<｜begin▁of▁sentence｜>### Instruction:
As an Intercultural Trainer, imagine you're assisting a group of professionals from diverse backgrounds in improving their communication skills for a multinational project. They're using NetworkX, a tool for visualizing networks, to map out their collaboration dynamics. However, they're encountering difficulty in managing the placement of edge labels on their graph. They want to ensure that the labels don't overlap with the edges themselves, as this could lead to confusion.

They've asked for guidance on creating a custom Matplotlib edge drawer to address this issue. This involves specifying the position of the edge labels in a way that minimizes overlap with the edges while still maintaining clarity in the visualization. By implementing this solution, they aim to enhance their ability to analyze and interpret the network dynamics, fostering smoother communication and collaboration across cultural boundaries.
### Response:
import matplotlib.pyplot as plt
import networkx as nx

class CustomMatplotlibEdgeDrawer(nx.drawing.nx_pylab.EdgeDrawer):
    def get_label_position(self, edge, label_pos):
        # In this custom edge drawer, we override the default label position
        x_start, y_start = self._pos[edge[0]]
        x_end, y_end = self._pos[edge[1]]
        # Midpoint calculation
        mid_x = (x_start + x_end) / 2.0
        mid_y = (y_start + y_end) / 2.0
        # The default alignment is to avoid overlapping the label with the edge
        alignment = ('center', 'center')
        return (mid_x, mid_y), alignment

# Assuming we have a NetworkX graph
G = nx.Graph()
G.add_edges_from([(1, 2), (2, 3), (3, 4)])
pos = nx.spring_layout(G)

# Plot the graph using our custom edge drawer
ax = plt.gca()
drawer = CustomMatplotlibEdgeDrawer(G, pos, ax=ax)
for edge in G.edges():
    label_pos, align = drawer.get_label_position(edge, 'center')
    # Draw the edge label
    ax.text(label_pos[0], label_pos[1], str(edge),
            horizontalalignment=align[0], verticalalignment=align[1])

nx.draw(G, pos, ax=ax)
plt.show()
<|EOT|>
