| # 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 |
| # plnorm(q, mean=0, sd=1, lower.tail = TRUE, log.p = FALSE) <-- distribution |
| #----------------------------------------------------------------------------- |
| tol <- 1E-9 |
| |
| # Function definitions |
| |
| 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] <- plnorm(point, mu, sigma, log = FALSE) |
| } |
| 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] <- dlnorm(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("LogNormal test cases\n") |
| |
| mu <- 2.1 |
| sigma <- 1.4 |
| distributionValues <- c(0, 0, 0, 0, 0.00948199951485, 0.432056525076, 0.381648158697, 0.354555726206, 0.329513316888, 0.298422824228) |
| densityValues <- c(0, 0, 0, 0, 0.0594218160072, 0.0436977691036, 0.0508364857798, 0.054873528325, 0.0587182664085, 0.0636229042785) |
| 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, 0.0396495152787, 0.16601209243, 0.272533253269, 0.357618409638, 0.426488363093, 0.483255136841, 0.530823013877) |
| densityValues <- c(0, 0.0873055825147, 0.0847676303432, 0.0677935186237, 0.0544105523058, 0.0444614628804, 0.0369750288945, 0.0312206409653) |
| 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 <- 0 |
| 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, 0.755891404214, 0.864031392359, 0.917171480998, 0.946239689548) |
| densityValues <- c(0, 0, 0, 0.398942280401, 0.156874019279, 0.07272825614, 0.0381534565119, 0.0218507148303) |
| verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol) |
| verifyDensity(distributionPoints, densityValues, mu, sigma, tol) |
| |
| mu <- 0 |
| sigma <- 0.1 |
| 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, 1.28417563064e-117, 1.39679883412e-58, 1.09839325447e-33, 2.52587961726e-20, 2.0824223487e-12) |
| densityValues <- c(0, 0, 0, 2.96247992535e-114, 1.1283370232e-55, 4.43812313223e-31, 5.85346445002e-18, 2.9446618076e-10) |
| verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol) |
| verifyDensity(distributionPoints, densityValues, mu, sigma, tol) |
| |
| displayDashes(WIDTH) |