Datasets:

EnjunDu
/

GraphMaster

import json

def clean_graph_data(input_file, output_file):
    """
    Clean graph data by removing nodes with mask="None", ensuring sequential node_ids,
    and updating all neighbor references accordingly.
    """
    # Load the JSON data
    with open(input_file, 'r', encoding='utf-8') as f:
        data = json.load(f)
    
    # Identify valid nodes (mask != "None") and their IDs
    valid_nodes = []
    valid_node_ids = set()
    
    for node in data:
        if 'mask' in node and node['mask'] != "None":
            valid_nodes.append(node)
            valid_node_ids.add(node['node_id'])
    
    # Create mapping from old node_id to new node_id
    old_to_new_mapping = {}
    new_id = 0
    
    for node in sorted(valid_nodes, key=lambda x: x['node_id']):
        old_to_new_mapping[node['node_id']] = new_id
        new_id += 1
    
    # Update node_ids and neighbors based on the mapping
    for node in valid_nodes:
        # Update neighbors first (while node_id is still the old one)
        new_neighbors = []
        for neighbor in node['neighbors']:
            if neighbor in valid_node_ids:  # Only keep neighbors that weren't removed
                new_neighbors.append(old_to_new_mapping[neighbor])
        node['neighbors'] = new_neighbors
        
        # Update node_id
        node['node_id'] = old_to_new_mapping[node['node_id']]
    
    # Sort nodes by new node_id for better readability
    valid_nodes.sort(key=lambda x: x['node_id'])
    
    # Save the cleaned data
    with open(output_file, 'w') as f:
        json.dump(valid_nodes, f, indent=2)
    
    return f"Successfully cleaned the graph data. Removed {len(data) - len(valid_nodes)} nodes with mask='None'."

# Usage
result = clean_graph_data('wikics.json', 'wikics_cleaned.json')
print(result)

	import json

	def clean_graph_data(input_file, output_file):
	"""
	Clean graph data by removing nodes with mask="None", ensuring sequential node_ids,
	and updating all neighbor references accordingly.
	"""
	# Load the JSON data
	with open(input_file, 'r', encoding='utf-8') as f:
	data = json.load(f)

	# Identify valid nodes (mask != "None") and their IDs
	valid_nodes = []
	valid_node_ids = set()

	for node in data:
	if 'mask' in node and node['mask'] != "None":
	valid_nodes.append(node)
	valid_node_ids.add(node['node_id'])

	# Create mapping from old node_id to new node_id
	old_to_new_mapping = {}
	new_id = 0

	for node in sorted(valid_nodes, key=lambda x: x['node_id']):
	old_to_new_mapping[node['node_id']] = new_id
	new_id += 1

	# Update node_ids and neighbors based on the mapping
	for node in valid_nodes:
	# Update neighbors first (while node_id is still the old one)
	new_neighbors = []
	for neighbor in node['neighbors']:
	if neighbor in valid_node_ids: # Only keep neighbors that weren't removed
	new_neighbors.append(old_to_new_mapping[neighbor])
	node['neighbors'] = new_neighbors

	# Update node_id
	node['node_id'] = old_to_new_mapping[node['node_id']]

	# Sort nodes by new node_id for better readability
	valid_nodes.sort(key=lambda x: x['node_id'])

	# Save the cleaned data
	with open(output_file, 'w') as f:
	json.dump(valid_nodes, f, indent=2)

	return f"Successfully cleaned the graph data. Removed {len(data) - len(valid_nodes)} nodes with mask='None'."

	# Usage
	result = clean_graph_data('wikics.json', 'wikics_cleaned.json')
	print(result)