|
def | __init__ (self, samples=None, ixs=None, n=5000, npaths=100, isPositive=False, percentile=1) |
|
def | mean (self, grid, alpha, U, T) |
|
def | var (self, grid, alpha, U, T, mean) |
|
◆ __init__()
def python.uq.estimators.MonteCarloStrategy.MonteCarloStrategy.__init__ |
( |
|
self, |
|
|
|
samples = None , |
|
|
|
ixs = None , |
|
|
|
n = 5000 , |
|
|
|
npaths = 100 , |
|
|
|
isPositive = False , |
|
|
|
percentile = 1 |
|
) |
| |
Constructor
@param samples: ndarray containing monte carlo samples
@param ixs: list of indices for which there is data available
@param n: number of samples per path
@param npaths: number of paths
@param epsilon: maximal error with respect to the central limit theorem
@param beta: confidence level for central limit theorem
@param isPositive: forces the function to be positive
◆ mean()
def python.uq.estimators.MonteCarloStrategy.MonteCarloStrategy.mean |
( |
|
self, |
|
|
|
grid, |
|
|
|
alpha, |
|
|
|
U, |
|
|
|
T |
|
) |
| |
◆ var()
def python.uq.estimators.MonteCarloStrategy.MonteCarloStrategy.var |
( |
|
self, |
|
|
|
grid, |
|
|
|
alpha, |
|
|
|
U, |
|
|
|
T, |
|
|
|
mean |
|
) |
| |
◆ samples
python.uq.estimators.MonteCarloStrategy.MonteCarloStrategy.samples |
◆ verbose
python.uq.estimators.MonteCarloStrategy.MonteCarloStrategy.verbose |
Referenced by python.uq.operations.forcePositivity.operationMakePositiveFast.OperationMakePositiveFast.addFullGridPoints(), python.uq.refinement.RefinementManager.RefinementManager.candidates(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGridCandidates.computeCandidates(), python.uq.operations.forcePositivity.findIntersections.IntersectionCandidates.findIntersections(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGridCandidates.getLocalMaxLevel(), python.uq.manager.ASGCUQManager.ASGCUQManager.learnDataWithoutTest(), python.uq.manager.ASGCUQManager.ASGCUQManager.learnDataWithTest(), python.uq.operations.forcePositivity.operationMakePositive.OperationMakePositive.makeCurrentNodalValuesPositive(), python.uq.operations.forcePositivity.operationMakePositive.OperationMakePositive.makePositive(), python.uq.operations.forcePositivity.operationMakePositiveFast.OperationMakePositiveFast.makePositive(), python.uq.manager.ASGCUQManager.ASGCUQManager.recomputeStats(), python.uq.refinement.RefinementManager.RefinementManager.refineGrid(), and python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGridCandidates.splitFullGrids().
The documentation for this class was generated from the following file: