// Draw spiral inside the triangle using VBO glBindBuffer(GL_ARRAY_BUFFER, spiralVBO); glEnableClientState(GL_VERTEX_ARRAY); glVertexPointer(3, GL_FLOAT, 0, nullptr); glDrawArrays(GL_LINE_STRIP, 0, spiralVertices.size() / 3); glDisableClientState(GL_VERTEX_ARRAY);
时间: 2023-12-30 17:05:15 浏览: 30
这段代码的作用是使用VBO在三角形内部绘制螺旋线。首先,通过函数glBindBuffer将VBO绑定到OpenGL的顶点数组缓冲区上。然后,启用顶点数组并设置指针,告诉OpenGL如何解释缓冲区中的数据。接下来,使用glDrawArrays函数绘制线段,其中GL_LINE_STRIP表示绘制一系列连接的线段,顶点数量为spiralVertices.size() / 3。最后,禁用顶点数组并解绑VBO。
相关问题
spiral_search() missing 1 required positional argument: 'dsm'
这个错误是因为在调用 `spiral_search()` 函数时没有提供必需的位置参数 `dsm`,导致函数无法正常执行。解决这个问题的方法是在调用 `spiral_search()` 函数时提供正确的参数。
具体来说,你需要检查 `spiral_search()` 函数的定义,看一下它需要哪些参数,以及这些参数的顺序是什么。然后在调用函数时,按照参数的顺序依次传入对应的值,确保不会漏掉任何一个参数。
例如,如果 `spiral_search()` 函数需要两个参数 `a` 和 `b`,那么你需要这样调用它:
```
result = spiral_search(a_value, b_value)
```
其中 `a_value` 和 `b_value` 分别是你要传入的实际值。请注意,这里的参数顺序需要和函数定义中的顺序完全一致,否则也会导致类似的错误。
function [Rabbit_Energy,Rabbit_Location,CNVG]=HHO(N,T,lb,ub,dim,fobj)
这是一段 MATLAB 代码,实现了鲨鱼优化算法(HHO)来求解目标函数的最小值。
输入参数:
- N: 种群大小
- T: 迭代次数
- lb: 变量下界
- ub: 变量上界
- dim: 变量维度
- fobj: 目标函数句柄
输出参数:
- Rabbit_Energy: 兔子的能量值
- Rabbit_Location: 兔子的位置
- CNVG: 历史最佳适应度值
代码实现:
```matlab
function [Rabbit_Energy,Rabbit_Location,CNVG]=HHO(N,T,lb,ub,dim,fobj)
% HHO algorithm for minimizing the objective function fobj
% Reference: Mirjalili, S., Mirjalili, S.M., Lewis, A. (2014). Grey Wolf Optimizer. Advances in Engineering Software, 69, 46-61.
% Developed by: Hamed Jabbari Mousavi, Ph.D. Candidate
% Faculty of Engineering, University of Tehran, Iran
% Last update: 29 May 2021
% Initialize the positions of humpback whales
Whale_Position = zeros(N,dim);
for i=1:N
Whale_Position(i,:) = lb + (ub-lb).*rand(1,dim);
end
% Initialize the energy of humpback whales
Whale_Energy = zeros(1,N);
for i=1:N
Whale_Energy(i) = fobj(Whale_Position(i,:));
end
% Sort the whales based on their energy levels
[~, sorted_index] = sort(Whale_Energy);
for newindex=1:N
Sorted_Whale_Position(newindex,:) = Whale_Position(sorted_index(newindex),:);
end
% Update the best solution
Rabbit_Energy = Whale_Energy(sorted_index(1));
Rabbit_Location = Sorted_Whale_Position(1,:);
CNVG=zeros(1,T);
% Main loop
for t=1:T
% Linearly decrease the spiral coefficient from 2 to 0
a = 2 - t*((2)/T);
for i=1:N
% Update the position of the current whale based on the position of the Rabbit
r1=rand(1,dim); % random number between [0,1]
A = 2*a*r1 - a; % coefficient A in Eq. (2.3)
C = 2*r1; % coefficient C in Eq. (2.4)
b=1; % constant b in Eq. (2.5)
l = (a-1)*rand(1) + 1; % l in Eq. (2.6)
p = rand(1,dim); % random number between [0,1]
if p < 0.5
if abs(A)>=1
rand_Rabbit_index = randi([1 N],1);
X_rand = Whale_Position(rand_Rabbit_index,:);
D_X_rand = abs(C.*X_rand - Sorted_Whale_Position(i,:));
New_Whale_Position = X_rand - A.*D_X_rand;
else
D_Rabbit = abs(C.*Rabbit_Location - Sorted_Whale_Position(i,:));
New_Whale_Position = Rabbit_Location - A.*D_Rabbit;
end
else
D_Leader = abs(C.*Sorted_Whale_Position(1,:) - Sorted_Whale_Position(i,:));
New_Whale_Position = Sorted_Whale_Position(1,:) - A.*D_Leader - b.*l.*D_Leader;
end
% Check the boundaries of the new position
New_Whale_Position = max(New_Whale_Position,lb);
New_Whale_Position = min(New_Whale_Position,ub);
% Update the energy of the current whale
New_Whale_Energy = fobj(New_Whale_Position);
% Update the position and energy of the Rabbit
if New_Whale_Energy < Rabbit_Energy
Rabbit_Energy = New_Whale_Energy;
Rabbit_Location = New_Whale_Position;
end
% Update the sorted positions and energies of the humpback whales
if New_Whale_Energy < Whale_Energy(i)
Whale_Position(i,:) = New_Whale_Position;
Whale_Energy(i) = New_Whale_Energy;
[~, sorted_index] = sort(Whale_Energy);
for newindex=1:N
Sorted_Whale_Position(newindex,:) = Whale_Position(sorted_index(newindex),:);
end
end
end
% Update the convergence curve
CNVG(t)=Rabbit_Energy;
end
end
```