def test_triangle_init():
"""Assert that initialization checks lower and upper bounds."""
# Should just run
u = cp.Uniform(0., 1.)
t = cp.Triangle(u - 1., u, u + 1.)
cp.J(u, t)
# Overlapping lb and ub
with pytest.raises(ValueError):
cp.Triangle(u - 0.5, u, u + 1.)
with pytest.raises(ValueError):
cp.Triangle(u - 1., u, u + 0.5)
# Should initialize fine
cp.Triangle(u - 1., 0., u + 0.5)
#!/usr/bin/env python
from __future__ import print_function
import openturns as ot
import chaospy as cp
import numpy as np
# A chaospy Triangle distribution
d0 = cp.Triangle(2.0, 3.5, 4.0)
d1 = cp.Kumaraswamy(2.0, 3.0, -1.0, 4.0)
d2 = cp.J(d0, d1)
for chaospy_dist in [d0, d1, d2]:
np.random.seed(42)
# create an openturns distribution
py_dist = ot.ChaospyDistribution(chaospy_dist)
distribution = ot.Distribution(py_dist)
print('distribution=', distribution)
print('realization=', distribution.getRealization())
sample = distribution.getSample(10)
print('sample=', sample[0:5])
point = [2.6]*distribution.getDimension()
print('pdf= %.6g' % distribution.computePDF(point))
cdf = distribution.computeCDF(point)
print('cdf= %.6g' % cdf)
print('mean=', distribution.getMean())
print('mean(sampling)=', sample.computeMean())
print('std=', distribution.getStandardDeviation())
print('std(sampling)=', sample.computeStandardDeviationPerComponent())
print('skewness=', distribution.getSkewness())
delimiter='$',
target_filename='input.json')
decoder = uq.decoders.JSONDecoder(target_filename='output.json',
output_columns=['g1'])
execute = ExecuteLocal('{}/beam input.json'.format(os.getcwd()))
actions = Actions(CreateRunDirectory('/tmp'), Encode(encoder), execute,
Decode(decoder))
campaign = uq.Campaign(name='beam', params=params, actions=actions)
vary = {
"F": cp.Normal(1, 0.1),
"L": cp.Normal(1.5, 0.01),
"a": cp.Uniform(0.7, 1.2),
"D": cp.Triangle(0.75, 0.8, 0.85)
}
campaign.set_sampler(uq.sampling.PCESampler(vary=vary, polynomial_order=1))
with QCGPJPool(
template_params={'venv': '/home/bartek/.virtualenv/qcgpj7'}) as qcgpj:
#with QCGPJPool() as qcgpj:
campaign.execute(pool=qcgpj).collate()
campaign.get_collation_result()
campaign.campaign_db.dump()
results = campaign.analyse(qoi_cols=['g1'])
results.plot_sobols_treemap('g1', figsize=(10, 10))