Help with storing data in a 4-D double matrix

I have a data set in the form of 8 columns. I have attached a dummy xlsx file to show the data structure.

As it can be seen, the data set includes [time, frequency, idx, node number, V1, V2, V3, V4]. I'm trying to sort and store these in a way such that I can access V3 values of a particular frequency and of a particular time. Purpose is to be able to access V3 values of a given time/frequency.

What I thought of the structure was something like this.

Re_vx = zeros(length(node_no), 2, length(time), length(frequency));

So I get a matrix in the form of (node_no, V3, time_set, freq_set).

How can I go about this? TIA!

Answer 1

[Voss]

How about storing that data set as a table:

t = readtable('new1.xlsx');
t = renamevars(t,t.Properties.VariableNames, ...
    {'time','frequency','idx','node_no','V1','V2','V3','V4'})

t = 144×8 table
     time     frequency    idx    node_no       V1           V2          V3           V4   
    ______    _________    ___    _______    _________    ________    _________    ________

    1.0472       0.1        1        1          0.2377     0.26627      0.75846     0.31877
    1.0472       0.1        1        2         0.60871     0.54889      0.64385    0.088389
    1.0472       0.1        1        3         0.82648     0.45033      0.38874     0.16956
    1.0472       0.1        1        4         0.29342     0.23107      0.64533     0.44209
    1.0472       0.1        1        5         0.26534     0.34716    0.0031364       0.681
    1.0472       0.1        1        6         0.75924     0.93866      0.36407     0.27537
    1.0472       0.1        1        7       0.0079028     0.33617     0.036416     0.19378
    1.0472       0.1        1        8         0.46993     0.47571      0.86852     0.35832
    1.0472       0.1        1        9         0.44592     0.90444       0.2673     0.30641
    1.0472       0.1        1       10         0.84343     0.07228      0.19927     0.94522
    1.0472       0.1        1       11         0.44459    0.078301      0.37323     0.12497
    1.0472       0.1        1       12         0.94596     0.50363      0.71822     0.21068
    1.0472       0.2        1        1         0.58522     0.48479      0.26291     0.72812
    1.0472       0.2        1        2         0.83658     0.77427      0.60219     0.23663
    1.0472       0.2        1        3         0.44332      0.1263      0.62431    0.057136
    1.0472       0.2        1        4         0.11618     0.84017      0.84411      0.1615

And using logical indexing to get the values at a particular time and frequency:

my_time = t.time(15)

my_time = 1.0472

my_freq = t.frequency(15)

my_freq = 0.2000

result = t(t.time == my_time & t.frequency == my_freq,:)

result = 12×8 table
     time     frequency    idx    node_no       V1          V2         V3          V4   
    ______    _________    ___    _______    ________    ________    _______    ________

    1.0472       0.2        1        1        0.58522     0.48479    0.26291     0.72812
    1.0472       0.2        1        2        0.83658     0.77427    0.60219     0.23663
    1.0472       0.2        1        3        0.44332      0.1263    0.62431    0.057136
    1.0472       0.2        1        4        0.11618     0.84017    0.84411      0.1615
    1.0472       0.2        1        5         0.1831     0.86732    0.65839     0.53164
    1.0472       0.2        1        6       0.090321    0.091064    0.64369     0.63566
    1.0472       0.2        1        7        0.24416     0.29224    0.88131     0.76682
    1.0472       0.2        1        8        0.54519     0.64255    0.87907     0.47458
    1.0472       0.2        1        9        0.10051     0.85658    0.65277     0.45944
    1.0472       0.2        1       10        0.87678    0.076611    0.94155     0.34647
    1.0472       0.2        1       11        0.59088     0.54855     0.5428     0.99147
    1.0472       0.2        1       12        0.31276     0.83399    0.76469      0.8957

result.V3

ans = 12×1

0.2629 0.6022 0.6243 0.8441 0.6584 0.6437 0.8813 0.8791 0.6528 0.9416

[Jake]

Thank you for the response, Voss. This works when I know the specific time or a frequency that I need the V3 values of. But I wanted to get these sorted in a way that I can access them rather easily. For example, say I want to access the V3 values of frequency f1, f2, f3 but within the time t1. If I had the desired matrix (following the dummy image I attached above), those would be val(:,:,1,1), val(:,:,2,1), val(:,:,3,1).

Also, my dataset is pretty large too :( Anyway, thank you so much for the response.

EDIT:

I realized my comment and the question I posted have some contradicting points. What I wanted is to store the values in a matrix in the form of (node_no, V3, time_set, freq_set). So, if I want to get all the V3 values of the 1st time period I can access it simply by Re_vx(:,:,1,:), or at least that's what I imagined. There should be more efficient or better ways to achieve this, and I appreciate any suggestion! :)