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#! /usr/bin/env python
from __future__ import print_function
from openturns import *
TESTPREAMBLE()
RandomGenerator.SetSeed(0)
try:
# Gamma related functions
# pGamma
kMin = 0.2
kMax = 5.0
nK = 5
xMin = 0.1
xMax = 0.9
nX = 5
for i1 in range(nK):
k = kMin + (kMax - kMin) * i1 / (nK - 1)
for iX in range(nX):
x = xMin + (xMax - xMin) * iX / (nX - 1)
print("pGamma(", k, ", %.12g" % x, ")=%.6g" % DistFunc.pGamma(
k, x), ", complementary=%.6g" % DistFunc.pGamma(k, x, True))
# qGamma
kMin = 0.2
kMax = 5.0
nK = 5
qMin = 0.1
qMax = 0.9
nQ = 5
for i1 in range(nK):
k = kMin + (kMax - kMin) * i1 / (nK - 1)
for iQ in range(nQ):
q = qMin + (qMax - qMin) * iQ / (nQ - 1)
print("qGamma(", k, ", %.12g" % q, ")=%.6g" % DistFunc.qGamma(
k, q), ", complementary=%.6g" % DistFunc.qGamma(k, q, True))
# rGamma
kMin = 0.2
kMax = 5.0
nK = 5
nR = 5
for i1 in range(nK):
k = kMin + (kMax - kMin) * i1 / (nK - 1)
for iR in range(nR):
print("rGamma(", k, ")=%.6g" % DistFunc.rGamma(k))
except:
import sys
print("t_DistFunc_gamma.py", sys.exc_info()[0], sys.exc_info()[1])
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