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在Matlab中使用循环创建矩阵

[英]Creating Matrix with a loop in Matlab

I want to create a matrix of the following form 我想创建以下形式的矩阵

    Y = [1 x x.^2 x.^3 x.^4 x.^5 ... x.^100]

Let x be a column vector. 令x为列向量。 or even some more variants such as 甚至更多的变体,例如

    Y = [1 x1 x2 x3 (x1).^2 (x2).^2 (x3).^2 (x1.x2) (x2.x3) (x3.x1)]

Let x1,x2 and x3 be column vectors Let us consider the first one. 令x1,x2和x3为列向量让我们考虑第一个。 I tried using something like 我尝试使用类似

    Y = [1 : x : x.^100]

But this also didn't work because it means take Y = [1 x 2.*x 3.*x ... x.^100] ? 但这也不起作用,因为这意味着取Y = [1 x 2. * x 3. * x ... x。^ 100]吗? (ie all values between 1 to x.^100 with difference x) So, this also cannot be used to generate such a matrix. (即,所有1到x。^ 100之间的值都具有x差)因此,这也不能用于生成这样的矩阵。 Please consider x = [1; 请考虑x = [1; 2; 2; 3; 3; 4]; 4]; and suggest a way to generate this matrix 并提出一种生成该矩阵的方法

    Y = [1 1 1 1 1;
         1 2 4 8 16;
         1 3 9 27 81;
         1 4 16 64 256];

without manually having to write 无需手动编写

    Y = [ones(size(x,1)) x x.^2 x.^3 x.^4]

Use this bsxfun technique - 使用此bsxfun技术-

N = 5; %// Number of columns needed in output
x = [1; 2; 3; 4]; %// or [1:4]'
Y = bsxfun(@power,x,[0:N-1])

Output - 输出-

Y =
     1     1     1     1     1
     1     2     4     8    16
     1     3     9    27    81
     1     4    16    64   256

If you have x = [1 2; 3 4; 5 6] 如果x = [1 2; 3 4; 5 6] x = [1 2; 3 4; 5 6] x = [1 2; 3 4; 5 6] and you want Y = [1 1 1 2 4; 1 3 9 4 16; 1 5 25 6 36] x = [1 2; 3 4; 5 6]并且您希望Y = [1 1 1 2 4; 1 3 9 4 16; 1 5 25 6 36] Y = [1 1 1 2 4; 1 3 9 4 16; 1 5 25 6 36] Y = [1 1 1 2 4; 1 3 9 4 16; 1 5 25 6 36] ie Y = [ 1 x1 x1.^2 x2 x2.^2 ] for column vectors x1 , x2 ..., you can use this one-liner - Y = [1 1 1 2 4; 1 3 9 4 16; 1 5 25 6 36]Y = [ 1 x1 x1.^2 x2 x2.^2 ]对于列向量x1x2 ...,您可以使用这种单线-

[ones(size(x,1),1) reshape(bsxfun(@power,permute(x,[1 3 2]),1:2),size(x,1),[])]

Using an adapted Version of the code found in Matlabs vander()-Function (which is also to be found in the polyfit-function) one can get a significant speedup compared to Divakars nice and short solution if you use something like this: 使用Matlabs vander()-Function中找到的代码的改编版(也可以在polyfit-function中找到),与Divakars不错的简短解决方案相比,如果您使用以下代码,则可以显着提高速度:

N = 5;
x = [1:4]';
V(:,n+1) = ones(length(x),1);
for j = n:-1:1
   V(:,j) = x.*V(:,j+1);
end
V = V(:,end:-1:1);

It is about twice as fast for the example given and it gets about 20 times as fast if i set N=50 and x = [1:40]' . 对于给定的示例,它的速度大约是它的两倍,如果我将N=50设置N=50 x = [1:40]' ,它的速度大约是它的20倍。 Although I state that is not easy to compare the times, just as an option if speed is an issue, you might have a look at this solution. 尽管我说比较时间并不容易,但是如果速度是一个问题,可以选择一种解决方案。

in octave, broadcasting allows to write 以八度为单位,广播允许写

N=5;
x = [1; 2; 3; 4];
y = x.^(0:N-1)

output - 输出-

y =

     1     1     1     1     1
     1     2     4     8    16
     1     3     9    27    81
     1     4    16    64   256

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