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#! /usr/bin/env python
from __future__ import print_function
from openturns import *
TESTPREAMBLE()
RandomGenerator.SetSeed(0)
try:
# We create a numerical math function */
myFunction = NumericalMathFunction(
["E", "F", "L", "I"], ["d"], ["-F*L^3/(3*E*I)"])
dim = myFunction.getInputDimension()
# We create a normal distribution point of dimension dim
myDistribution = Normal(dim)
# We create a 'usual' RandomVector from the Distribution
vect = RandomVector(myDistribution)
# We create a composite random vector
output = RandomVector(myFunction, vect)
# We create an StandardEvent from this RandomVector
myStandardEvent = StandardEvent(output, Less(), 1.0)
print("myStandardEvent=", myStandardEvent)
# We compute one realization of the event
# E = (Y=f(X), operator, threshold)
# E as a RandomVector : Y
print("myStandardEvent (as a RandomVector) realization =",
repr(RandomVector.getRealization(myStandardEvent)))
# E as a Bernoulli
print("myStandardEvent realization=", repr(
myStandardEvent.getRealization()))
# We compute a sample of the event
print("myStandardEvent sample=", repr(myStandardEvent.getSample(10)))
# Build a standard event based on an event
R = CorrelationMatrix(dim)
for i in range(dim - 1):
R[i + 1, i] = 0.5
mean = NumericalPoint(dim, 0.0)
sigma = NumericalPoint(dim, 1.0)
myDistribution2 = Normal(mean, sigma, R)
# We create a 'usual' RandomVector from the Distribution
vect2 = RandomVector(myDistribution2)
# We create a composite random vector
output2 = RandomVector(myFunction, vect2)
# We create an Event from this RandomVector */
myEvent = Event(output2, Less(), 1.0)
# Create a StandardEvent based on this Event */
stdEvent = StandardEvent(myEvent)
# Check if the StandardEvent is really a StandardEvent */
# Get a sample from the second antecedent of the standard event */
size = 2000
# Check if the failure probabilities are the same */
print("Failure probability (Event)=%.6f" %
myEvent.getSample(size).computeMean()[0])
print("Failure probability (StandardEvent)=%.6f" %
stdEvent.getSample(size).computeMean()[0])
collection = UserDefinedPairCollection(
3, UserDefinedPair(NumericalPoint(dim), 0.0))
point = NumericalPoint(dim)
point[0] = 1.0
point[1] = 0.5
point[2] = 1.0
point[3] = 0.5
collection[0] = UserDefinedPair(point, 0.3)
point[0] = 2.0
point[1] = 1.0
point[2] = 2.0
point[3] = 1.0
collection[1] = UserDefinedPair(point, 0.325)
point[0] = 3.0
point[1] = 1.5
point[2] = 3.0
point[3] = 1.5
collection[2] = UserDefinedPair(point, 0.375)
myDistribution3 = UserDefined(collection)
# We create a 'usual' RandomVector from the Distribution */
vect3 = RandomVector(myDistribution3)
# We create a composite random vector */
output3 = RandomVector(myFunction, vect3)
# We try to create a StandardEvent from this RandomVector */
try:
myStandardEvent3 = StandardEvent(output3, Less(), 1.0)
except:
print("Error trying to build myStandardEvent3")
except:
import sys
print("t_StandardEvent_std.py", sys.exc_info()[0], sys.exc_info()[1])
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