MATLAB: How to interpolate under specific condition

interpolatemissingnantime gap

Hi everyone. I would appreciate your help on this.
I have a daily timeseries of temperature observations for 2006-2016.
I want to reconstruct missing values (see attached) with an interpolation method only if the missing values cover less that 3 days. If the gap is larger (>4days), I want NaN values to be preserved. Column A contains the dates I have temperature observations (NaT indicates temperature is NaN) and Column C is the full time sequence 2006-2016.
How can I do this? I am totally confused… The interpolation method could be anything, I have not decided on this yet.
Thank you in advance!
PS. I am on R2019a.

Best Answer

Hi, this code should work:
The file Daily data.xlsx must be in the same directory as your script!
DATA = importdata('Daily data.xlsx'); % importing all data
MeanTemp = DATA.data.Sheet1; % creating an array containg the mean Temp measured
pos = find(isnan(MeanTemp)); % find NaN elements
x_val = (1:length(MeanTemp))'; % creatin a 'pseudo-timeline' vector
for i = 4:length(pos) % finding the index of 4 or more consecutive NaN
    
    if (pos(i)==pos(i-2)+2 && pos(i)==pos(i-1)+1 && pos(i)==pos(i-3)+3)
        consec_days(i)=true;
    end
end
consec_nan = find(consec_days==true); % index of pos where we want to keep NaN
y = pos;
y(consec_nan-3) = 0;
y(consec_nan-2) = 0;
y(consec_nan-1) = 0;
y(consec_nan) = 0;
k = find(y==0); % excluding 4 or more consecutive days in interpolation
y(k)=[]; % NaN to be interpolated
%--------INTERPOLATION-----------------%
MeanTemp(pos)=[]; % values to be interpolated
x_val(pos)=[];
x_unknown_temp = [x_val;y];
x_unknown_temp = sort(x_unknown_temp);
MeanTemp_interpolated = spline(x_val,MeanTemp,x_unknown_temp);      
MeanTemp_interpolated1 = interp1(x_val,MeanTemp,x_unknown_temp);    
%---------INTERPOLATION-END-------------%
% Creating a matrix with 2 rows 
% containg the values of NaN interpolated
% in both cases
% (spline first column, interp1 second column)
Values_interpolated(:,1) = MeanTemp_interpolated(y);    
Values_interpolated(:,2) = MeanTemp_interpolated1(y);
% Date-time line below:
datetime1 = datetime(2006,01,01):caldays(1):datetime(2016,12,31);
% String_Values_interpolated contains Values_interpolated
% and the relative day
String_Values_interpolated = num2cell(Values_interpolated(1:end,1:2));
String_Values_interpolated(:,3) = cellstr(datetime1(y))';
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