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#! /usr/bin/env python
from __future__ import print_function
from openturns import *
TESTPREAMBLE()
RandomGenerator.SetSeed(0)
try:
dim = 3
R = CorrelationMatrix(dim)
for i in range(dim):
for j in range(i):
R[i, j] = 0.5 * (1.0 + i) / dim
distribution = NormalCopula(R)
size = 10000
sample = distribution.getSample(size)
factory = NormalCopulaFactory()
estimatedDistribution = factory.build(sample)
print("distribution=", distribution)
print("Estimated distribution=", estimatedDistribution)
# non-regression for #572
estimated_dist = NormalCopulaFactory().build(distribution.getSample(10))
mydist = ComposedDistribution(
DistributionCollection(dim, Normal()), estimated_dist)
estimatedDistribution = factory.build()
print("Default distribution=", estimatedDistribution)
estimatedNormalCopula = factory.buildAsNormalCopula(sample)
print("NormalCopula =", distribution)
print("Estimated normalCopula=", estimatedNormalCopula)
estimatedNormalCopula = factory.buildAsNormalCopula()
print("Default normalCopula=", estimatedNormalCopula)
except:
import sys
print("t_NormalCopulaFactory_std.py", sys.exc_info()[0], sys.exc_info()[1])
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