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Java example source code file (paretoTestCases)

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

Learn more about this Java project at its project page.

Java - Java tags/keywords

apache, density, distribution, failed, false, license, see, succeeded, the, values, width, you

The paretoTestCases 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 LogNormal distribution tests in
# org.apache.commons.math.distribution.LogNormalDistributionTest
#
# 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
# ppareto(q, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE) <-- distribution
# The VGAM library which includes the function above must be installed to run
# this test.
# See https://cran.r-project.org/web/packages/VGAM/index.html
#-----------------------------------------------------------------------------
tol <- 1E-9

# Function definitions

library(VGAM)
source("testFunctions")           # utility test functions

# function to verify distribution computations

verifyDistribution <- function(points, expected, mu, sigma, tol) {
 rDistValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDistValues[i] <- ppareto(point, mu, sigma)
    }
    output <- c("Distribution test mu = ",mu,", sigma = ", sigma)
    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, mu, sigma, tol) {
 rDensityValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDensityValues[i] <- dpareto(point, mu, sigma, log = FALSE)
    }
    output <- c("Density test mu = ",mu,", sigma = ", sigma)
    if (assertEquals(expected, rDensityValues, tol, "Density Values")) {
        displayPadded(output, SUCCEEDED, WIDTH)
    } else {
        displayPadded(output, FAILED, WIDTH)
    }
}

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

mu <- 2.1
sigma <- 1.4
distributionValues <- c(0, 0, 0, 0, 0, 0.791089998892, 0.730456085931, 0.689667290488, 0.645278794701, 0.578763688757)
densityValues <- c(0, 0, 0, 0, 0, 0.0455118580441, 0.070444173646, 0.0896924681582, 0.112794186114, 0.151439332084)
distributionPoints <- c(-2.226325228634938, -1.156887023657177, -0.643949578356075, -0.2027950777320613, 0.305827808237559,
                6.42632522863494, 5.35688702365718, 4.843949578356074, 4.40279507773206, 3.89417219176244)
verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)
verifyDensity(distributionPoints, densityValues, mu, sigma, tol)

distributionValues <- c(0, 0, 0, 0.510884134236, 0.694625688662, 0.785201995008, 0.837811522357, 0.871634279326)
densityValues <- c(0, 0, 0.666666666, 0.195646346305, 0.0872498032394, 0.0477328899983, 0.0294888141169, 0.0197485724114)
distributionPoints <- c(mu - 2 *sigma, mu - sigma, mu, mu + sigma,
		mu + 2 * sigma,  mu + 3 * sigma, mu + 4 * sigma,
                    mu + 5 * sigma)
verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)
verifyDensity(distributionPoints, densityValues, mu, sigma, tol)

mu <- 1
sigma <- 1
distributionPoints <- c(mu - 2 *sigma, mu - sigma, mu, mu + sigma,
		mu + 2 * sigma,  mu + 3 * sigma, mu + 4 * sigma,
                    mu + 5 * sigma)
distributionValues <- c(0, 0, 0, 0.5, 0.666666666667, 0.75, 0.8, 0.833333333333)
densityValues <- c(0, 0, 1, 0.25, 0.111111111111, 0.0625, 0.04, 0.0277777777778)
verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)
verifyDensity(distributionPoints, densityValues, mu, sigma, tol)

mu <- 0.1
sigma <- 0.1
distributionPoints <- c(mu - 2 *sigma, 0, mu, mu + sigma,
		mu + 2 * sigma,  mu + 3 * sigma, mu + 4 * sigma,
                    mu + 5 * sigma)
distributionValues <- c(0, 0, 0, 0.0669670084632, 0.104041540159, 0.129449436704, 0.148660077479, 0.164041197922)
densityValues <- c(0, 0, 1, 0.466516495768, 0.298652819947, 0.217637640824, 0.170267984504, 0.139326467013)
verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)
verifyDensity(distributionPoints, densityValues, mu, sigma, tol)

displayDashes(WIDTH)

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