How can I create another matrix with the sum of every 30 rows in a 14,400 by 11 matrix?

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txvmi07
txvmi07 2014-6-13
评论： Habeeb Alasadi 2015-7-2
I have a matrix with 11 columns of daily data for 40 years (14,400 days) and need the sum of every 30 days to be calculated. After looking around a lot I decided I'd ask on here. Thanks in advance for the help!

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采纳的回答

Andrei Bobrov
Andrei Bobrov 2014-6-13
out = squeeze(sum(reshape(yourdata',11,30,[]),2))';

更多回答（5 个）

Image Analyst
Image Analyst 2014-6-13
Did you try the brute force approach? It's pretty simple and intuitive and fast:
m = randi(9, [14400, 11]);
otuputRow = 1;
for row = 1 : 30 : size(m, 1)
theSums(otuputRow, :) = sum(m(row:row+29,:));
otuputRow = otuputRow + 1;
end
theSums
Matt J
Matt J 2014-6-13
If the 30-day blocks to be summed are tiled, you can also do
result = downsampn(yourMatrix,[30,1])*30;
where downsampn is given by,
function M=downsampn(M,bindims)
%DOWNSAMPN - simple tool for downsampling n-dimensional nonsparse arrays
%
% M=downsampn(M,bindims)
%
%in:
%
% M: an array
% bindims: a vector of integer binning dimensions
%
%out:
%
% M: the downsized array
nn=length(bindims);
[sz{1:nn}]=size(M); %M is the original array
sz=[sz{:}];
newdims=sz./bindims;
args=num2cell([bindims;newdims]);
M=reshape(M,args{:});
for ii=1:nn
M=mean(M,2*ii-1);
end
M=reshape(M,newdims);
  1 个评论
Cedric
Cedric 2014-6-13
I don't think that we can beat this one. I expected Andrei's solution to be faster, but it seems that dealing with pages makes it slower than iterating over "bindims"..

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Matt J
Matt J 2014-6-13
result = conv2(yourMatrix,ones(30,1),'valid');
Cedric
Cedric 2014-6-13
编辑：Cedric 2014-6-13
Here are a couple additional ways, if you need a sum for each block of 30 days (not a "moving" sum), assuming that your original matrix is named M:
Base on accumarray
M_aggregated = zeros( size(M,1)/30, size(M,2) ) ;
blockId = zeros( size(M,1), 1 ) ;
blockId(1:30:end) = 1 ;
blockId = cumsum( blockId ) ;
for cId = 1 : size(M,2)
M_aggregated(:,cId) = accumarray( blockId, M(:,cId) ) ;
end
Based on matrix product
% - Build aggregation matrix.
aggr = repmat( {ones(1,30)}, size(M,1)/30, 1 ) ;
aggr = blkdiag( aggr{:} ) ;
% - Aggregate data.
M_aggregated = aggr * M ;
txvmi07
txvmi07 2014-6-16
Thank you everyone for your generous help! All of your suggestions worked great and seeing all the different methodologies was extremely helpful. I've generated a hyperbolic decline curve for an oil and gas well in order to estimate the ultimate volumes that it will produce over 40 years (~14,400 days). While having this data on a daily basis is great it's more function to further analysis on a monthly basis.
I will say that Andrei's response was likely the simplest, but that all examples worked perfectly.
Thanks again!

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