Is there any way to get a matrix from data set which contains x position, y position and magnitude?

I would like to generate a 2D matrix with rows being x position and y being y position and the matrix should be filled with magnitude at the points where it is detected. Sprry for the naive question. I do not have magnitudes at every points so some of the entries should be blank in the matrix.

[Rafael Hernandez-Walls]

I do not have magnitudes at every points so some of the entries should be blank in the matrix (put in this part: NaN).

[Adam Danz]

Please provide examples of the x,y position data and the magnitudes.

For example, are they all vectors? Are x and y vectors while the magnitudes are a matrix? Are there any duplicate (x,y) values?

[AAS]

X and Y are just position values and there is an additional value at each position. There can be duplicate X and Y values.

I basically have a set of points which has 3 components (x, y, magnitude). There can be many points that have x and y value but could have different magnitudes (maybe in this case, I can average them and input that into the matrix)

[KSSV]

This can be done.....attach your data.

Answer 1

[Adam Danz]

Inputs are x, y, and m, which are your (x,y) coordinates and magnitudes, all the same length.

Outputs are magMat and T. The former is a matrix of mean magnitudes for each (x,y) coordinate where rows are the unique y values (yUnq) and columns are the unique x values (xUnq). The later is the same data displayed in a table.

% Create demo data
rng('default')
x = randi(8,1,20)-4; 
y = randi(6,1,20)-3; 
m = randi(10, 1,20); %magnitudes

% discretize magnitude values into unique (x,y) groups
[xyGroup, ~, xyID] = unique([x(:),y(:)], 'rows'); 
% Compute mean of each (x,y) group
magMean = accumarray(xyID, m, [size(xyGroup,1),1], @mean); 

% Create magnitude matrix where columns are unique 
% x values and rows are unique y values
xUnq = unique(x); 
yUnq = unique(y); 

magMat = nan(numel(yUnq), numel(xUnq)); 
[~, col] =  ismember(xyGroup(:,1), xUnq); 
[~, row] =  ismember(xyGroup(:,2), yUnq); 

ind = sub2ind(size(magMat), row, col); 
magMat(ind) = magMean;

% summarize results in table
T = array2table(magMat, 'VariableNames', compose('x=%.1g',xUnq), 'RowNames', compose('y=%.1g',yUnq));
% T =
%   6×8 table
%             x=-3    x=-2    x=-1    x=0    x=1    x=2    x=3     x=4  
%             ____    ____    ____    ___    ___    ___    ___    ______
%     y=-2    NaN     NaN     NaN       2    NaN    NaN      2    4.6667
%     y=-1    NaN     NaN     NaN     NaN    NaN    NaN    NaN    6.3333
%     y=0     NaN     NaN     NaN     NaN      7    NaN    NaN       NaN
%     y=1     NaN     NaN     NaN     NaN    NaN    NaN      5         8
%     y=2       5       4       5      10    NaN      2    NaN       NaN
%     y=3     NaN       8     NaN     NaN    NaN    NaN      6         8

[AAS]

Thank you very much!!

Answer 2

[Steven Lord]

Use either accumarray or sparse if the X and Y coordinates are positive integer values.

>> rng default
>> x = randi(4, 6, 1);
>> y = randi(4, 6, 1);
>> v = (1:6).';
>> coords = table(x, y, v)
>> A = accumarray([x, y], v, [4 4])

Since I called rng default you should have generated the same x and y as I did. This means you should see that two values in v, 3 and 6, are at the same coordinates (1, 4). Therefore A(1, 4) is 3+6 = 9.

The [4, 4] in the accumarray call ensures A would be a 4-by-4 matrix even if there were no entry in the 4th row or 4th column.

accumarray([1 1; 2 2; 3 3], [1; 1; 1]) % 3-by-3
accumarray([1 1; 2 2; 3 3], [1; 1; 1], [4 4]) % 4-by-4

[AAS]

If they arent positive integer values, is there any alternate way (Can we convert these X and Y values to some form of indices?) because what you have here is exactly what I need.

Thanks

[Steven Lord]

discretize your coordinates and use the bin numbers or see the "Unique Values and Their Indices" example on the documentation page for the unique function. The uniquetol function may also be of use.