#! /usr/bin/env python

from openturns import *

TESTPREAMBLE()
RandomGenerator.SetSeed(0)

try:
    # 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" % DistFunc.pBeta(p1, p2, x), ", complementary=%.6g" % 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" % DistFunc.qBeta(p1, p2, q), ", complementary=%.6g" % 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" % DistFunc.rBeta(p1, p2)

except:
    import sys
    print "t_DistFunc_beta.py", sys.exc_type, sys.exc_value
