Commons Math example source code file (cauchyTestCases.R)

This example Commons Math source code file (cauchyTestCases.R) 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, cauchy, density, failed, false, false, license, license, r, succeeded, values, values, width, width

The Commons Math cauchyTestCases.R 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 Cauchy distribution tests in
# org.apache.commons.math.distribution.CauchyDistributionTest
#
# 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, median, scale, tol) {
 rDistValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDistValues[i] <- pcauchy(point, median, scale, log = FALSE)
    }
    output <- c("Distribution test median = ",median,", scale = ", scale)
    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, median, scale, tol) {
 rDensityValues <- rep(0, length(points))
    i <- 0
    for (point in points) {
        i <- i + 1
        rDensityValues[i] <- dcauchy(point, median, scale, log = FALSE)
    }
    output <- c("Density test median = ",median,", scale = ", scale)
    if (assertEquals(expected, rDensityValues, tol, "Density Values")) {
        displayPadded(output, SUCCEEDED, WIDTH)
    } else {
        displayPadded(output, FAILED, WIDTH)
    }       
}

# function to verify quantiles

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

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

median <- 1.2
scale <- 2.1
distributionValues <- c(0.001, 0.01, 0.025, 0.05, 0.1, 0.999,
                0.990, 0.975, 0.950, 0.900)
densityValues <- c(1.49599158008e-06, 0.000149550440335, 0.000933076881878, 0.00370933207799, 0.0144742330437,
                1.49599158008e-06, 0.000149550440335, 0.000933076881878, 0.00370933207799, 0.0144742330437)
distributionPoints <- c(-667.24856187, -65.6230835029, -25.4830299460, -12.0588781808, -5.26313542807,
                669.64856187, 68.0230835029, 27.8830299460, 14.4588781808, 7.66313542807)
verifyDistribution(distributionPoints, distributionValues, median, scale, tol)
verifyDensity(distributionPoints, densityValues, median, scale, tol)
verifyQuantiles(distributionValues, distributionPoints, median, scale, tol)

displayDashes(WIDTH)