def test_sorm(setup):
dist1 = Normal(loc=500, scale=100)
dist2 = Normal(loc=1000, scale=100)
dist = [dist1, dist2]
form_obj = FORM(distributions=dist, runmodel_object=setup)
form_obj.run()
sorm_obj = SORM(form_object=form_obj)
for file_name in glob.glob("Model_Runs_*"):
shutil.rmtree(file_name)
np.testing.assert_allclose(sorm_obj.failure_probability, 2.8803e-7, rtol=1e-02)
def test_seeds_xu_is_none(setup):
path = os.path.abspath(os.path.dirname(__file__))
os.chdir(path)
dist1 = Normal(loc=200, scale=20)
dist2 = Normal(loc=150, scale=10)
dist = [dist1, dist2]
form_obj = FORM(distributions=dist, runmodel_object=setup)
form_obj.run()
for file_name in glob.glob("Model_Runs_*"):
shutil.rmtree(file_name)
np.testing.assert_allclose(form_obj.u_record[0][0][0], [0., 0.],
rtol=1e-02)
def test_seeds_x_is_none(setup):
path = os.path.abspath(os.path.dirname(__file__))
os.chdir(path)
dist1 = Normal(loc=200, scale=20)
dist2 = Normal(loc=150, scale=10)
dist = [dist1, dist2]
form_obj = FORM(distributions=dist, runmodel_object=setup, seed_u=[1, 1])
form_obj.run()
for file_name in glob.glob("Model_Runs_*"):
shutil.rmtree(file_name)
np.testing.assert_allclose(form_obj.failure_probability,
0.0126,
rtol=1e-02)
def test_form_example():
path = os.path.abspath(os.path.dirname(__file__))
os.chdir(path)
model = PythonModel(model_script='pfn3.py',
model_object_name='example1',
delete_files=True)
RunModelObject = RunModel(model=model)
dist1 = Normal(loc=200., scale=20.)
dist2 = Normal(loc=150, scale=10.)
Q = FORM(distributions=[dist1, dist2],
runmodel_object=RunModelObject,
tol1=1e-5,
tol2=1e-5)
Q.run()
# print results
np.allclose(Q.DesignPoint_U, np.array([-2., 1.]))
np.allclose(Q.DesignPoint_X, np.array([160., 160.]))
assert Q.beta[0] == 2.236067977499917
assert Q.failure_probability[0] == 0.012673659338729965
np.allclose(Q.dg_u_record, np.array([0., 0.]))
# %%
# %% md
#
# Initially we have to import the necessary modules.
# %%
from UQpy.run_model.RunModel import RunModel
from UQpy.run_model.model_execution.PythonModel import PythonModel
from UQpy.distributions import Normal
from UQpy.reliability import FORM
dist1 = Normal(loc=20., scale=3.5)
dist2 = Normal(loc=5., scale=0.8)
dist3 = Normal(loc=4., scale=0.4)
model = PythonModel(
model_script='pfn.py',
model_object_name="example3",
)
RunModelObject3 = RunModel(model=model)
Z0 = FORM(distributions=[dist1, dist2, dist3], runmodel_object=RunModelObject3)
Z0.run()
print('Design point in standard normal space: %s' % Z0.DesignPoint_U)
print('Design point in original space: %s' % Z0.DesignPoint_X)
print('Hasofer-Lind reliability index: %s' % Z0.beta)
print('FORM probability of failure: %s' % Z0.failure_probability)
import shutil
import numpy as np
import matplotlib.pyplot as plt
from UQpy.run_model.RunModel import RunModel
from UQpy.run_model.model_execution.PythonModel import PythonModel
from UQpy.distributions import Normal
from UQpy.reliability import FORM
model = PythonModel(model_script='pfn.py', model_object_name="example1")
RunModelObject = RunModel(model=model)
dist1 = Normal(loc=200., scale=20.)
dist2 = Normal(loc=150, scale=10.)
Q = FORM(distributions=[dist1, dist2], runmodel_object=RunModelObject, tol1=1e-5, tol2=1e-5)
Q.run()
# print results
print('Design point in standard normal space: %s' % Q.DesignPoint_U)
print('Design point in original space: %s' % Q.DesignPoint_X)
print('Hasofer-Lind reliability index: %s' % Q.beta)
print('FORM probability of failure: %s' % Q.failure_probability)
print(Q.dg_u_record)
# Supporting function
def multivariate_gaussian(pos, mu, Sigma):
n = mu.shape[0]
Sigma_det = np.linalg.det(Sigma)
import shutil
import numpy as np
from UQpy.run_model.RunModel import RunModel
from UQpy.run_model.model_execution.PythonModel import PythonModel
from UQpy.distributions import Normal
from UQpy.reliability import FORM
from UQpy.reliability import SORM
from UQpy.distributions import Lognormal
m0 = 7
v0 = 1.4
mu = np.log(m0) - np.log(np.sqrt(1 + (v0 / m0) ** 2))
scale = np.exp(mu)
s = np.sqrt(np.log(1 + (v0 / m0) ** 2))
loc_ = 0.0
dist1 = Normal(loc=20., scale=2)
dist2 = Lognormal(s=s, loc=0.0, scale=scale)
model = PythonModel(model_script='pfn.py', model_object_name="example4",)
RunModelObject4 = RunModel(model=model)
form = FORM(distributions=[dist1, dist2], runmodel_object=RunModelObject4)
form.run()
Q0 = SORM(form_object=form)
# print results
print('SORM probability of failure: %s' % Q0.failure_probability)
# :math:`g(U) = -\frac{1}{\sqrt{d}}\sum_{i=1}^{d} u_i + \beta`
#
# The probability of failure in this case is :math:`P(F) ≈ 10^{−3}` for :math:`β = 3.0902`
#
# Initially we have to import the necessary modules.
#%%
import shutil
from UQpy.run_model.RunModel import RunModel
from UQpy.run_model.model_execution.PythonModel import PythonModel
from UQpy.distributions import Normal
from UQpy.reliability import FORM
dist1 = Normal(loc=0., scale=1.)
dist2 = Normal(loc=0., scale=1.)
model = PythonModel(model_script='pfn.py', model_object_name="example2")
RunModelObject2 = RunModel(model=model)
Z = FORM(distributions=[dist1, dist2], runmodel_object=RunModelObject2)
Z.run()
# print results
print('Design point in standard normal space: %s' % Z.DesignPoint_U)
print('Design point in original space: %s' % Z.DesignPoint_X)
print('Hasofer-Lind reliability index: %s' % Z.beta)
print('FORM probability of failure: %s' % Z.failure_probability)