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#! /bin/sh
# This script tests: pgmnoise
# Also requires:
# These tests are for examining the integrity of the random number
# generator. There is some overlap between the tests here and tests
# in pgmnoise.test, but the tests here are better focused for
# diagnosing problems with the random number generator.
#
# Test 1 is for determining the kind of random number generator in
# use.
#
# Test 2 prints random numbers in an output format close to what the
# test in the original Mersenne Twister code produces.
#
# If these tests fail, subsequent tests which depend on random numbers
# will fail too. There is no provision (beyond remarks in the script
# files) for generators other than the Mersenne Twister in those
# tests.
echo "Test 1: Should produce:"
echo "P2"
echo "12 1"
echo "1023"
echo "720 296 192 858 101 57 298 629 804 1019 64 617"
echo "Above output is for Mersenne Twister"
# GNU libc rand(): 593 252 207 990 507 824 961 805 559 110 167 172
# MAC OS rand(): 9 782 60 418 364 654 670 172 1022 515 593 903
pgmnoise -maxval=1023 -randomseed=3791 -plain 12 1
echo
echo "Test 2: Mersenne Twister random number generator"
echo "Should produce:"
echo "3499211612 581869302 3890346734 3586334585 545404204"
echo "4161255391 3922919429 949333985 2715962298 1323567403"
echo " ... "
echo " 297480282 1101405687 1473439254 2634793792 1341017984"
echo " Total 1000 integers, 200 lines"
echo
# Use perl to avoid mawk limitation
# (cannot convert 32 bit integers)
perlPgmProcessorProgram='
if (($#F+1) == 10) {
for (my $i = 0; $i <= 9; $i += 2) {
my $r = $F[$i + 1] * 65536 + $F[$i];
printf "%10u ", $r;
}
print "";
}
'
pgmnoise -randomseed=5489 -plain -maxval=65535 10 200 | \
perl -walne "$perlPgmProcessorProgram"
# The above outputs (10 * 200 / 2) = 1000 samples.
# Method to generate output for Test 2 from original
# Mersenne Twister source code
#
# Download Mersenne Twister code. See lib/util/randmersenne.c for URL.
# Edit mt19937ar.c:
# In function main() at bottom of file, replace
# init_by_array(init, length);
# with
# init_genrand(5489UL);
#
# We need only the output of genrand_int32().
# Remove the second loop which produces double-precision floating point
# random numbers with genrand_real2().
#
# Compile: gcc mt19937ar.c -o mt1000
# Execute: ./mt1000
# 1000 may seem like a large number of samples but there is a reason
# for this. The generator produces random integers in batches of 624.
# The number of samples must be larger than 624 to ensure proper
# generation in batches after the first.
# If you encounter problems, adjust the 200 (rows) above and tweak
# the code in mt19937ar.c accordingly to produce more random numbers.
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