Java example source code file (exponentialTestCases)

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The exponentialTestCases Java example 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 exponential distribution tests in
# org.apache.commons.math.distribution.ExponentialDistributionTest
#
# 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>")
#
#------------------------------------------------------------------------------
tol <- 1E-9

# Function definitions

source("testFunctions")           # utility test functions

# function to verify distribution computations

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

# function to verify density computations
verifyDensity <- function(points, expected, mean, tol) {
 rDensityValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDensityValues[i] <- dexp(point, 1/mean)
    }
    output <- c("Density test mean = ", mean)
    if (assertEquals(expected, rDensityValues, tol, "Density Values")) {
        displayPadded(output, SUCCEEDED, WIDTH)
    } else {
        displayPadded(output, FAILED, WIDTH)
    }
}

# function to verify quantiles
verifyQuantiles <- function(points, expected, mean, tol) {
	rQuantileValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rQuantileValues[i] <- qexp(point, 1/mean, log = FALSE)
    }
    output <- c("Quantile test mean = ", mean)
    if (assertEquals(expected, rQuantileValues, tol, "Quantile Values")) {
        displayPadded(output, SUCCEEDED, WIDTH)
    } else {
        displayPadded(output, FAILED, WIDTH)
    }
}


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

mean <- 5

distributionValues <- c(0, 0, 0.001, 0.01, 0.025, 0.05, 0.1, 0.999,
                0.990, 0.975, 0.950, 0.900)
densityValues <- c(0.2, 0.2, 0.1998, 0.198, 0.195, 0.19, 0.18, 0.000200000000000,
                0.00200000000002, 0.00499999999997, 0.00999999999994, 0.0199999999999)
distributionPoints <- c(0, 0, 0.00500250166792, 0.0502516792675, 0.126589039921, 0.256466471938,
                0.526802578289, 34.5387763949, 23.0258509299, 18.4443972706, 14.9786613678, 11.5129254650)
verifyDistribution(distributionPoints, distributionValues, mean, tol)
verifyQuantiles(distributionValues, distributionPoints, mean, tol)
verifyDensity(distributionPoints, densityValues, mean, tol)

output <- "Probability test P(.25 < X < .75)"
if (assertEquals(0.0905214480757, pexp(.75, 1/mean) - pexp(.25, 1/mean), tol, "Probability value")) {
    displayPadded(output, SUCCEEDED, WIDTH)
} else {
    displayPadded(output, FAILED, WIDTH)
}

displayDashes(WIDTH)