Ichthyostega
064651335f
It covers now roughly the same procedures as before, yet the scheme how to do verification is quite different. Furthermore, we allocate large random-sized buffers now and implant `TestFrame` instances, and so also the verification covers a significant storage area.
141 lines
4.2 KiB
C++
141 lines
4.2 KiB
C++
/*
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Random(Test) - verify framework for controlled random number generation
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Copyright (C)
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2024, Hermann Vosseler <Ichthyostega@web.de>
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**Lumiera** is free software; you can redistribute it and/or modify it
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under the terms of the GNU General Public License as published by the
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Free Software Foundation; either version 2 of the License, or (at your
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option) any later version. See the file COPYING for further details.
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* *****************************************************************/
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/** @file random-test.cpp
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** unit test \ref Random_test
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*/
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#include "lib/test/run.hpp"
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#include "lib/random.hpp"
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#include "lib/util.hpp"
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#include "lib/test/diagnostic-output.hpp"
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using util::isLimited;
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namespace lib {
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namespace test {
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/******************************************************************//**
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* @test demonstrate simple access to random number generation,
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* as well as the setup of controlled random number sequences.
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* @see random.hpp
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*/
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class Random_test : public Test
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{
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virtual void
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run (Arg)
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{
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simpleUsage();
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verify_distributionVariants();
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verify_reproducibleSequence();
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}
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/** @test demonstrate usage of default random number generators.
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* @note should [draw a seed](\ref Test::seedRand()) once per Test instance
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*/
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void
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simpleUsage()
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{
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seedRand();
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int r1 = rani();
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CHECK (0 <= r1 and r1 < RAND_MAX);
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int r2 = rani();
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CHECK (0 <= r2 and r2 < RAND_MAX);
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CHECK (r1 != r2); // may fail with very low probability
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}
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/** @test properties of predefined distributions provided for convenience
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* - the upper bound for `rani(bound)` is exclusive
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* - uniform distributions are sufficiently uniform
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* - spread of normal distribution is within expected scale
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*/
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void
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verify_distributionVariants()
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{
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double avg{0.0};
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const uint N = 1e6;
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for (uint i=0; i < N; ++i)
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avg += 1.0/N * rani (1000);
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auto expect = 500;
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auto error = fabs(avg/expect - 1);
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CHECK (error < 0.005);
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for (uint i=0; i < N; ++i)
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CHECK (isLimited(0, rani(5), 4));
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for (uint i=0; i < N; ++i)
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CHECK (0 != ranHash());
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auto sqr = [](double v){ return v*v; };
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double spread{0.0};
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for (uint i=0; i < N; ++i)
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spread += sqr (ranNormal() - 0.5);
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spread = sqrt (spread/N);
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CHECK (spread < 1.12);
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}
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/** @test demonstrate that random number sequences can be reproduced
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* - use a rigged SeedNucleus, always returning a fixed seed
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* - build two distinct random sequence generators, yet seeded
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* from the same source; they will produce the same sequence
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* - sequences can be re-shuffled by a seed value, so that
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* the following random numbers will start to differ
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* - but even this re-shuffling is deterministic
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*/
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void
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verify_reproducibleSequence()
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{
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class : public SeedNucleus
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{
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uint64_t getSeed() override { return 55; }
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}
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coreOfEvil;
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Random src1{coreOfEvil};
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int r1 = src1.i32();
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uint64_t r2 = src1.u64();
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double r3 = src1.uni();
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Random src2{coreOfEvil};
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CHECK (r1 == src2.i32());
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CHECK (r2 == src2.u64());
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CHECK (r3 == src2.uni());
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src1.reseed (coreOfEvil);
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CHECK (src1.u64() != src2.u64());
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src2.reseed (coreOfEvil);
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CHECK (src1.u64() != src2.u64());
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(void) src2.u64();
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CHECK (src1.u64() == src2.u64());
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CHECK (src1.i32() == src2.i32());
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CHECK (src1.uni() == src2.uni());
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}
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};
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LAUNCHER (Random_test, "unit common");
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}} // namespace lib::test
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