def atest_stochastic_universal_sampling(self):
self.set_positions_resampling_set()
setNpRandomSeed()
indices = [0,0,1,3,3,4]
solutions = self.resample(indices)
dautils.stochasticUniversalSampling(self.resamplingDrifterSet, self.resamplingVar)
assert2DListAlmostEqual(self, self.resamplingDrifterSet.getDrifterPositions().tolist(), solutions, 2, "stochastic universal sampling, probabilistic duplicates")
def atest_stochastic_universal_sampling(self):
self.set_positions_resampling_set()
setNpRandomSeed()
indices = [0,0,1,3,3,4]
solutions = self.resample(indices)
dautils.stochasticUniversalSampling(self.resamplingDrifterSet, self.resamplingVar)
assert2DListAlmostEqual(self, self.resamplingDrifterSet.getDrifterPositions().tolist(), solutions, 2, "stochastic universal sampling, probabilistic duplicates")
def atest_stochastic_universal_sampling_with_duplicates(self):
self.set_positions_resampling_set()
setNpRandomSeed()
indices = [0, 0, 1, 3, 3, 4]
solutions = self.resample(indices)
dautils.stochasticUniversalSampling(self.resamplingDrifterSet)
self.assertEqual(self.resamplingDrifterSet.getDrifterPositions().tolist(), \
solutions)
def atest_stochastic_universal_sampling_with_duplicates(self):
self.set_positions_resampling_set()
setNpRandomSeed()
indices = [0,0,1,3,3,4]
solutions = self.resample(indices)
dautils.stochasticUniversalSampling(self.resamplingDrifterSet)
self.assertEqual(self.resamplingDrifterSet.getDrifterPositions().tolist(), \
solutions)
