# 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 Normal distribution tests in
# org.apache.commons.math.distribution.NormalDistributionTest
#
# 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
# pnorm(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] <- pnorm(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] <- dnorm(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("Normal test cases\n")

mu <- 2.1
sigma <- 1.4
distributionValues <- c(0.001, 0.01, 0.025, 0.05, 0.1, 0.999,
                0.990, 0.975, 0.950, 0.900)
densityValues <- c(0.00240506434076, 0.0190372444310, 0.0417464784322, 0.0736683145538, 0.125355951380,
                0.00240506434076, 0.0190372444310, 0.0417464784322, 0.0736683145538, 0.125355951380)
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( 0.0227501319482, 0.158655253931, 0.5, 0.841344746069, 0.977249868052,
                     0.998650101968, 0.999968328758, 0.999999713348)
densityValues <- c(0.0385649760808, 0.172836231799, 0.284958771715, 0.172836231799, 0.0385649760808,
                0.00316560600853, 9.55930184035e-05, 1.06194251052e-06)
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)
densityValues <- c(0.0539909665132, 0.241970724519, 0.398942280401, 0.241970724519, 0.0539909665132,
                0.00443184841194, 0.000133830225765, 1.48671951473e-06)
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)
densityValues <- c(0.539909665132, 2.41970724519, 3.98942280401, 2.41970724519,
                0.539909665132, 0.0443184841194, 0.00133830225765, 1.48671951473e-05)
verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)
verifyDensity(distributionPoints, densityValues, mu, sigma, tol)

displayDashes(WIDTH)