我有以下代碼爲我的網絡擴散研究中的頂點建模輕量級框架。最初的原型是從Python中的框架,我翻譯成Java。我遇到的問題是,儘管此代碼運行速度比Python版本高達10000個頂點,但對於更多數量的頂點(100,000+)而言,它會停止運行。事實上,python版本在1.2分鐘內執行,而java版本即使在執行7分鐘後也不會返回。我不知道爲什麼相同的代碼在更多的頂點處崩潰,我需要幫助修復代碼。Java代碼執行時間問題
import java.util.*;
public class Vertex
{
private int id;
private HashMap<Integer, Double> connectedTo;
private int status;
public Vertex(int key)
{
this.id = key;
this.connectedTo = new HashMap<Integer, Double>();
this.status = 0;
}
public void addNeighbour(int nbr, double weight)
{
this.connectedTo.put(nbr, weight);
}
public int getId()
{
return this.id;
}
public double getWeight(int nbr)
{
return this.connectedTo.get(nbr);
}
public int getStatus()
{
return this.status;
}
public Set<Integer> getConnections()
{
return this.connectedTo.keySet();
}
//testing the class
public static void main(String[] args)
{
int noOfVertices = 100000;
Vertex[] vertexList = new Vertex[noOfVertices];
for (int i = 0; i < noOfVertices; i++) {
vertexList[i] = new Vertex(i);
}
for (Vertex v : vertexList) {
int degree = (int)(500*Math.random()); //random choice of degree
int neighbourCount = 0; // count number of neighbours built up
while (neighbourCount <= degree) {
int nbr = (int) (noOfVertices * Math.random()); // randomly choose a neighbour
double weight = Math.random(); // randomly assign a weight for the relationship
v.addNeighbour(nbr, weight);
neighbourCount++;
}
}
}
}
僅供參考,這段代碼的Python版本如下:
import random
class Vertex:
def __init__(self, key):
self.id = key
self.connectedTo = {}
def addNeighbor(self, nbr, weight=0):
self.connectedTo[nbr] = weight
def __str__(self):
return str(self.id) + ' connectedTo: ' \
+ str([x.id for x in self.connectedTo])
def getConnections(self):
return self.connectedTo.keys()
def getId(self):
return self.id
def getWeight(self, nbr):
return self.connectedTo[nbr]
if __name__ == '__main__':
numberOfVertices = 100000
vertexList = [Vertex(i) for i in range(numberOfVertices)] # list of vertices
for vertex in vertexList:
degree = 500*random.random()
# build up neighbors one by one
neighbourCount = 0
while neighbourCount <= degree:
neighbour = random.choice(range(numberOfVertices))
weight = random.random() # random choice of weight
vertex.addNeighbor(neighbour, weight)
neighbourCount = neighbourCount + 1
我目前正在研究此問題,並會盡快發佈一些優化代碼! –
如果沒有配置文件,不容易分辨,實際上幾乎可以在任何地方。只是一個快速點:看看有'nextInt(綁定)'方法的'java.util.Random'類(它不太可能是一個相當大的加速,但仍然)。 –
找到了解決方案並在下面發佈! –