我正在开发一个有限元程序,其中我的输入是节点(ListNodes double[node_index, x, y, z]
的列表,其中(x,y,z)
是笛卡尔系统中节点的坐标),元素的列表是(ListElements double[element_index, node1_index, node2_index, etc])
以及每个元素(double[element_index])
的一些数据。
我必须在有限元模型中的某个给定区域上恒定地搜索数据,该区域由某个绑定的[xmin, xmax, ymin, ymax, zmin, zmax]
定义。为了检索该区域的数据,我首先查找其节点(搜索(x,y,z)
在边界内的节点),然后查找其元素,最后检索该元素的数据。
功能1:检查节点是否在区域内
private static bool IsBounded(double[] node, double xmin, double ymin, double zmin, double xmax, double ymax, double zmax)
{
return ((node[1] >= xmin) && (node[1] <= xmax) && (node[2] >= ymin) && (node[2] <= ymax) && (node[3] >= zmin) && (node[3] <= zmax));
}
功能2:检查所有节点以查找区域内的节点并将其添加到zoneNodes
ListPoint.Where(node => IsBounded(node, xmin, ymin, zmin, xmax, ymax, zmax)).ToList().ForEach(node => zoneNodes.Add(Convert.ToInt32(node[0])));
功能3:在区域内查找元素
// Loop over all elements
for (int j = 0; j < ListElement.Count; j++)
{
int status = 0;
for (int i = 1; i < ElementList[j].Count; i++)
{
// For each element, check how many nodes are inside the zone
if (zoneNodes.Contains(Convert.ToInt32(ListElement[j][i])))
{
status++;
}
}
// If all the nodes of this element are inside the zone then the element is inside the zone
if (status == ListElement[j].Count - 1)
{
zoneElements.Add(Convert.ToInt32(ElementList[j][0]));
}
}
功能4:然后,对于区域内的每个元素,我们都可以检索数据
但是,此过程非常缓慢。有什么方法可以改善此过程以获得更快的性能?
谢谢
答案 0 :(得分:0)
我不确定此代码是否是您想要的。
请退房。
减少词典计算时间的主要事情是使用字典。
字典的时间复杂度通常为O(1)。
public class Sample
{
// add data to that variables.
System.Collections.Generic.Dictionary<double, Point> pointPerElement = new System.Collections.Generic.Dictionary<double, Point>();
System.Collections.Generic.Dictionary<double, Cube> cubePerElement = new System.Collections.Generic.Dictionary<double, Cube>();
System.Collections.Generic.List<double> elements = new System.Collections.Generic.List<double>();
private void Calculate()
{
foreach (var element in elements)
{
if (pointPerElement.ContainsKey(element) == false || cubePerElement.ContainsKey(element) == false)
{
continue;
}
var point = pointPerElement[element];
var cube = cubePerElement[element];
if (cube.IsBouded(point))
{
// add point or cube or element to list.
}
}
}
}
private struct Point
{
public double x;
public double y;
public double z;
public Point(double x, double y, double z)
{
this.x = x;
this.y = y;
this.z = z;
}
public static Point GetVector(Point from, Point to)
{
return new Point(to.x - from.x, to.y - from.y, to.z - from.z);
}
}
private struct Range
{
public double min;
public double max;
public double length;
public double center;
public Range(double min, double max)
{
System.Diagnostics.Debug.Assert(min < max);
this.min = min;
this.max = max;
this.length = max - min;
this.center = length * 0.5;
}
}
private struct Cube
{
public Range xRange;
public Range yRange;
public Range zRange;
private Point center;
public Cube(Range xRange, Range yRange, Range zRange)
{
this.xRange = xRange;
this.yRange = yRange;
this.zRange = zRange;
this.center = new Point(xRange.center, yRange.center, zRange.center);
}
public bool IsBouded(Point point)
{
var v = Point.GetVector(point, this.center);
var doubledV = new Point(v.x * 2, v.y * 2, v.z * 2);
return doubledV.x <= this.xRange.length
&& doubledV.y <= this.yRange.length
&& doubledV.z <= this.yRange.length;
}
}