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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
# 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" % ot.DistFunc.pGamma(k, x),
", complementary=%.6g" % ot.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" % ot.DistFunc.qGamma(k, q),
", complementary=%.6g" % ot.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" % ot.DistFunc.rGamma(k))
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