Additional question: 'If the water depth starts from 0.5 m or higher, make the 0 m part NaN and then compress the (depth) / (average salinity) values equally.' -> In this case, what command is needed to put NaN in place of 0 m? Should I use ?
How to compress data into numerical intervals
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I am trying to compress the water depth data from the given CTD.mat in the following manner.
pwd;
load('pwd\CTD.mat');
A = (1:22).';
for c = 1:21
for cc(c) = CTD.Depth{1, c}(1:end)
for A = 1:22
if cc(c) < 0.5
A = 1;
CTD.Depth2{1, c}(A) = 0;
elseif cc(c) < 1
A = 2;
CTD.Depth2{1, c}(A) = 0.5;
elseif cc(c) < 1.5
A = 3;
CTD.Depth2{1, c}(A) = 1;
elseif cc(c) < 2
A = 4;
CTD.Depth2{1, c}(A) = 1.5;
elseif cc(c) < 2.5
A = 5;
CTD.Depth2{1, c}(A) = 2;
elseif cc(c) < 3
A = 6;
CTD.Depth2{1, c}(A) = 2.5;
elseif cc(c) < 3.5
A = 7;
CTD.Depth2{1, c}(A) = 3
elseif cc(c) < 4
A = 8;
CTD.Depth2{1, c}(A) = 3.5
elseif cc(c) < 4.5
A = 9;
CTD.Depth2{1, c}(A) = 4
elseif cc(c) < 5
A = 10;
CTD.Depth2{1, c}(A) = 4.5
elseif cc(c) < 5.5
A = 11;
CTD.Depth2{1, c}(A) = 5
elseif cc(c) < 6
A = 12;
CTD.Depth2{1, c}(A) = 5.5
elseif cc(c) < 6.5
A = 13;
CTD.Depth2{1, c}(A) = 6
elseif cc(c) < 7
A = 14;
CTD.Depth2{1, c}(A) = 6.5
elseif cc(c) < 7.5
A = 15;
CTD.Depth2{1, c}(A) = 7
elseif cc(c) < 8
A = 16;
CTD.Depth2{1, c}(A) = 7.5
elseif cc(c) < 8.5
A = 17;
CTD.Depth2{1, c}(A) = 8
elseif cc(c) < 9
A = 18;
CTD.Depth2{1, c}(A) = 8.5
elseif cc(c) < 9.5
A = 19;
CTD.Depth2{1, c}(A) = 9
elseif cc(c) < 10
A = 20;
CTD.Depth2{1, c}(A) = 9.5
elseif cc(c) < 10.5
A = 21;
CTD.Depth2{1, c}(A) = 10
else
A = 22;
CTD.Depth2{1, c}(A) = 10.5
end
end
end
end
Please tell me how to fix this code. Also, I would like to compress the salinity data in CTD.mat like the right part of the given image file, can you explain how?
采纳的回答
Dyuman Joshi
2023-10-2
编辑:Dyuman Joshi
2023-10-2
Here's an approach -
%Load the data
load('CTD.mat');
arr = CTD.Depth;
n = numel(arr);
%Pre-allocate the variable in which the output is to be stored
CTD.Sal2 = cell(size(CTD.Sal));
for k=1:numel(arr)
vec = arr{1,k};
%Specify groups to sort data into
%For each set of data maximum value might be differ, so define the bins accordingly
m = ceil(max(vec)/0.5)*0.5;
bins = 0:0.5:m;
%Indices of data sorted according to groups defined
idx=discretize(vec,bins);
%Calculate the mean of the data corresponding to the group indices
CTD.Sal2{1,k} = accumarray(idx, CTD.Sal{1,k}, [], @mean);
end
%Check the value for the 1st array as shown in the image
disp(CTD.Sal2{1,1})
5 个评论
Dyuman Joshi
2023-10-2
For that, you can will have need some more manipulation.
Also, I have combined all the operations here -
load('CTD.mat');
arr = CTD.Depth;
n = numel(arr);
%Preallocation
CTD.Sal2 = cell(size(CTD.Sal));
CTD.Temp2 = cell(size(CTD.Temp));
CTD.Depth2 = cell(size(CTD.Depth));
%All commands in a single for loop
for k=1:numel(arr)
vec = arr{1,k};
m = ceil(max(vec)/0.5)*0.5;
bins = (0:0.5:m)';
idx=discretize(vec,bins);
CTD.Sal2{1,k} = accumarray(idx, CTD.Sal{1,k}, [], @mean, NaN);
CTD.Temp2{1,k} = accumarray(idx, CTD.Temp{1,k}, [], @mean, NaN);
CTD.Depth2{1,k} = sign(accumarray(idx, 1, [], [], NaN)).*bins(1:end-1);
end
disp(CTD.Sal2{1,1})
disp(CTD.Temp2{1,5})
disp(CTD.Depth2{1,5})
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