kopia lustrzana https://github.com/vsamy/DiFipp
104 wiersze
3.5 KiB
C++
104 wiersze
3.5 KiB
C++
// Copyright (c) 2019, Vincent SAMY
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// All rights reserved.
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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// 1. Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// 2. Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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// ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
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// WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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// DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
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// ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
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// (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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// LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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// ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
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// (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
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// SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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// The views and conclusions contained in the software and documentation are those
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// of the authors and should not be interpreted as representing official policies,
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// either expressed or implied, of the FreeBSD Project.
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#pragma once
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#include "typedefs.h"
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#include <tuple>
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#include <cmath>
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#include <random>
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template <typename T>
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using FunctionGenerator = std::tuple<difi::vectX_t<T>, difi::vectX_t<T>, difi::vectX_t<T>>;
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template <typename T>
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FunctionGenerator<T> sinGenerator(int nrSteps, T frequency, T dt = 0.001)
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{
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using namespace difi;
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std::random_device rd{};
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std::mt19937 gen{rd()};
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vectX_t<T> truth;
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vectX_t<T> noisy;
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vectX_t<T> derivative;
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for (int i = 0; i < nrSteps; ++i) {
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// truth
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truth(i) = std::sin(2 * pi<T> * frequency * i * dt);
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// noisy
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std::normal_distribution<T> d{truth(i), T(0.01)};
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noisy(i) = truth(i) + d(gen);
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// derivative
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derivative(i) = 2 * pi<T> * frequency * i * std::cos(2 * pi<T> * frequency * i * dt);
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}
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return { truth, noisy, derivative };
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}
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template <typename T>
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FunctionGenerator<T> polyGenerator(int nrSteps, difi::vectX_t<T> coeffs, T dt = 0.001)
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{
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using namespace difi;
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Expects(coeffs.size() >=2);
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std::random_device rd{};
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std::mt19937 gen{rd()};
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auto computePoly = [](const VectX_t<T>& coeffs, T time) {
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auto recursiveComputation = [time, &coeffs](int i, T result) {
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if (i > 0)
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return recursiveComputation(i - 1, time * result + coeffs(i - 1));
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else
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return result;
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};
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return recursiveComputation(coeffs.size(), 0);
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};
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vectX_t<T> derivativeCoeffs(coeffs.size() - 1);
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for (Eigen::Index i = 1; i < coeffs.size(); ++i)
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derivativeCoeffs(i - 1) = i * coeffs.tail(i);
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vectX_t<T> truth;
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vectX_t<T> noisy;
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vectX_t<T> derivative;
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for (int i = 0; i < nrSteps; ++i) {
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// truth
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truth(i) = computePoly(coeffs, i * dt);
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// noisy
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std::normal_distribution<T> d{truth(i), T(0.01)};
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noisy(i) = truth(i) + d(gen);
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// derivative
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derivative(i) = computePoly(derivativeCoeffs, i * dt);
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}
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return { truth, noisy, derivative };
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} |