Vectorising nested for loops

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Melanie VT
Melanie VT 2023-3-10
移动：Stephen23 2023-3-11
Hi,
I’m trying to vectorise the following code snippet that works using the attached data. Unfortunately, I couldn’t succeed. Any ideas on how to deal with it?
Cheers,
Mel
k=0;
struct_data = struct('idx',[],'count',[],'size',[]);
for i = 1:size(table_data,1)
for j = 1:list(i)
k=k+1;
struct_data(k,1).idx = k;
struct_data(k,1).count = table_data.count(i);
struct_data(k,1).size = table_data.size(i);
end
end
  2 个评论
Stephen23
Stephen23 2023-3-10
Are you intentionally storing lots of scalar cell arrays containing character vectors, or is the intent to actually just store the character vectors without the superfluous scalar cell arrays? If you only need the text, replace
table_data.size(i);
with
table_data.size{i};
https://www.mathworks.com/help/matlab/matlab_prog/access-data-in-a-cell-array.html
Melanie VT
Melanie VT 2023-3-10
Thank you for your contribution!

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采纳的回答

Voss
Voss 2023-3-10
编辑：Voss 2023-3-10
Ran in:
% unzip and load data
unzip data.zip
load data.mat
% run the loop method, for later comparison
k=0;
struct_data = struct('idx',[],'count',[],'size',[]);
for i = 1:size(table_data,1)
for j = 1:list(i)
k=k+1;
struct_data(k,1).idx = k;
struct_data(k,1).count = table_data.count(i);
struct_data(k,1).size = table_data.size{i}; % note this change:
% I made struct_data(k).size a char, instead of
% a scalar cell array containing a char
end
end
struct_data_save = struct_data;
% a "vectorized" method
idx = find(list);
struct_data = table2struct(removevars(table_data(repelem(idx,list(idx)),:),'district'));
C = num2cell(1:numel(struct_data));
[struct_data.idx] = deal(C{:});
% are the results the same?
isequal(struct_data,struct_data_save)
ans = logical
1
  2 个评论
Voss
Voss 2023-3-10
编辑：Voss 2023-3-10
Ran in:
If you really want struct_data(k).size to be a 1x1 cell array containing a character vector (as in {'venti'}), as opposed to just a character vector (as in 'venti'), you can do it with a couple of additional lines of code:
% unzip and load data
unzip data.zip
load data.mat
% run the loop method, for later comparison
k=0;
struct_data = struct('idx',[],'count',[],'size',[]);
for i = 1:size(table_data,1)
for j = 1:list(i)
k=k+1;
struct_data(k,1).idx = k;
struct_data(k,1).count = table_data.count(i);
struct_data(k,1).size = table_data.size(i); % scalar cell array this time
end
end
struct_data_save = struct_data;
% a "vectorized" method
idx = find(list);
struct_data = table2struct(removevars(table_data(repelem(idx,list(idx)),:),'district'));
C = num2cell(1:numel(struct_data));
[struct_data.idx] = deal(C{:});
C = num2cell({struct_data.size});
[struct_data.size] = deal(C{:});
% are the results the same?
isequal(struct_data,struct_data_save)
ans = logical
1
Melanie VT
Melanie VT 2023-3-10
That is awesome! Thank you so much for providing solutions for both scenarios🙏

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更多回答（1 个）

Stephen23
Stephen23 2023-3-10
Ran in:
S = load('data.mat')
S = struct with fields:
list: [27×1 double] table_data: [27×3 table]
list = S.list
list = 27×1
0 100 60 0 0 0 0 0 0 0
tdat = S.table_data
tdat = 27×3 table
district count size ________ _____ __________ {[ 1]} 91 {'venti' } {[ 2]} 116 {'venti' } {[ 3]} 112 {'venti' } {[ 4]} 8 {'venti' } {[ 5]} 23 {0×0 char} {[ 6]} 16 {0×0 char} {[ 7]} 7 {0×0 char} {[ 8]} 1 {0×0 char} {[ 9]} 28 {0×0 char} {[10]} 58 {'tall' } {[11]} 43 {'venti' } {[12]} 13 {'trenta'} {[13]} 68 {'tall' } {[14]} 108 {'grande'} {[15]} 102 {'venti' } {[16]} 76 {'venti' }
k=0;
out0 = struct('idx',[],'count',[],'size',[]);
for i = 1:size(tdat,1)
for j = 1:list(i)
k=k+1;
out0(k,1).idx = k;
out0(k,1).count = tdat.count(i);
out0(k,1).size = tdat.size{i};
end % ^ ^ fixed indexing
end
out0
out0 = 160×1 struct array with fields:
idx count size
Without an explicit loop:
out1 = repelem(table2struct(removevars(tdat,'district')),list);
idx = num2cell(1:numel(out1));
[out1.idx] = idx{:}
out1 = 160×1 struct array with fields:
count size idx
isequal(out0,out1)
ans = logical
1
  1 个评论
Melanie VT
Melanie VT 2023-3-10
移动：Stephen23 2023-3-11
This solution is even almost 1.5 times faster than the one above! I’m truly grateful to you all🙏🏼
This post is also an Accepted Answer with appreciation😊

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