Gets the parameters then adds the command plus parameters to the host object job list. Then tells the host to run. After all jobs have completed, collect the data and call analyze(). If iteration_cb is defined, call it.
The callback must take two parameters. The first one is the sweep object, the second is the handle to the hdf5 file of the run. It must return a boolean. If True is returned, the sweep is over. If false, the sweep parameters may be changed and it will continue.
Returns True on success.
Class implementing Latin hypercube sampling (LHS).
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Class implementing Monte Carlo sampling.
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Class implementing gPC using Smolyak Sparse Grids
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If level is set too low, then the response surface will not precisely fit the observed responses. The goodness of the fit is calculated as by RMSE. A perfect fit will have RMSE=0.
Class implementing a simple sweep.
This sweep does evaluations at the given points.
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