| # 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) |