Convert distance matrix to a table

How can I convert the output matrix Z to a table with the following structure?

Object1 Object2 Distance
1       2       0.2954
1       3       1.0670
2       1       0.2954
2       3       0.9448
3       1       1.0670
3       2       0.9448

Code:

rng('default') % For reproducibility
X = rand(3,2);
D = pdist(X)
Z = squareform(D)

[Adam Danz]

Your data do not produce the example.

Z =
            0       0.2954        1.067
       0.2954            0      0.94476
        1.067      0.94476            0

[dan kin]

I used rand.Maybe because of this?

[Adam Danz]

I set the RNG seed which should produce the same results. If you look carefully, you'll see that except for the 0s, the numbers in my Z are also in your example.

[dan kin]

The output I showed in my question is table I wish to generate

[Adam Danz]

I don't know how you produced the matrix but to convert it to a table, see my answer below. If you need help producing the matrix, you'll have to provide more info about it.

[Adam Danz]

Here's how to convert a matrix to a table and add column names.

m =[1       2       0.2954
    1       3       1.0670
    2       1       0.2954
    2       3       0.9448
    3       1       1.0670
    3       2       0.9448];
t = array2table(m,'VariableNames', {'Object1','Object2','Distance'})

[Akira Agata]

How about making a graph object?

rng('default') % For reproducibility
X = rand(3,2);
D = pdist(X);
Z = squareform(D);
G = graph(Z);

Then, G.Edges becomes almost what you want to obtain, like:

>> G.Edges
ans =
  3×2 table
    EndNodes    Weight 
    ________    _______
     1    2      0.2954
     1    3       1.067
     2    3     0.94476

Answer 1

[Akira Agata]

Or, if you want the full list of (from, to, distance) set, how about the following?

rng('default') % For reproducibility
X = rand(3,2);
D = pdist(X);
Z = squareform(D);

[row,col] = find(Z);
d = arrayfun(@(r,c) Z(r,c),row,col);

T = table(row,col,d,'VariableNames',{'Object1','Object2','Distance'});
T = sortrows(T);

The result is:

>> T
ans =
  6×3 table
    Object1    Object2    Distance
    _______    _______    ________
       1          2        0.2954 
       1          3         1.067 
       2          1        0.2954 
       2          3       0.94476 
       3          1         1.067 
       3          2       0.94476