I have a challenge to order my matrix. The provided functions like sortrows work in the opposite way...
Take this 2D matrix
M =
40 45 68
50 65 58
60 55 48
57 67 44
,
The objective is to find matrix O that indicates the sorting index (rank) per row, i.e.:
O =
1 2 3
1 3 2
3 2 1
2 3 1
.
So for the second row 50 is the smallest element (1), 65 the largest (3), and 58 is the second largest (2), therefore row vector [1 3 2].
[~,sorted_inds] = sort(M,2);
will do.
I think you're looking for the second output of the regular sort function:
[~,I] = sort(M,2)
This syntax supresses the actual sorted matrix Msorted, and returns the indices I such that
for j = 1:n, Msorted(j,:) = M(I(j,:),j); end
Type doc sort for more information.
Related
Say I have a matrix, M:
9.89E+10 3.12E+10 29
8.88E+10 8.16E+10 9
9.97E+10 8.31E+10 22
8.10E+10 6.55E+10 94
2.17E+10 8.11E+09 53
6.34E+10 8.84E+10 54
5.69E+10 7.07E+10 8
9.23E+10 8.24E+10 38
8.88E+10 5.81E+10 27
And I have another array, A:
A=8.88E+10, 9.23E+10
I want all the entries in M that contain all the entries in A. That is, my output should be a matrix, N:
8.88E+10 8.16E+10 9
9.23E+10 8.24E+10 38
8.88E+10 5.81E+10 27
I can do this using a code like:
count=1;
for i=1:size(A,1)
for j=1:size(M,1)
if M(j,1)==A(i,1)
extracted(count,:)=M(j,:);
count=count+1;
end
end
end
But I guess there could be a one liner code in MATLAB to do this. Is there any?
One Liner Solution
N = M(sum(ismember(M,A),2)>0,:);
Explanation
The ismember function generates a binary matrix of the same size of M, which contains 1 for each value in M which exists in A and 0 otherwise.
We use sum function to sum each row in that matrix. rows which sum up to a value which is bigger than 0 are rows which contains values from A.
Last, we generate the out matrix by taking all the rows from M which fits to the constraint from previous stage.
Result
N =
8.88E+10 8.16E+10 9
9.23E+10 8.24E+10 38
8.88E+10 5.81E+10 27
I have a few multidimensional matrices of dimensions mxnxt, where each element in mxn is an individual sensor input, and t is time. What I want to do is analyse only the peak values for each element in mxn over t, so I would end up with a single 2D matrix of mxn containing only max values.
I know there are are ways to get a single overall max value, but is there a way to combine this with element-by-element operations like bsxfun so that it examines each individual element over t?
I'd be grateful for any help you can give because I'm really stuck at the moment. Thanks in advance!
Is this what you want?
out = max(A,[],3); %// checking maximum values in 3rd dimension
Example:
A = randi(50,3,3,3); %// Random 3x3x3 dim matrix
out = max(A,[],3);
Results:
A(:,:,1) =
35 5 8
38 12 42
23 46 27
A(:,:,2) =
50 6 39
4 49 41
23 1 44
A(:,:,3) =
5 41 10
20 22 14
13 46 8
>> out
out =
50 41 39
38 49 42
23 46 44
You can call max() with the matrix and select the dimension (look the documentation) on which the operation will be calculated, e.g
M = max(A,[],3)
I am a novice at Matlab and am struggling a bit with creating a loop that will a convert a 283080 x 2 matrix - column 1 lists all stockID numbers (each repeated 60 times) and column 2 contains all lagged monthly returns (60 observations for each stock) into a 60 x 4718 matrix with a column for each stockID and its corresponding lagged returns falling in 60 rows underneath each ID number.
My aim is to then try to calculate a variance-covariance matrix of the returns.
I believe I need a loop because I will be repeating this process over 70 times as I have multiple data sets in this same current format
Thanks so much for the help!
Let data denote your matrix. Then:
aux = sortrows(data,1); %// sort rows according to value in column 1
result = reshape(aux(:,2),60,[]); %// reshape second column as desired
If you need to insert the stockID values as headings (first row of result), add this as a last line:
result = [ unique(aux(:,1)).'; result ];
A simple example, replacing 60 by 2:
>> data = [1 100
2 200
1 101
2 201
4 55
3 0
3 33
4 56];
>> aux = sortrows(data,1);
>> result = reshape(aux(:,2),2,[])
>> result = [ unique(aux(:,1)).'; result ];
result =
1 2 3 4
100 200 0 55
101 201 33 56
This question is an outgrowth of MatLab (or any other language) to convert a matrix or a csv to put 2nd column values to the same row if 1st column value is the same?
If
A = [2 3 234 ; 2 44 33; 2 12 22; 3 123 99; 3 1232 45; 5 224 57]
1st column | 2nd column | 3rd column
2 3 234
2 44 33
2 12 22
3 123 99
3 1232 45
5 224 57
then running
[U ix iu] = unique(A(:,1) );
r= accumarray( iu, A(:,2:3), [], #(x) {x'} )
will show me the error
Error using accumarray
Second input VAL must be a vector with one element for each row in SUBS, or a
scalar.
I want to make
1st col | 2nd col | 3rd col | 4th col | 5th col | 6th col| 7th col
2 3 234 44 33 12 22
3 123 99 1232 45
5 224 57
I know how to do it using for and if, but that spends too much time for big data.
How can I do this?
Thank you in advance!
You're misusing accumarray in the solution provided to your previous question. The first parameter iu is the vector of indices and the second parameter should be a vector of values, of the same length. What you did here is specify a matrix as the second parameter, which in fact has twice more values than indices in iu.
What you need to do in order to make it work is create a vector of indices both for the second column and for the third column (they are the same indices, not coincidentally!) and specify a matching column vector of values, like so:
[U, ix, iu] = unique(A(:,1));
vals = reshape(A(:, 2:end).', [], 1); %'// Columnize values
subs = reshape(iu(:, ones(size(A, 2) - 1, 1)).', [], 1); %'// Replicate indices
r = accumarray(subs, vals, [], #(x){x'});
This solution is generalized for any number of columns that you want to pass to accumarray.
I want to calculate the sum of the elements surrounding a given element in a matrix. So far, I have written these lines of code:
for i=1:m,
rij(1:n)=0
for j=1:n,
alive = tijdelijk(i-1,j)+tijdelijk(i+1,j)+tijdelijk(i-1,j-1)+tijdelijk(i+1,j-1)+tijdelijk(i,j+1)+tijdelijk(i,j-1)+tijdelijk(i-1,j+1)+tijdelijk(i+1,j+1)
This results in an error because, for example, i-1 becomes zero for i=1. Anyone got an idea how to do this without getting this error?
You can sum the elements via filtering. conv2 can be used for this manner.
Let me give an example. I create a sample matrix
>> A = reshape(1:20, 4, 5)
A =
1 5 9 13 17
2 6 10 14 18
3 7 11 15 19
4 8 12 16 20
Then, I create a filter. The filter is like a mask where you put the center on the current cell and the locations corresponding to the 1's on the filter are summed. For eight-connected neighbor case, the filter should be as follows:
>> B = [1 1 1; 1 0 1; 1 1 1]
B =
1 1 1
1 0 1
1 1 1
Then, you simply convolve the matrix with this small matrix.
>> conv2(A, B, 'same')
ans =
13 28 48 68 45
22 48 80 112 78
27 56 88 120 83
18 37 57 77 50
If you want four-connected neighbors, you can make the corners of your filter 0. Similarly, you can design any filter for your purpose, such as for averaging all neighbors instead of summing them.
For details, please see the convolution article in Wikipedia.
Two possibilities : change the limits of the loops to i=k:(m-k) and j=k:(n-k) or use blkproc
ex :
compute the 2-D DCT of each 8-by-8 block
I = imread('cameraman.tif');
fun = #dct2;
J = blkproc(I,[8 8],fun);
imagesc(J), colormap(hot)
There are lots of things you can do at the edges. Which you do depends very specifically on your problem and is different from usage case to usage case. Typical things to do:
If (i-1) or (i+1) is out of range, then just ignore that element. This is equivalent to zero padding the matrix with zeros around the outside and adjusting the loop limits accordingly
Wrap around the edges. In other words, for an MxN matrix, if (i-1) takes you to 0 then instead of taking element (i-1, j) = (0, j) you take element (M, j).
Since your code mentions "your teacher" I'd guess that you can ask what should happen at the edges (or working it out in a sensible manner may well be part of the task!!).