Average range when value is reached

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Osnofa
Osnofa 2019-6-27
评论： Osnofa 2019-7-12
Hello,
I have a tough situation in hands.
File format (sample file attached)
day_of_year | solar height | d1 | d2 | d3 | d4
I need to apply a correction to d1 to d4 based on solar height.
For each day I need to fing the average value of d1, d2, d3 and d4 for:
1- once solar height hits -18 (degrees) in the morning I need to average the previous 60 data values (if this happens on cell 101, i need the average of cells 40 to 100)
2 -once solar height hits -18 (degrees) in the afternoon/night I need to average the following 60 data values
3 - Obtain the average value between 1 and 2 for each day of the year.
Note: Solar Height is negative before sunrise and after sunset, being positive during the day.
I don't have really an idea on how to proceed from here...
This file has 59 days, so the result would be a matrix 59*4 results.
thanks for the attention

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Guillaume
Guillaume 2019-6-28
Here is how I'd do it. First create a function that takes a Mx5 matrix of {solar_height, d1 ... d4} data for a single day and return your desired 1x4 output for that day:
function dayaverage = processday(solardata)
%solardata: matrix whose first column is the solar height. A MxN matrix
%dayaverage: the average solar data for the day as 1x(N-1) vector
%... explanation of algorithm goes here
morningstart = find(solardata(:, 1) >= -18, 1); %find where solar height first goes above -18
assert(morningstart > 60, 'morning starts too early to be able to average the previous 60 rows');
morningaverage = mean(solardata(morningstart-60:morningstart-1, 2:end), 1);
afternoonend = find(solardata(:, 1) >= -18, 1, 'last'); %find where solar height is last above -18
assert(afternoonend < size(solardata, 1) - 60, 'afternoon ends too late to be able to average the next 60 rows');
afternoonaverage = mean(solardata(afternoonend+1:afternoonend+60, 2:end), 1);
dayaverage = (morningaverage + afternoonaverage) / 2;
end
Then import your data into a table:
solardata = readtable('test_data.txt');
solardata.Properties.VariableNames = {'day_of_year', 'solar_height', 'd1', 'd2', 'd3', 'd4'};
head(solardata) %if you want to preview the table
It's then trivial to call the above function for each day:
dailysolardata = rowfun(@processday, solardata, 'GroupingVariable', 'day_of_year', 'SeparateInputs', false, 'OutputVariableName', 'd')
if you prefer individual dn variable in the output instead of Mx4 variable:
dailysolardata = splitvars(dailysolardata, 'd', 'NewVariableNames', compose('d%d', 1:4))
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Guillaume
Guillaume 2019-7-11
编辑：Guillaume 2019-7-11
1) is easy to fix by replacing the last line of the function with:
dayaverage = mean([morningaverage; afternoonaverage], 'omitnan');
You'll still get NaN if both morning and afternoon are NaN. You may or may not want to add the 'omitnan' option to the calculation of morningaverage and afternoonaverage. But if you do, there will be less than 60 values used for the mean calculation when NaNs are present.
Note that there's no use for nanmean anymore, the mean function can omit nan as shown, and doesn't require any toolbox.
As for 2, what values where you expecting and which range of rows did you expect to be averaged for morning and afternoon of day 7?
Osnofa
Osnofa 2019-7-12
Thanks.
meanwhile I had solved 1. I used nanmean instead of mean with the omitnan flag.
Regarding 2, I was performing the double check on a slightly different file (other tests). It was correct, my bad.
Just a note:
This process takes way much more time compared to the other proposed solution, but it works and it servers the purpose. For now I don't need efficiency, only to do the task.
Thanks for the solution :)

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Shubham Gupta
Shubham Gupta 2019-6-28
I assumed that you have test_data in a mat file, for this answer I am assuming the data stored in the variable named 'TestData'. I think you should achieve the desired result with the following code :
Ind = find(abs(TestData(:,2)+18)<0.097); % Finding indices that are close to Solar height of -18 (deg)
d_SH = [0;diff(TestData(:,2))]; % Variation in solar height
%% Loop to store average values
for i=1:length(Ind)
j = Ind(i);
if d_SH(j)>0 % If solar height is increasing ( Sunrise )
Out(i,:) = mean(TestData(j-60:j,3:6));
else % If solar height is decreasing ( Sunset )
Out(i,:) = mean(TestData(j:j+60,3:6));
end
end
%% Averaging Sunrise and Sunset data
for k=1:length(Out)/2
Desired_out(k,:) = mean(Out(2*k-1:2*k,:));
end
  1 个评论
Osnofa
Osnofa 2019-7-9
编辑：Osnofa 2019-7-11
Hello,
Thanks for the input and sorry for the late reply. I've been testing this and found some inconsistency.
Ind = find(abs(TestData(:,2)+18)<0.097); % Finding indices that are close to Solar height of -18 (deg)
This indice is not always correct. how did you choose the 0.097 value?
the number of values obtained for Ind is weird because it is 3852, being 2 per day it means it should be 1926 days. However, the dataseries has 1642 days. I'm using the complete data that can be found here: https://ufile.io/9iufdg9j
The indice is not allways correct, sometimes it passed the target value and others is ok.
Thanks.

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