I have the following script for importing text files into matlab which include hourly data, where I am then trying to convert them into daily averages:
clear all
pathName = ...
TopFolder = pathName;
dirListing = dir(fullfile(TopFolder,'*.txt'));%Lists the folders in the directory specified by pathName.
for i = 1:length(dirListing);
SubFolder{i} = dirListing(i,1).name;%obtain the name of each folder in
%the specified path.
end
%import data
for i=1:length(SubFolder);
rawData1{i} = importdata(fullfile(pathName,SubFolder{i}));
end
%convert into daily averages
rawData2=cell2mat(rawData1);
%create one matrix for entire data set
altered=reshape(rawData2,24,(size(rawData2,2)*365));
%convert into daily values
altered=mean(altered)';
%take the average for each day
altered=reshape(altered,365,size(rawData2,2));
%convert back into original format
My problem lies in trying to convert the data back into the same format as ‘rawData1’ which was a cell for each variable (where each variable is denoted by ‘SubFolder’. The reason for doing this is that all but one of the variables are vectors, where the remaining variable is a matrix (8760*11).
So, an example of this would be:
clear all
cell_1 = rand(8760,1);
cell_2 = rand(8760,1);
cell_3 = rand(8760,1);
cell_4 = rand(8760,1);
cell_5 = rand(8760,1);
cell_6 = rand(8760,11);
cell_7 = rand(8760,1);
cell_8 = rand(8760,1);
cell_9 = rand(8760,1);
data = {cell_1,cell_2,cell_3,cell_4,cell_5,cell_6,cell_7,cell_8,cell_9};
Where I need to convert each cell in ‘data’ from hourly values into daily averages (i.e. 365 rows).
Any advice would be much appreciated.
I think this does what you want.
However that is kind of confusing so I will explain a little.
This part
mean(reshape(x,24,[]))'inside of thecellfunwill reshape each cell in data into a 24 by 365, compute the mean, then turn it back into a single column. This works fine when the original data only has 1 column … but for cell_6 with 11 columns it puts all the data end to end. So I added an additionreshape(...)wrapper around themean(...)part to put it back into the original 11 columns … or more precises N columns that are 365 rows in length.Note: This is going to give you errors if you ever have data sets dimensions are not 8760 by X.