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#! /usr/bin/env python
import openturns as ot
ot.TESTPREAMBLE()
# Beta related functions
# pBeta
p1Min = 0.2
p1Max = 5.0
n1 = 5
p2Min = 0.2
p2Max = 5.0
n2 = 5
xMin = 0.1
xMax = 0.9
nX = 5
for i1 in range(n1):
p1 = p1Min + (p1Max - p1Min) * i1 / (n1 - 1)
for i2 in range(n2):
p2 = p2Min + (p2Max - p2Min) * i2 / (n2 - 1)
for iX in range(nX):
x = xMin + (xMax - xMin) * iX / (nX - 1)
print(
"pBeta(",
p1,
", ",
p2,
", %.12g" % x,
")=%.6g" % ot.DistFunc.pBeta(p1, p2, x),
", complementary=%.6g" % ot.DistFunc.pBeta(p1, p2, x, True),
)
# qBeta
p1Min = 0.2
p1Max = 5.0
n1 = 5
p2Min = 0.2
p2Max = 5.0
n2 = 5
qMin = 0.1
qMax = 0.9
nQ = 5
for i1 in range(n1):
p1 = p1Min + (p1Max - p1Min) * i1 / (n1 - 1)
for i2 in range(n2):
p2 = p2Min + (p2Max - p2Min) * i2 / (n2 - 1)
for iQ in range(nQ):
q = qMin + (qMax - qMin) * iQ / (nQ - 1)
print(
"qBeta(",
p1,
", ",
p2,
", %.12g" % q,
")=%.6g" % ot.DistFunc.qBeta(p1, p2, q),
", complementary=%.6g" % ot.DistFunc.qBeta(p1, p2, q, True),
)
# rBeta
p1Min = 0.2
p1Max = 5.0
n1 = 5
p2Min = 0.2
p2Max = 5.0
n2 = 5
nR = 5
for i1 in range(n1):
p1 = p1Min + (p1Max - p1Min) * i1 / (n1 - 1)
for i2 in range(n2):
p2 = p2Min + (p2Max - p2Min) * i2 / (n2 - 1)
for iR in range(nR):
print("rBeta(", p1, ", ", p2, ")=%.6g" % ot.DistFunc.rBeta(p1, p2))
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