def run_atan_sg(inputspace, gridType, level, numGridPoints,
boundaryLevel, fullGrid, refinement, out, plot):
testSetting = AtanPeridynamicExample(inputspace)
if refinement is not None:
testSetting.run_adaptive_sparse_grid(Grid.stringToGridType(gridType),
level, numGridPoints, refinement,
boundaryLevel, fullGrid, out,
plot)
else:
testSetting.run_regular_sparse_grid(Grid.stringToGridType(gridType),
level, numGridPoints, boundaryLevel,
fullGrid, out, plot)
def run_sobol_g_function_sg(fullModel, gridType, level, numGridPoints,
fullGrid, refinement, out):
testSetting = SobolGFunctionSudret2008(fullModel)
sobol_indices, N = testSetting.run_sparse_grids(
Grid.stringToGridType(gridType), level, numGridPoints, fullGrid,
refinement, out)
return testSetting.sobol_indices, sobol_indices, N
def run_adaptive_sparse_grid(self, gridTypeStr, level, maxGridSize, refinement,
boundaryLevel=None, out=False,
plot=False):
np.random.seed(1234567)
gridType = Grid.stringToGridType(gridTypeStr)
results = {'surrogate': 'asg',
'grid_type': gridType,
'is_full': False,
'time_steps': self.toi,
'setting': self.setting,
'num_dims': self.numDims,
'qoi': self.qoi,
'max_grid_size': maxGridSize,
'boundary_level': boundaryLevel,
'refinement': refinement,
'refinement_technique': 'refinement',
'adaptPoints': 5,
'adaptRate': 0.05,
'adpatEps': 1e-10,
'results': {}}
# ----------------------------------------------------------
# define the learner
# ----------------------------------------------------------
builder = UQBuilder()
self.defineUQSetting(builder)
uqSetting = builder.andGetResult()
uqManager = TestEnvironmentSG().buildSetting(self.params,
level=level,
gridType=gridType,
deg=20,
maxGridSize=maxGridSize,
isFull=False,
adaptive=refinement,
adaptPoints=5,
# adaptRate=0.05,
epsilon=1e-10,
boundaryLevel=boundaryLevel,
qoi=self.qoi,
toi=self.toi,
saveAfterN=-1, # dont save at all
uqSetting=uqSetting,
uqSettingRef=self.uqSettings['ref'])
# ----------------------------------------------
# first run
oldSize = uqManager.uqSetting.getSize()
while uqManager.hasMoreSamples():
uqManager.runNextSamples()
# ----------------------------------------------------------
# specify ASGC estimator
analysis = ASGCAnalysisBuilder().withUQManager(uqManager)\
.withAnalyticEstimationStrategy()\
.andGetResult()
analysis.setVerbose(False)
# ----------------------------------------------------------
label = "asg_l%i_%s" % (level, gridTypeStr)
self.runAnalysis(analysis, uqManager, "sg", label,
out, plot, results)
# update results
results["max_grid_size"] = uqManager.getGrid().getSize()
if out:
# store results
filename = os.path.join(self.pathResults,
"%s-qoi%s_%s_d%i_%s_Nmax%i_r%s_N%i.pkl" % (self.radix, self.qoi,
"asg",
self.numDims,
gridTypeStr,
maxGridSize,
refinement,
uqManager.getGrid().getSize()))
fd = open(filename, "w")
pkl.dump(results, fd)
fd.close()
def run_regular_sparse_grid(self, gridTypeStr,
level,
maxGridSize,
boundaryLevel=1,
isFull=False,
out=False,
plot=False):
np.random.seed(1234567)
gridType = Grid.stringToGridType(gridTypeStr)
results = {'surrogate': 'sg',
'grid_type': gridType,
'is_full': False,
'time_steps': self.toi,
'setting': self.setting,
'num_dims': self.numDims,
'qoi': self.qoi,
'max_grid_size': maxGridSize,
'boundary_level': boundaryLevel,
'refinement': None,
'results': {}}
while True:
print("-" * 80)
print("level = %i, grid type = %s" % (level, gridTypeStr))
builder = UQBuilder()
self.defineUQSetting(builder)
uqSetting = builder.andGetResult()
uqManager = TestEnvironmentSG().buildSetting(self.params,
level=level,
gridType=gridType,
deg=20,
maxGridSize=maxGridSize,
isFull=isFull,
boundaryLevel=boundaryLevel,
qoi=self.qoi,
toi=self.toi,
saveAfterN=-1,
uqSetting=uqSetting,
uqSettingRef=self.uqSettings['ref'])
if uqManager.sampler.getSize() > maxGridSize:
print("DONE: %i > %i" % (uqManager.sampler.getSize(), maxGridSize))
break
# ----------------------------------------------
oldSize = uqManager.uqSetting.getSize()
while uqManager.hasMoreSamples():
uqManager.runNextSamples()
# ----------------------------------------------------------
# specify ASGC estimator
analysis = ASGCAnalysisBuilder().withUQManager(uqManager)\
.withAnalyticEstimationStrategy()\
.andGetResult()
analysis.setVerbose(False)
# ----------------------------------------------------------
label = "sg_l%i_%s" % (level, gridTypeStr)
self.runAnalysis(analysis, uqManager, "sg", label,
out, plot, results)
level += 1
# update results
results["max_grid_size"] = uqManager.getGrid().getSize()
if out:
# store results
filename = os.path.join(self.pathResults,
"%s-qoi%s_%s_d%i_%s_Nmax%i_r%i_N%i.pkl" % (self.radix, self.qoi,
"sg" if not isFull else "fg",
self.numDims,
gridTypeStr,
maxGridSize,
False,
uqManager.getGrid().getSize()))
fd = open(filename, "w")
pkl.dump(results, fd)
fd.close()
def run_ishigami_sg(gridType, level, numGridPoints, fullGrid, refinement, out):
testSetting = IshigamiSudret2008()
sobol_indices, N = testSetting.run_sparse_grids(
Grid.stringToGridType(gridType), level, numGridPoints, fullGrid,
refinement, out)
return testSetting.sobol_indices, sobol_indices, N
