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#! /usr/bin/env python
from __future__ import print_function
from openturns import *
TESTPREAMBLE()
RandomGenerator.SetSeed(0)
try:
# NonCentralChiSquare related functions
# dNonCentralChiSquare
nuMin = 0.2
nuMax = 5.0
n1 = 5
lambdaMin = 0.2
lambdaMax = 5.0
n2 = 5
xMin = 0.1
xMax = 0.9
nX = 5
for i1 in range(n1):
nu = nuMin + (nuMax - nuMin) * i1 / (n1 - 1)
for i2 in range(n2):
lambda_ = lambdaMin + (lambdaMax - lambdaMin) * i2 / (n2 - 1)
for iX in range(nX):
x = xMin + (xMax - xMin) * iX / (nX - 1)
print("dNonCentralChiSquare(", nu, ", ", lambda_, ", %.12g" %
x, ")=%.6g" % DistFunc.dNonCentralChiSquare(nu, lambda_, x))
# pNonCentralChiSquare
nuMin = 0.2
nuMax = 5.0
n1 = 5
lambdaMin = 0.2
lambdaMax = 5.0
n2 = 5
xMin = 0.1
xMax = 0.9
nX = 5
for i1 in range(n1):
nu = nuMin + (nuMax - nuMin) * i1 / (n1 - 1)
for i2 in range(n2):
lambda_ = lambdaMin + (lambdaMax - lambdaMin) * i2 / (n2 - 1)
for iX in range(nX):
x = xMin + (xMax - xMin) * iX / (nX - 1)
print("pNonCentralChiSquare(", nu, ", ", lambda_, ", %.12g" % x, ")=%.6g" % DistFunc.pNonCentralChiSquare(
nu, lambda_, x), ", complementary=%.6g" % DistFunc.pNonCentralChiSquare(nu, lambda_, x, True))
# rNonCentralChiSquare
nuMin = 0.2
nuMax = 5.0
n1 = 5
lambdaMin = 0.2
lambdaMax = 5.0
n2 = 5
nR = 5
for i1 in range(n1):
nu = nuMin + (nuMax - nuMin) * i1 / (n1 - 1)
for i2 in range(n2):
lambda_ = lambdaMin + (lambdaMax - lambdaMin) * i2 / (n2 - 1)
for iR in range(nR):
print("rNonCentralChiSquare(", nu, ", ", lambda_, ")=%.6g" %
DistFunc.rNonCentralChiSquare(nu, lambda_))
except:
import sys
print("t_DistFunc_noncentralchisquare.py",
sys.exc_info()[0], sys.exc_info()[1])
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