Compute attribute matrix for edge weights
M, color_order = nx.attr_matrix(G, edge_attr='weight', node_attr='color')
print("Attribute matrix:\n", M)
print("Color order:", color_order)
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