# 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-7

# 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)
    }       
}

#--------------------------------------------------------------------------
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)
distributionPoints <- c(-2.226325, -1.156887, -0.6439496, -0.2027951,
                0.3058278, 6.426325, 5.356887, 4.84395, 4.402795, 3.894172)

verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)

distributionValues <- c(0.02275013, 0.1586553, 0.5, 0.8413447, 
                0.9772499, 0.9986501, 0.9999683,  0.9999997)
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)

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)
verifyDistribution(distributionPoints, distributionValues, 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)
verifyDistribution(distributionPoints, distributionValues, mu, sigma, tol)

displayDashes(WIDTH)