Covert a cell with the same indices into individual matrices

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MarshallSc
MarshallSc 2021-7-7
评论： MarshallSc 2021-7-7
Hello, does anyone how I can convert a 10*10 cell array that each contains a 4*4 matrix into individual matrices. For example considering the code below:
x1 = rand(10,10);
y1 = rand(10,10);
z1 = rand(10,10);
r1 = rand(10,10);
a1 = cat(3,x1,y1,z1,r1);
x2 = rand(10,10);
y2 = rand(10,10);
z2 = rand(10,10);
r2 = rand(10,10);
a2 = cat(4,x2,y2,z2,r2);
tmp = num2cell(sqrt(a1./a2),3:4);
fun = @(a)reshape(a,4,4);
out = cellfun(fun,tmp,'uni',0);
What I'm looking to do is to convert each components of the cell with the same index into a seperate matrix, so that at the end I would have 16 seperate 10*10 matrices. For example considering all the (1,1) of the cells (out{1}(1,1), out{2}(1,1), out{3}(1,1), ...). Can one for loop be used to this conversion that at the end 16 different 10*10 matrices will be produced? Or is it better to change the method to calculate the result of the above code (out) from the beginning so that the matrices are obtained themselves? Thank you.

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Stephen23
Stephen23 2021-7-7
Ran in:
It is not clear to me why you need to split the numeric data into 100 4x4 matrices, just to recombine the numeric data into 16 10x10 matrices. Why not skip the middle entirely, and go straight to the 16 10x10 matrices?
x1 = rand(10,10);
y1 = rand(10,10);
z1 = rand(10,10);
r1 = rand(10,10);
a1 = cat(3,x1,y1,z1,r1);
x2 = rand(10,10);
y2 = rand(10,10);
z2 = rand(10,10);
r2 = rand(10,10);
a2 = cat(4,x2,y2,z2,r2);
out2 = reshape(num2cell(sqrt(a1./a2),1:2),4,4) % <- try this
out2 = 4×4 cell array
{10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double} {10×10 double}
cmp2 = out2{4,1} % for comparison
cmp2 = 10×10
2.9656 0.7360 0.9425 1.2257 0.4062 1.3241 0.8456 0.8951 1.8988 1.1643 0.8959 0.8702 2.7521 2.4620 1.2179 1.2658 1.2211 0.7416 1.2571 1.7134 2.3034 1.2035 1.2259 1.4452 0.8945 1.5588 1.6855 1.0448 0.3416 1.0999 0.6387 0.7931 0.3847 1.1504 1.3599 0.9472 0.9657 0.7773 2.4375 0.4988 12.2880 1.0568 0.3826 1.0354 0.3258 2.1765 0.4227 0.9767 0.5842 0.8154 3.5563 1.5147 1.8729 0.8701 0.8464 0.5248 3.8636 1.4231 0.5179 0.3991 1.0273 1.6911 1.0084 1.0902 1.1016 0.8318 1.2163 1.4484 0.9842 0.7283 5.0321 1.3926 0.9870 0.6820 1.3326 1.2969 1.0028 0.7557 0.4904 1.8180 0.9030 1.1801 1.0515 0.4170 1.5448 1.3636 0.5483 0.2722 0.1757 0.7456 0.2963 1.1006 0.6940 1.9821 0.7103 1.0029 0.3302 1.2735 1.1195 1.0808
Comparing against your very indirect approach:
tmp = num2cell(sqrt(a1./a2),3:4);
fun = @(a)reshape(a,4,4);
out1 = cellfun(fun,tmp,'uni',0)
out1 = 10×10 cell array
{4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double} {4×4 double}
cmp1 = cellfun(@(m)m(4,1),out1) % for comparison
cmp1 = 10×10
2.9656 0.7360 0.9425 1.2257 0.4062 1.3241 0.8456 0.8951 1.8988 1.1643 0.8959 0.8702 2.7521 2.4620 1.2179 1.2658 1.2211 0.7416 1.2571 1.7134 2.3034 1.2035 1.2259 1.4452 0.8945 1.5588 1.6855 1.0448 0.3416 1.0999 0.6387 0.7931 0.3847 1.1504 1.3599 0.9472 0.9657 0.7773 2.4375 0.4988 12.2880 1.0568 0.3826 1.0354 0.3258 2.1765 0.4227 0.9767 0.5842 0.8154 3.5563 1.5147 1.8729 0.8701 0.8464 0.5248 3.8636 1.4231 0.5179 0.3991 1.0273 1.6911 1.0084 1.0902 1.1016 0.8318 1.2163 1.4484 0.9842 0.7283 5.0321 1.3926 0.9870 0.6820 1.3326 1.2969 1.0028 0.7557 0.4904 1.8180 0.9030 1.1801 1.0515 0.4170 1.5448 1.3636 0.5483 0.2722 0.1757 0.7456 0.2963 1.1006 0.6940 1.9821 0.7103 1.0029 0.3302 1.2735 1.1195 1.0808
isequal(cmp1,cmp2)
ans = logical
1
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Stephen23
Stephen23 2021-7-7
编辑：Stephen23 2021-7-7
Ran in:
"Also, the output of out2 is givng me a 4*4 cell array, shouldn't be a 16*16 cell array..."
You have a sum total of
10*10*4*4
ans = 1600
numeric elements (arranged in 100 4x4 matrices). If we divide those elements into 10x10 matrices, then you will have 16 said matrices... which can be arranged in a 4x4 cell array. It is not clear how you want to duplicate/interpolate/extrapolate/whatever 1600 numeric elements in order to get
10*10*16*16
ans = 25600
numeric elements.
"...(the result that I'm looking to get)?"
The result you requested was "...at the end 16 different 10*10 matrices will be produced...".
As far as I am aware, 4x4 == 16.

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