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

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AAS on 4 Sep 2020
Commented: Steven Lord on 5 Sep 2020
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.

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Adam Danz on 4 Sep 2020
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 on 4 Sep 2020
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 on 4 Sep 2020
This can be done.....attach your data.

Adam Danz on 4 Sep 2020
Edited: Adam Danz on 4 Sep 2020
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

#### 1 Comment

AAS on 5 Sep 2020
Thank you very much!!

Steven Lord on 4 Sep 2020
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 on 4 Sep 2020
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 on 5 Sep 2020
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.

R2018a

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