Add more tests

Author: BaseMax

test12.py

@@ -0,0 +1,33 @@
+import networkx as nx
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Create a random graph with 10,000 nodes and 50,000 edges
+G = nx.gnm_random_graph(1000, 5000)
+
+# Set random weights for the edges
+weights = np.random.rand(len(G.edges))
+nx.set_edge_attributes(G, dict(zip(G.edges, weights)), 'weight')
+
+# Generate a layout using the spring layout algorithm
+pos = nx.spring_layout(G)
+
+# Assign colors to the nodes based on their degree
+node_colors = np.array(list(dict(G.degree()).values()))
+node_colors = (node_colors - node_colors.min()) / (node_colors.max() - node_colors.min())
+
+# Assign colors to the edges based on their weight
+edge_weights = nx.get_edge_attributes(G, 'weight')
+edge_weights_norm = (np.array(list(edge_weights.values())) - min(edge_weights.values())) / (max(edge_weights.values()) - min(edge_weights.values()))
+cmap = plt.cm.get_cmap('Blues')
+edge_colors = cmap(edge_weights_norm)
+
+# Draw the graph using the layout and color scheme
+nx.draw(G, pos=pos, node_color=node_colors, edge_color=edge_colors, with_labels=False, node_size=5, width=0.5)
+
+# Add a title and subtitle to the plot
+plt.title("Random Graph with 10,000 Nodes and 50,000 Edges")
+plt.suptitle("Generated using the gnm_random_graph() function from NetworkX")
+
+# Display the plot
+plt.show()

test13.py

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+import networkx as nx
+import matplotlib.pyplot as plt
+
+# Create a random graph with 50 nodes
+G = nx.fast_gnp_random_graph(50, 0.2)
+
+# Generate a layout using the spring layout algorithm
+pos = nx.spring_layout(G)
+
+# Draw the graph using the layout and default settings
+nx.draw(G, pos)
+
+# Add a title to the plot
+plt.suptitle("Generated using the fast_gnp_random_graph() function from NetworkX", fontsize=12)
+
+# Display the plot
+plt.show()