[英]A nested loop with variable number of loops
I have a function that outputs a matrix in a new basis. 我有一个以新的方式输出矩阵的函数。 However, depending on the size of the matrix the number of basis matrix differ.
但是,根据矩阵的大小,基础矩阵的数量不同。 So in simplified "Matlab pseudo code":
所以在简化的“Matlab伪代码”中:
if matrixsize==1
for a1=1:4
out(a1)=Matrix*basis(a1)
end
elseif matrixsize==2
for a1=1:4
for a2=a1:4
out(a1,a2)=Matrix*basis(a1)*basis(a2)
end
end
elseif matrixsize==3
for a1=1:4
for a2=a1:4
for a3=a2:4
out(a1,a2,a3)=Matrix*basis(a1)*basis(a2)*basis(a3)
end
end
end
elseif ...
and so on 等等
Is it possible to write this code, for any value of matrix size? 对于矩阵大小的任何值,是否可以编写此代码? In other words: Is it possible to create a loop that automatically creates the loops above?
换句话说:是否可以创建一个自动创建上述循环的循环? If this does not work in Matlab, is there maybe a solution in Python?
如果这在Matlab中不起作用,那么Python中可能有一个解决方案吗?
(Background: This question comes from quantum physics, where I want to write a quantum state in the Pauli basis) (背景:这个问题来自量子物理学,我想在保利基础上写一个量子态)
Here is a working Matlab code that shows the problem: 这是一个工作的Matlab代码,显示了问题:
function T=newbasis(n)
%create a random matrix
m=2^n;
M=randn(m);
%Pauli matrices
s{1}=sparse([1,0;0,1]);
s{2}=sparse([0,1;1,0]);
s{3}=sparse([0,-1i;1i,0]);
s{4}=sparse([1,0;0,-1]);
if n==1
for a1=1:4
T(a1)=trace(M*betterkron(s{a1}));
end
elseif n==2
for a1=1:4
for a2=a1:4
T(a1,a2)=trace(M*betterkron(s{a1},s{a2}));
end
end
elseif n==3
for a1=1:4
for a2=a1:4
for a3=a2:4
T(a1,a2,a3)=trace(M*betterkron(s{a1},s{a2},s{a3}));
end
end
end
else
T=[]
end
%Not very clever but just to keep it simple
function krn=betterkron(A,varargin)
krn = A;
for j = 2:nargin;
krn = kron(krn,varargin{j-1});
end
end
end
Although it is possible in principle to do multiple loops like this with a recursive function, it will be complicated. 虽然原则上可以用递归函数做这样的多个循环,但它会很复杂。 Luckily using multiple loops isn't the best way to do it.
幸运的是,使用多个循环并不是最好的方法。 MATLAB lets you convert back and forth between N-dimensional subscripts and 1-dimensional linear indices.
MATLAB允许您在N维下标和1维线性索引之间来回转换。 So you can do a single loop over the linear indices, then convert back to N-dimensional subscripts.
因此,您可以对线性索引执行单个循环,然后转换回N维下标。 So something like this:
所以像这样:
for i=1:numel(Matrix) % loop over linear index
inds = ind2sub(size(Matrix), i); % convert linear index to subscript
% Each index should be greater than or equal to the previous
% e.g. a2=a1:4, a2 starts at a1 so cannot be less than a1
if any(diff(inds) < 0)
continue
end
% Do the calculation
% s{inds} is equivalent to s{i1}, s{i2}, ...
T(i) = trace(M*betterkron(s{inds}));
end
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