398. Random Pick Index

本文介绍了一个算法问题的解决方案:给定一个可能包含重复元素的整数数组和一个目标值,随机返回目标值的一个索引。该算法使用了随机化的思想来确保每次选择的索引具有相同的概率。

摘要生成于 C知道 ,由 DeepSeek-R1 满血版支持, 前往体验 >

Given an array of integers with possible duplicates, randomly output the index of a given target number. You can assume that the given target number must exist in the array.

Note:
The array size can be very large. Solution that uses too much extra space will not pass the judge.

Example:

int[] nums = new int[] {1,2,3,3,3};
Solution solution = new Solution(nums);

// pick(3) should return either index 2, 3, or 4 randomly. Each index should have equal probability of returning.
solution.pick(3);

// pick(1) should return 0. Since in the array only nums[0] is equal to 1.
solution.pick(1);

思路:
给了一个数组,包含若干数,可能有重复,然后再给一个数,查找其位置,如果这个数在数组中只出现了一次就返回那个位置,如果不止一次就随机返回一个。

class Solution {

    private int[] nums;
    private Random random;

    public Solution(int[] nums) {
        this.nums = nums;
        this.random = new Random();
    }

    public int pick(int target) {
        int result = -1;
        int upbound = 1;
        for (int i = 0; i < nums.length; i++) {
            if (nums[i] == target) {
                if (random.nextInt(upbound) == 0) {
                    result = i;
                } 
                upbound++;
            }
        }
        return result;
    }
}

/**
 * Your Solution object will be instantiated and called as such:
 * Solution obj = new Solution(nums);
 * int param_1 = obj.pick(target);
 */
def spatially_regular_gen(): # Generator loop for i in range(num_per_epoch): # Choose the cloud with the lowest probability cloud_idx = int(np.argmin(self.min_possibility[split])) # choose the point with the minimum of possibility in the cloud as query point point_ind = np.argmin(self.possibility[split][cloud_idx]) # Get all points within the cloud from tree structure points = np.array(self.input_trees[split][cloud_idx].data, copy=False) # Center point of input region center_point = points[point_ind, :].reshape(1, -1) # Add noise to the center point noise = np.random.normal(scale=cfg.noise_init / 10, size=center_point.shape) pick_point = center_point + noise.astype(center_point.dtype) # Check if the number of points in the selected cloud is less than the predefined num_points if len(points) < cfg.num_points: # Query all points within the cloud queried_idx = self.input_trees[split][cloud_idx].query(pick_point, k=len(points))[1][0] else: # Query the predefined number of points queried_idx = self.input_trees[split][cloud_idx].query(pick_point, k=cfg.num_points)[1][0] # Shuffle index queried_idx = DP.shuffle_idx(queried_idx) # Get corresponding points and colors based on the index queried_pc_xyz = points[queried_idx] queried_pc_xyz = queried_pc_xyz - pick_point queried_pc_colors = self.input_colors[split][cloud_idx][queried_idx] queried_pc_labels = self.input_labels[split][cloud_idx][queried_idx] # Update the possibility of the selected points dists = np.sum(np.square((points[queried_idx] - pick_po
04-04
将以下代码转换为python:function newpop=zmutate(pop,popsize,pm1,pm2,fitness1,M,N,Tn0,Tn1,Q,ST0,maxT,t,maxgen,LCR,ECR,MCR,FC,ICR) %M为辅助坑道数量;N为单元数 x=pop(:,1:2*M+1);%分段点位置 y=pop(:,2*M+2:4*M+2);%是否选择该分段点 z=pop(:,4*M+3:6*M+4);%开挖方向 W=pop(:,6*M+5:8*M+6);%作业班次 lenx=length(x(1,:)); leny=length(y(1,:)); lenz=length(z(1,:)); lenW=length(W(1,:)); avefit=sum(fitness1)/popsize; worstfit=min(fitness1); % sumy=sum(y); % lenz=sumy+1; % lenW=sumy+1; for i=1:popsize %选择popsize次,每次选择一个,输出一个 %随机选择一个染色体 pick=rand; while pick==0 pick=rand; end index=ceil(pick*popsize); f1=fitness1(index); if f1<=avefit % pm=(exp(-t/maxgen))*(pm1-(pm1-pm2)*(f1-avefit)/max(fitness1)-avefit); pm=1/(1+exp(t/maxgen))*(pm1-(pm1-pm2)*(f1-avefit)/max(fitness1)-avefit); else % pm=(exp(-t/maxgen))*pm1; pm=1/(1+exp(t/maxgen))*pm1; end pick=rand; while pick==0 pick=rand; end if pick>pm continue; end % flag0=0; % while(flag0==0) %随机选择变异位置 pick1=rand; pick2=rand; pick3=rand; pick4=rand; while pick1*pick2*pick3*pick4==0 pick1=rand; pick2=rand; pick3=rand; pick4=rand; end posx=ceil(pick1*lenx); posy=ceil(pick2*leny); %x,y变异 randx=randi([1,N-1]); while ismember(randx,x(index,:)) randx=randi([1,N-1]); end b=x(index,posx); x(index,posx)=randx; a=[0 1]; c=y(index,posy); y(index,posy)=setxor(y(index,posy),a); %z,W变异 posz=ceil(pick3*lenz); posW=ceil(pick4*lenW); d=z(index,posz); z(index,posz)=setxor(z(index,posz),a); randW=randi([1,3]); while randW==W(index,posW) randW=randi([1,3]); end e=W(index,posW); W(index,posW)=randW; mpop=[x(index,:),y(index,:),z(index,:),W(index,:)]; mtime=ztime(mpop,M,N,Tn0,Tn1,Q,ST0); mutfit=zcost(mpop,M,N,mtime(:,1),mtime(:,2:2*M+3),mtime(:,2*M+4:2*M+2+N),LCR,ECR,MCR,FC,ICR,Q); if mtime(:,1)>maxT||mutfit<=worstfit x(index,posx)=b; y(index,posy)=c; z(index,posz)=d; W(index,posW)=e; end end newpop=[x,y,z,W]; end
05-26
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值