BAYESIAN Inversion (Error: Number of dimensions must be a positive scalar integer between 1 and 1111)

Hello UQWorld!

I have the following problem in BAYESIAN Inversion analysis:

for a set of the input vector as a N X M matrix, I have an output matrix of size N X Nout.
in case the location of measurements (Nout) exceeds 1111 I can not run the analysis anymore. here is the error:
Number of dimensions must be a positive scalar integer between 1 and 1111.

Error in qrandset/set.Dimensions (line 198)
error(message(‘stats:qrandset:InvalidNumberOfDimensions’, obj.getMaxDims));

Error in qrandset (line 162)
obj.Dimensions = Dims;

Error in sobolset (line 110)
obj = obj@qrandset(varargin{:});

Error in uq_sampleU (line 62)
options.SobolGen = sobolset(M);

Error in uq_default_input (line 104)
u(:,indNonConst) = uq_sampleU(N, M,samplingOptions);

Error in uq_initialize_uq_inversion (line 707)
Seed = uq_getSample(Internal.FullPrior,Opt.Value.MCMC.NChains,‘sobol’)’;

Error in PODIbays (line 76)
myBayesianAnalysis = uq_createAnalysis(BayesOpts);


I have a measurement on the 2331 Nodes of a 2D field displacement during 200 time-frames. therefore for each parameter vector as INPUT of my forward operator, I have an output in the shape of 2331 X 200 matrix. because outputs of a UQLab model accept only vectors, I reshaped my 2331X200 matrix to a 1 X 466200 vector. so my Nout is 466200 and UQlab can not run the analysis because of the limitation of the ‘sobol’ function in Matlab.

is there any solution for this problem?

Best Regards,