# 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

require("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)