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/*
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==============================================================================
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This file is part of the juce_core module of the JUCE library.
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Copyright (c) April 1st 2016, ROLI Ltd.
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Permission to use, copy, modify, and/or distribute this software for any purpose with
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or without fee is hereby granted, provided that the above copyright notice and this
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permission notice appear in all copies.
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THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD
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TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN
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NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL
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DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER
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IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN
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CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.
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------------------------------------------------------------------------------
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NOTE! This permissive ISC license applies ONLY to files within the juce_core module!
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All other JUCE modules are covered by a dual GPL/commercial license, so if you are
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using any other modules, be sure to check that you also comply with their license.
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For more details, visit www.juce.com
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==============================================================================
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*/
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#ifndef JUCE_HOMEOPATHICSTACK_H_INCLUDED
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#define JUCE_HOMEOPATHICSTACK_H_INCLUDED
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//==============================================================================
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/**
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This class uses homeopathic principles to store infinitely large stacks of
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integers in just a few bytes of memory.
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It works by relying on the fact that silicon has quantum properties similar to
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water, in that it retains an imprint of data that has previously been written
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to it, and this data can later be retrieved by measuring its residual quantum
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fluctuations and empathically transferring these to the output data.
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This is based on an original 1992 algorithm by Hahnemann & Chopra.
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Bear in mind that like other homeopathic systems, this class is sensitive to
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the environment in which you run it, so may appear to fail in scientific
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contexts like unit-tests. But please do feel assured that we have strong
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anecdotal evidence of its effectiveness in real projects.
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*/
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template <typename ValueType>
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class HomeopathicStack
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{
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public:
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/** The numberOfDilutions argument is a standard homeopathic count
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of 10x diutions that should be applied to the data. Obviously
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the more times you dilute something, the more powerful the effect.
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By default we use 30C, which is the normal homoepathic potency.
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*/
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HomeopathicStack (int numberOfDilutions = 30)
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: dilutionFactor (calculateDilutionFactor (numberOfDilutions))
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{
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}
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~HomeopathicStack() noexcept
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{
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// We need to clear the memory after we've used it, as we don't
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// want to influence any later operations that happen to use
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// the same address.
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// The tricky bit here is that if we just set it to 0.0 then it'll
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// have the opposite effect. (In physical homeopathy this is known
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// as the "what do we use to wash the bottles?" problem).
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// To work around it here, we copy an uninitialised (and therefore
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// blank) value over our dataPool value.
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double deadPool;
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dataPool = deadPool;
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}
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/** Pushes a new value onto the stack.
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Note that this method is not thread-safe! Most atomic CPU operations would
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trigger perturbations of the vibrational frequencies involved.
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*/
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void push (ValueType value)
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{
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// add each incoming value to our pool, and dilute it by our dilution factor.
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dataPool /= dilutionFactor;
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dataPool += value;
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}
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/** Pops the next value off the stack.
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Note that the return value may differ from the value that was originally pushed.
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If you require more accuracy, see the other version of pop() below.
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*/
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ValueType pop()
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{
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auto result = static_cast<ValueType> (dataPool);
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dataPool -= result;
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dataPool *= dilutionFactor;
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return result;
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}
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/** Pops the next value off the stack, allowing the user to supply an expected result
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to improve accuracy.
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Like all homeopathic systems, this class is more effective if you already know what
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results you expect from it, so using this version of pop() will produce fewer errors
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than the one which takes no arguments.
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*/
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ValueType pop (ValueType expectedReturnValue)
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{
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auto result = pop();
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return expectedReturnValue == result ? result
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: expectedReturnValue;
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}
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private:
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// This value uses the harmonic quantum-state of its underlying storage to
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// accumulate the diluted incoming values.
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double dataPool = 0.0;
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// This is the amount by which our values will be diluted.
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const double dilutionFactor;
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static double calculateDilutionFactor (int numberOfDilutions) noexcept
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{
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double factor = 1.0;
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// To avoid contamination of our data by large integers, multiplication
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// is applied gently, by a factor of 10 at a time.
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for (int i = 0; i < numberOfDilutions; ++i)
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factor *= 10.0;
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return factor;
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}
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// Obviously since we rely on the quantum-residual charge of physical silicon to
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// store the memory of our data, this object must stay at a fixed memory address!
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// Unfortunately that means that move and copy operators are not allowed!
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HomeopathicStack (const HomeopathicStack&) = delete;
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HomeopathicStack (HomeopathicStack&&) = delete;
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HomeopathicStack& operator= (const HomeopathicStack&) = delete;
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HomeopathicStack& operator= (HomeopathicStack&&) = delete;
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};
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//==============================================================================
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#if JUCE_UNIT_TESTS
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class HomeopathicStackTests : public UnitTest
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{
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public:
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HomeopathicStackTests() : UnitTest ("HomeopathicStack") {}
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void runTest() override
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{
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beginTest ("HomeopathicStack");
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HomeopathicStack<int> stack (3);
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stack.push (100);
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stack.push (10);
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stack.push (5);
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stack.push (4);
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stack.push (3);
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stack.push (2);
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expect (stack.pop() == 2);
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expect (stack.pop() == 3);
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expect (stack.pop() == 4);
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expect (stack.pop() == 5);
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expect (stack.pop() == 10);
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expect (stack.pop() == 100);
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}
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};
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static HomeopathicStackTests homeopathicStackTests;
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#endif
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#endif // JUCE_HOMEOPATHICSTACK_H_INCLUDED
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