<｜begin▁of▁sentence｜>### Instruction:
Imagine we're in the tactical operations center mapping out strategies for emergency response. We have two separate command hierarchies — let's call them Team Alpha Tree (T1) and Team Bravo Tree (T2), each representing a structured chain of command. These are organized just like a fire team would be, efficiently balanced for quick action, and we have their structures laid out in our system.

We need to create a unified incident command system by bringing Team Alpha Tree and Team Bravo Tree together. This would be like establishing a new incident command post where both teams report to one central commander. To do this, we’re looking to employ a tactic similar to merging command structures, albeit using our digital tools. 

How can the operation room's planning software use the no longer supported 'join' function in NetworkX to approach this? We'd be creating a new digital command tree with a fresh root that oversees both Team Alpha and Team Bravo's existing trees. It's critical to make sure this new command tree accurately reflects the singular oversight without losing any of the existing balance and hierarchy. If our structural data were stored in a GML file format, we'd need to mention the file name to properly import it into NetworkX before performing the merge. 

How can we simulate this unified command structure while keeping the integrity of our teams' balanced hierarchy intact, using the outdated tools we have at our disposal?
### Response:
import networkx as nx

# Create two separate trees
T1 = nx.balanced_tree(2, 3, create_using=nx.DiGraph)
T2 = nx.balanced_tree(2, 2, create_using=nx.DiGraph)

# Add a new root node
T1.add_node('new_root')

# Use the deprecated 'join' function (which is an alias for 'join_trees')
# to join T1 and T2 with the new root
T = nx.join('new_root', [T1, T2])
print(nx.info(T))
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