Commons Math example source code file (hypergeometricTestCases)

This example Commons Math source code file (hypergeometricTestCases) is included in the DevDaily.com "Java Source Code Warehouse" project. The intent of this project is to help you "Learn Java by Example" ^TM.

Java - Commons Math tags/keywords

apache, distribution, failed, false, false, license, license, r, r, succeeded, true, values, width, width

The Commons Math hypergeometricTestCases source code

# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#------------------------------------------------------------------------------
# R source file to validate Hypergeometric distribution tests in
# org.apache.commons.math.distribution.HypergeometricDistributionTest
#
# To run the test, install R, put this file and testFunctions
# into the same directory, launch R from this directory and then enter
# source("<name-of-this-file>")
#
# R functions used
# dhyper(x, m, n, k, log = FALSE) <- density 
# phyper(q, m, n, k, lower.tail = TRUE, log.p = FALSE) <- distribution
# qhyper(p, m, n, k, lower.tail = TRUE, log.p = FALSE) <- quantiles
#------------------------------------------------------------------------------
tol <- 1E-6                       # error tolerance for tests
#------------------------------------------------------------------------------
# Function definitions

source("testFunctions")           # utility test functions

# function to verify density computations

verifyDensity <- function(points, expected, good, bad, selected, tol) {
    rDensityValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDensityValues[i] <- dhyper(point, good, bad, selected)
    }
    output <- c("Density test good = ", good, ", bad = ", bad, 
                ", selected = ",selected)
    if (assertEquals(expected,rDensityValues,tol,"Density Values")) {
        displayPadded(output, SUCCEEDED, WIDTH)
    } else {
        displayPadded(output, FAILED, WIDTH)
    }       
}

# function to verify distribution computations

verifyDistribution <- function(points, expected, good, bad, selected, tol) {
    rDistValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDistValues[i] <- phyper(point, good, bad, selected)
    }
    output <- c("Distribution test good = ", good, ", bad = ",
                 bad, ", selected = ",selected)
    if (assertEquals(expected,rDistValues,tol,"Distribution Values")) {
        displayPadded(output, SUCCEEDED, WIDTH)
    } else {
        displayPadded(output, FAILED, WIDTH)
    }       
}

#--------------------------------------------------------------------------
cat("Hypergeometric test cases\n")

good <- 5
bad <- 5
selected <- 5

densityPoints <- c(-1, 0, 1, 2, 3, 4, 5, 10)
densityValues <- c(0, 0.003968, 0.099206, 0.396825, 0.396825, 0.099206, 
                   0.003968, 0)
distributionValues <- c(0, .003968, .103175, .50000, .896825, .996032,
                        1.00000, 1)
#Eliminate p=1 case because it will mess up adjustement below
inverseCumPoints <- c(0, 0.001, 0.010, 0.025, 0.050, 0.100, 0.999,
                      0.990, 0.975, 0.950, 0.900)
inverseCumValues <- c(-1, -1, 0, 0, 0, 0, 4, 3, 3, 3, 3)

verifyDensity(densityPoints, densityValues, good, bad, selected, tol)
verifyDistribution(densityPoints, distributionValues, good, bad, selected, tol)

i <- 0
rInverseCumValues <- rep(0,length(inverseCumPoints))
for (point in inverseCumPoints) {
  i <- i + 1
  rInverseCumValues[i] <- qhyper(point, good, bad, selected)
}

output <- c("Inverse Distribution test good = ", good, ", bad = ", bad, 
            ", selected = ", selected)
# R defines quantiles from the right, need to subtract one
if (assertEquals(inverseCumValues, rInverseCumValues-1, tol,
    "Inverse Dist Values")) {
    displayPadded(output, SUCCEEDED, 80)
} else {
    displayPadded(output, FAILED, 80)
}       

# Degenerate cases
good <- 5
bad <- 0
selected <- 3
densityPoints <- c(-1, 0, 1, 3, 10)
densityValues <- c(0, 0, 0, 1, 0)
distributionValues <- c(0, 0, 0, 1, 1)
verifyDensity(densityPoints, densityValues, good, bad, selected, tol)
verifyDistribution(densityPoints, distributionValues, good, bad, selected, tol)

good <- 0
bad <- 5
selected <- 3
densityPoints <- c(-1, 0, 1, 3, 10)
densityValues <- c(0, 1, 0, 0, 0)
distributionValues <- c(0, 1, 1, 1, 1)
verifyDensity(densityPoints, densityValues, good, bad, selected, tol)
verifyDistribution(densityPoints, distributionValues, good, bad, selected, tol)

good <- 3
bad <- 2
selected <- 5
densityPoints <- c(-1, 0, 1, 3, 10)
densityValues <- c(0, 0, 0, 1, 0)
distributionValues <- c(0, 0, 0, 1, 1)
verifyDensity(densityPoints, densityValues, good, bad, selected, tol)
verifyDistribution(densityPoints, distributionValues, good, bad, selected, tol)

displayDashes(WIDTH)