Let’s say we want to calibrate the same model (with only one output) with two different kinds of measurements (different discrepancy opts). How will we specify the MOMap array for that case? It’s like measuring the beam deflections at the midspan using two instruments of different accuracy. Then updating the same model which predicts beam deflections using the two kinds of data altogether.
The UQLab user manual on page 32 says:
The output IDs speciﬁed in the MOMap vector, are not unique. By giving the same index in the MOMap vectors of different data groups, it becomes possible to calibrate the same computational model using measurements gathered in different experiments
This part isn’t really clear to me. I tried giving the same ID to two different data groups and it returns an error:
The supplied MOMap does not uniquely address every model output
I’m reproducing a sample code below:
measures = [2.6, 2.4; 2.9, 2.8]; %Row 1 measured with discrepancy 1 % and Row 2 measured with discrepancy 2 disc = [0.5, 0.6] % Discrepancies for the two data groups % First data group data(1).Name = 'Measurements with discrepancy 1'; data(1).y = measures(1,:)'; data(1).MOMap = 1; % Measurement of model's first and only output discrepancyopts(1).Type = 'Gaussian'; discrepancyopts(1).Parameters = disc(1); % Second data group data(2).Name = 'Measurements with discrepancy 2'; data(2).y = measures(2,:)'; data(2).MOMap = 1; % Measurement of model's first and only output discrepancyopts(2).Type = 'Gaussian'; discrepancyopts(2).Parameters = disc(2);
What am I doing wrong here?