findOldestRecord,findTallestMan 考虑在创建对象或变量时使用initialize前缀 美式的initialize应优于英式的initialise。避免缩写init。 initializeProblemState 使用前缀is命名布尔函数 这是MathWorks代码和其他语言中的常见做法。 isOverpriced,iscomplete 在某些情况下有一些替代is前缀的方法更适合。这些前缀包括has,can和should。
MATLAB Online에서 열기 Dear MATLAB Users, I am trying to fill in the empty array using a recursive formula. The formula is shown as follows: (This expression is the base case for resursive function) For all In this formula, I already know theBarray which is ...
[a,b]ans = 1×4 cell array {[1]} {'f'} {'q'} {[5]} 您还可以使用函数形式cat,在该函数形式中,您可以选择要连接的维度: >> cat(3,a,b) 1×2×2 cell arrayans(:,:,1) = {[1]} {'f'}ans(:,:,2) = {'q'} {[5]} 要附加单个元素,可以执行a=[a,{1}],但这不是很有效...
elseif choose==3 %用FCM算法进行初始化 options=[NaN, NaN, NaN, 0]; [~, responsivity]=fcm(data, K, options); %用FCM算法求出隶属度矩阵 [~, label]=max(responsivity', [], 2); elseif choose==4 label = litekmeans(data, K,'Replicates',20); endlitekmeans.m1...
In this first example, we create a vectorvwith elements ranging from1to5. We then initialize an arraycumulativeSumwith zeros to store the cumulative sums. Next, using aforloop, we iterate through each element of the vector, progressively calculating the cumulative sum up to the current index ...
1、文件的打开与关闭 1）打开文件 在读写文件之前，必须先用fopen函数打开或创建文件，并指定对该...
circularities = NaN(size(B,1),1);% initialize circularities array to NaN forj = 1:size(B,1) boundary = B{j}; objectMask = poly2mask(boundary(:,2), boundary(:,1), size(AI,1), size(AI,2)); regionProps = regionprops(objectMask,'Area'...
You can use isnan() to identify nan locations and then build a cell array with nulls there. If m is your matrix (untested code): [rows, columns] = size(m); nanLocations = isnan(m); ca = cell(rows, columns);% Initialize cell array. ...
para_miu=data(rand_array(1:K), :); %随机排列取前K个数,在X矩阵中取这K行作为初始聚类中心 %欧氏距离,计算(X-para_miu)^2=X^2+para_miu^2-2*X*para_miu',矩阵大小为X_num*K distant=repmat(sum(data.*data,2),1,K)+repmat(sum(para_miu.*para_miu,2)',X_num,1)-2*data*para_miu...
0 링크 번역 댓글:William Dickie2019년 12월 9일 채택된 답변:Raunak Gupta What I am trying to do is associate the y1 value with an SSP(:,2) value depending upon its relationship to SSP(:,1) 's depth.