New translations graph_synthesizer.py (Chinese Simplified)

lang/zh/gklearn/utils/graph_synthesizer.py

@@ -0,0 +1,53 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Fri Sep 11 18:10:06 2020
+
+@author: ljia
+"""
+import numpy as np
+import networkx as nx
+import random
+
+
+class GraphSynthesizer(object):
+	
+	
+	def __init__(self):
+		pass
+	
+	
+	def random_graph(self, num_nodes, num_edges, num_node_labels=0, num_edge_labels=0, seed=None, directed=False, max_num_edges=None, all_edges=None):
+		g = nx.Graph()
+		if num_node_labels > 0:
+			node_labels = np.random.randint(0, high=num_node_labels, size=num_nodes)
+			for i in range(0, num_nodes):
+				g.add_node(str(i), atom=node_labels[i]) # @todo: update "atom".
+		else:
+			for i in range(0, num_nodes):
+				g.add_node(str(i))
+
+		if num_edge_labels > 0:
+			edge_labels = np.random.randint(0, high=num_edge_labels, size=num_edges)				
+			for idx, i in enumerate(random.sample(range(0, max_num_edges), num_edges)):
+				node1, node2 = all_edges[i]
+				g.add_edge(str(node1), str(node2), bond_type=edge_labels[idx])  # @todo: update "bond_type".
+		else:
+			for i in random.sample(range(0, max_num_edges), num_edges):
+				node1, node2 = all_edges[i]
+				g.add_edge(str(node1), str(node2))
+		
+		return g
+	
+	
+	def unified_graphs(self, num_graphs=1000, num_nodes=20, num_edges=40, num_node_labels=0, num_edge_labels=0, seed=None, directed=False):
+		max_num_edges = int((num_nodes - 1) * num_nodes / 2)
+		if num_edges > max_num_edges:
+			raise Exception('Too many edges.')
+		all_edges = [(i, j) for i in range(0, num_nodes) for j in range(i + 1, num_nodes)] # @todo: optimize. No directed graphs.
+			
+		graphs = []
+		for idx in range(0, num_graphs):		
+			graphs.append(self.random_graph(num_nodes, num_edges, num_node_labels=num_node_labels, num_edge_labels=num_edge_labels, seed=seed, directed=directed, max_num_edges=max_num_edges, all_edges=all_edges))
+			
+		return graphs