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#! /usr/bin/env python
import openturns as ot
import openturns.testing as ott
ot.TESTPREAMBLE()
# Instantiate one distribution object
distribution = ot.Multinomial(5, ot.Point(3, 0.25))
print("Distribution ", repr(distribution))
print("Distribution ", distribution)
# Is this distribution elliptical ?
print("Elliptical = ", distribution.isElliptical())
# Is this distribution continuous ?
print("Continuous = ", distribution.isContinuous())
# Test for realization of distribution
oneRealization = distribution.getRealization()
print("oneRealization=", oneRealization)
print("support=\n" + str(distribution.getSupport()))
interval = ot.Interval(
ot.Point(distribution.getDimension(), 1.0),
ot.Point(distribution.getDimension(), 3.0),
)
print(
"support restricted to the interval=\n"
+ str(interval)
+ " gives=\n"
+ str(distribution.getSupport(interval))
)
# Define a point
point = ot.Point(distribution.getDimension(), 1.0)
print("Point= ", repr(point))
# Show PDF and CDF at point
LPDF = distribution.computeLogPDF(point)
print("log pdf=%.6f" % LPDF)
PDF = distribution.computePDF(point)
print("pdf =%.6f" % PDF)
CDF = distribution.computeCDF(point)
print("cdf=%.5f" % CDF)
proba = distribution.computeProbability(
ot.Interval(
[i for i in range(distribution.getDimension())],
[i + 1.0 for i in range(distribution.getDimension())],
)
)
print("probability=%.5f" % proba)
quantile = distribution.computeQuantile(0.95)
print("quantile=", repr(quantile))
print("cdf(quantile)= %.6f" % distribution.computeCDF(quantile))
print("entropy=%.6f" % distribution.computeEntropy())
mean = distribution.getMean()
print("mean=", repr(mean))
covariance = distribution.getCovariance()
print("covariance=", repr(covariance))
parameters = distribution.getParametersCollection()
print("parameters=", repr(parameters))
parameter = distribution.getParameter()
print("parameter=", repr(parameter))
print("parameterDesc=", distribution.getParameterDescription())
distribution.setParameter(parameter)
ot.Log.Show(ot.Log.TRACE)
validation = ott.DistributionValidation(distribution)
validation.skipMoments() # slow
validation.skipCorrelation() # slow
validation.skipConditional() # FIXME
validation.run()
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