diff --git a/plugins/processing/signal-processing/doc/Doc_BoxAlgorithm_EntropyMeasure.dox-part b/plugins/processing/signal-processing/doc/Doc_BoxAlgorithm_EntropyMeasure.dox-part new file mode 100644 index 0000000000000000000000000000000000000000..50e866e6557490a1c823b49bc93cc7f4e51f60ab --- /dev/null +++ b/plugins/processing/signal-processing/doc/Doc_BoxAlgorithm_EntropyMeasure.dox-part @@ -0,0 +1,58 @@ +/** + * \page BoxAlgorithm_EntropyMeasure Entropy Measure +__________________________________________________________________ +Detailed description +__________________________________________________________________ + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Description| + + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Description| +__________________________________________________________________ + +Inputs description +__________________________________________________________________ + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Inputs| + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Inputs| + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Input1| + The input EEG signal. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Input1| +__________________________________________________________________ + +Outputs description +__________________________________________________________________ + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Output1| + The entropy corresponding to the input signal. The form of the output varies according to the scale and the multivariate parameters. + In the case of univariate uniscale (scale = 1) entropy, there will be one output, with as many channels as there were input channels, each output channel being the entropy of the corresponding input channel. + For multivariate uniscale entropy, there will be one output with one channel corresponding to the multivariate entropy of all the input channels. + For multiscale entropy, there will be as many outputs as indicated by the scale (output with index i corresponding to the entropy of scale i), and the number of channels for each output will be the same as just explained for scale 1. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Output1| +__________________________________________________________________ + +Settings description +__________________________________________________________________ + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting1| + The output entropy is the entropy of the last "Time window" seconds of signal. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting1| + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting2| + The output entropy is updated every "Time interval" seconds. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting2| + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting3| + The pattern length for sample entropy. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting3| + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting4| + The similarity threshold of patterns for sample entropy. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting4| + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting5| + Scale > 1 means multiscale entropy of scale "Scale". + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting5| + + * |OVP_DocBegin_BoxAlgorithm_EntropyMeasure_Setting6| + If "Multivariate" is true, then the box will compute multivariate entropy, otherwise it will compute univariate entropy. + * |OVP_DocEnd_BoxAlgorithm_EntropyMeasure_Setting6| diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/AbsctractEntropyCalculator.cpp b/plugins/processing/signal-processing/src/algorithms/entropy/AbsctractEntropyCalculator.cpp new file mode 100644 index 0000000000000000000000000000000000000000..5636f72e65ba13304ca5b27d1d67bc62011f1351 --- /dev/null +++ b/plugins/processing/signal-processing/src/algorithms/entropy/AbsctractEntropyCalculator.cpp @@ -0,0 +1,54 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file AbsctractEntropyCalculator.cpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "AbstractEntropyCalculator.hpp" + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + +EntropyCalculator::EntropyCalculator(int scale) : m_scale(scale) { + m_signal.resize(m_scale); + m_univariateEntropy.resize(m_scale); + m_multivariateEntropy.resize(m_scale); +} + +void EntropyCalculator::initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels) { + m_slidingWindowSize = slidingWindowSize; + m_intervalTimeSize = intervalTimeSize; + m_nbChannels = nbChannels; + + + for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) { + for(size_t channelIdx = 0; channelIdx < m_nbChannels; channelIdx++) { + m_signal[scaleIdx].emplace_back(slidingWindowSize / (scaleIdx + 1)); + } + } +} + +} +} +} \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/AbstractEntropyCalculator.hpp b/plugins/processing/signal-processing/src/algorithms/entropy/AbstractEntropyCalculator.hpp new file mode 100644 index 0000000000000000000000000000000000000000..77682206303a0ac47452b45cc3b7432f75767417 --- /dev/null +++ b/plugins/processing/signal-processing/src/algorithms/entropy/AbstractEntropyCalculator.hpp @@ -0,0 +1,64 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file AbsctractEntropyCalculator.hpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "../../defines.hpp" +#include <vector> +#include "SlidingWindowHelper.hpp" + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + +/// <summary> The abstract class EntropyCalculator describes the interface for entropy calculator classes. </summary> +class EntropyCalculator { +public: + EntropyCalculator(int scale); + + virtual void initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels); + + virtual void calculateUnivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) = 0; + virtual void calculateMultivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) = 0; + +protected: + int m_scale; // m_scale > 1 for multiscale entropy + size_t m_slidingWindowSize; + size_t m_intervalTimeSize; + size_t m_nbChannels; + + std::vector<std::vector<SlidingWindowChannel>> m_signal; + + std::vector<std::vector<double>> m_univariateEntropy; + std::vector<double> m_multivariateEntropy; + + int m_totSamplesCount = 0; + int m_totSampCntAtLastUpdate = 0; + +}; + + +} +} +} \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.cpp b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.cpp new file mode 100644 index 0000000000000000000000000000000000000000..f80e3e9af99fb9abcfa7af947de4bea3c3a5f22b --- /dev/null +++ b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.cpp @@ -0,0 +1,318 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file SampleEntropyCalculator.cpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "SampleEntropyCalculator.hpp" + +#include <boost/math/special_functions/binomial.hpp> + + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + +SampleEntropyCalculator::SampleEntropyCalculator(int m, double r, int scale): EntropyCalculator(scale), m_m(m), m_r(r) { + m_countM.resize(m_scale); + m_countM1.resize(m_scale); + m_univariateEntropy.resize(m_scale); + m_leftOffIndexes.resize(m_scale); +} + +void SampleEntropyCalculator::initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels) { + EntropyCalculator::initialize(slidingWindowSize, intervalTimeSize, nbChannels); + + double maxSimilarVectors = boost::math::binomial_coefficient<double>(slidingWindowSize,2); + m_maxTheoriticalEntropy = log(maxSimilarVectors); + + + + for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) { + + m_countM[scaleIdx].assign(m_nbChannels, SlidingWindowCounter(slidingWindowSize)); + m_countM1[scaleIdx].assign(m_nbChannels, SlidingWindowCounter(slidingWindowSize)); + m_univariateEntropy[scaleIdx].assign(m_nbChannels, m_maxTheoriticalEntropy); + m_leftOffIndexes[scaleIdx].assign(m_nbChannels, 0); + } + +} + +int SampleEntropyCalculator::similarVectors(size_t chanIdx, int startIdx1, int startIdx2, int scale) { + + + const std::deque<double>& timeSeries = m_signal[0][chanIdx].getData(); + if (startIdx1 > startIdx2 - scale) { + return 0; + } + + if (startIdx2 > (int)timeSeries.size() - (m_m+1)*scale) { + return 0; + } + + for(int k = 0; k < m_m + 1; k++) { + + double coarseGrainedVal1 = 0; + double coarseGrainedVal2 = 0; + + for(int s = 0; s < scale; s++) { + coarseGrainedVal1 += timeSeries[startIdx1+(k*scale)+s]; + coarseGrainedVal2 += timeSeries[startIdx2+(k*scale)+s]; + } + + coarseGrainedVal1 /= (double)scale; + coarseGrainedVal2 /= (double)scale; + + if(fabs(coarseGrainedVal1 - coarseGrainedVal2) > m_r) { + if(k < m_m) { return 0; } + return 1; + } + } + return 2; +} + + +int SampleEntropyCalculator::similarVectorsMultivariate(size_t chanIdx1, size_t chanIdx2, int startIdx1, int startIdx2, int scale) { + + + const std::deque<double>& timeSeries1 = m_signal[0][chanIdx1].getData(); + const std::deque<double>& timeSeries2 = m_signal[0][chanIdx2].getData(); + + if(chanIdx1 == chanIdx2 && startIdx1 >= startIdx2) { + return 0; + } + + if (startIdx1 > (int)timeSeries1.size() - (m_m+1)*scale || startIdx2 > (int)timeSeries2.size() - (m_m+1)*scale) { + return 0; + } + + for(int k = 0; k < m_m + 1; k++) { + + double coarseGrainedVal1 = 0; + double coarseGrainedVal2 = 0; + + for(int s = 0; s < scale; s++) { + coarseGrainedVal1 += timeSeries1[startIdx1+(k*scale)+s]; + coarseGrainedVal2 += timeSeries2[startIdx2+(k*scale)+s]; + } + + coarseGrainedVal1 /= (double)scale; + coarseGrainedVal2 /= (double)scale; + + if(fabs(coarseGrainedVal1 - coarseGrainedVal2) > m_r) { + if(k < m_m) return 0; + return 1; + } + } + return 2; +} + +void SampleEntropyCalculator::updateUnivariate(size_t scaleIdx, size_t chanIdx) { + // Update counts of similar vectors of queue N°chanIdx + int chanSize = m_signal[0][chanIdx].size(); + if(chanSize >= (m_m + 2) * (scaleIdx + 1)) { //otherwise the channel is too short for any calculation to be done + bool flag = false; + for(int newlyAddedVectIdx = m_leftOffIndexes[scaleIdx][chanIdx]; newlyAddedVectIdx <= (int)chanSize - (m_m+1) * ((int)scaleIdx+1) ; newlyAddedVectIdx += scaleIdx+1) { + + for(int vectIdx = newlyAddedVectIdx - (scaleIdx+1) ; vectIdx >= 0 ; vectIdx-=scaleIdx+1) { + flag = true; + + int similarityLevel = similarVectors(chanIdx, vectIdx, newlyAddedVectIdx, scaleIdx+1); + + if(similarityLevel == SIMILAR_LENGTH_M_PLUS_1) { + m_countM[scaleIdx][chanIdx].incrementAt(vectIdx); + m_countM1[scaleIdx][chanIdx].incrementAt(vectIdx); + } + + if(similarityLevel == SIMILAR_LENGTH_M) { + m_countM[scaleIdx][chanIdx].incrementAt(vectIdx); + } + } + } + if(flag) { + m_leftOffIndexes[scaleIdx][chanIdx] = chanSize - (m_m) * (scaleIdx+1); + } + } + + int totM = m_countM[scaleIdx][chanIdx].getTotal(); + int totM1 = m_countM1[scaleIdx][chanIdx].getTotal(); + + int a; + + if(totM == 0 || totM1 == 0) { // "infinite" entropy + // In theory, in that case, the entropy should be infinite. But to avoid setting it to an arbitrary high number, + // it is set to m_maxTheoriticalEntropy, which is higher than any value the entropy can reach when it's not infinite + m_univariateEntropy[scaleIdx][chanIdx] = m_maxTheoriticalEntropy; + } else { + m_univariateEntropy[scaleIdx][chanIdx] = -log((double)totM1/(double)totM); + } +} + +void SampleEntropyCalculator::updateMultivariate(size_t scaleIdx, size_t nbChannels) { + + int chanSize = m_signal[0][0].size(); + if(chanSize >= (m_m + 2) * (scaleIdx + 1)) { //otherwise the channel is too short for any calculation to be done + bool flag = false; + for (size_t newlyAddedVectChanIdx = 0 ; newlyAddedVectChanIdx < nbChannels; ++newlyAddedVectChanIdx) { + for(int newlyAddedVectIdx = m_leftOffIndexes[scaleIdx][newlyAddedVectChanIdx]; newlyAddedVectIdx <= (int)chanSize - (m_m+1) * ((int)scaleIdx+1) ; newlyAddedVectIdx += scaleIdx+1) { + + + for(size_t vectChanIdx = 0 ; vectChanIdx <= newlyAddedVectChanIdx; vectChanIdx++) { + for(int vectIdx = newlyAddedVectIdx ; vectIdx >= 0 ; vectIdx-=scaleIdx+1) { + + if((vectChanIdx < newlyAddedVectChanIdx && vectIdx <= newlyAddedVectIdx) || vectIdx <= newlyAddedVectIdx - scaleIdx) { + + flag = true; + + int similarityLevel = similarVectorsMultivariate(vectChanIdx, newlyAddedVectChanIdx, vectIdx, newlyAddedVectIdx, scaleIdx+1); + + if(similarityLevel == SIMILAR_LENGTH_M_PLUS_1) { + m_countM[scaleIdx][vectChanIdx].incrementAt(vectIdx); + m_countM1[scaleIdx][vectChanIdx].incrementAt(vectIdx); + } + + if(similarityLevel == SIMILAR_LENGTH_M) { + m_countM[scaleIdx][vectChanIdx].incrementAt(vectIdx); + } + + } + + } + } + } + + if(flag) { + m_leftOffIndexes[scaleIdx][newlyAddedVectChanIdx] = chanSize - (m_m) * (scaleIdx+1); + } + } + } + + int totM = 0; + int totM1 = 0; + + for(size_t chanIdx = 0; chanIdx < nbChannels; chanIdx++) { + totM += m_countM[scaleIdx][chanIdx].getTotal(); + totM1 += m_countM1[scaleIdx][chanIdx].getTotal(); + } + + if(totM == 0 || totM1 == 0) { // "infinite" entropy + // In theory, in that case, the entropy should be infinite. But to avoid setting it to an arbitrary high number, + // it is set to m_maxTheoriticalEntropy, which is higher than any value the entropy can reach when it's not infinite + m_multivariateEntropy[scaleIdx] = m_maxTheoriticalEntropy; + } else { + m_multivariateEntropy[scaleIdx] = -log((double)totM1/(double)totM); + + } + + +} + +void SampleEntropyCalculator::calculateUnivariate(double* &inputBuffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) { + bool mustUpdateEntropy = false; + + for(size_t sampleIdx = 0 ; sampleIdx < nbSamplesPerChannel; ++sampleIdx) { + + if(m_totSamplesCount + sampleIdx >= m_totSampCntAtLastUpdate + m_intervalTimeSize) { + m_totSampCntAtLastUpdate = m_totSamplesCount + sampleIdx; + mustUpdateEntropy = true; + } + for (size_t chanIdx = 0 ; chanIdx < nbChannels; ++ chanIdx) { + + // Update m_signal so it contains the latest m_timeWindow seconds of signal + m_signal[0][chanIdx].add(inputBuffer[chanIdx*nbSamplesPerChannel + sampleIdx]); + + for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) { + + m_countM[scaleIdx][chanIdx].add(0); + m_countM1[scaleIdx][chanIdx].add(0); + + // Remove samples older than m_timeWindow from the queue N°chanIdx + if (m_signal[0][chanIdx].size() > m_slidingWindowSize) { + if(m_leftOffIndexes[scaleIdx][chanIdx] != 0) { + m_leftOffIndexes[scaleIdx][chanIdx]--; + } + } + + if (mustUpdateEntropy) { + updateUnivariate(scaleIdx, chanIdx); + } + + outputMatrices[scaleIdx]->getBuffer()[chanIdx*nbSamplesPerChannel + sampleIdx] = m_univariateEntropy[scaleIdx][chanIdx]; + + } + + } + mustUpdateEntropy = false; + + } + m_totSamplesCount += nbSamplesPerChannel; +} + +void SampleEntropyCalculator::calculateMultivariate(double* &inputBuffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) { + bool mustUpdateEntropy = false; + + for(size_t sampleIdx = 0 ; sampleIdx < nbSamplesPerChannel; ++sampleIdx) { + + if(m_totSamplesCount + sampleIdx >= m_totSampCntAtLastUpdate + m_intervalTimeSize) { + m_totSampCntAtLastUpdate = m_totSamplesCount + sampleIdx; + mustUpdateEntropy = true; + } + for (size_t chanIdx = 0 ; chanIdx < nbChannels; ++ chanIdx) { + + // Update m_signal so it contains the latest m_timeWindow seconds of signal + m_signal[0][chanIdx].add(inputBuffer[chanIdx*nbSamplesPerChannel + sampleIdx]); + + for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) { + + m_countM[scaleIdx][chanIdx].add(0); + m_countM1[scaleIdx][chanIdx].add(0); + + // Remove samples older than m_timeWindow from the queue N°chanIdx + if (m_signal[0][chanIdx].size() > m_slidingWindowSize) { + if(m_leftOffIndexes[scaleIdx][chanIdx] != 0) { + m_leftOffIndexes[scaleIdx][chanIdx]--; + } + } + + } + } + + for(size_t scaleIdx = 0; scaleIdx < m_scale; scaleIdx++) { + if (mustUpdateEntropy) { + updateMultivariate(scaleIdx, nbChannels); + } + + outputMatrices[scaleIdx]->getBuffer()[sampleIdx] = m_multivariateEntropy[scaleIdx]; + } + + + mustUpdateEntropy = false; + + } + m_totSamplesCount += nbSamplesPerChannel; +} + + +} +} +} \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.hpp b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.hpp new file mode 100644 index 0000000000000000000000000000000000000000..dffeffe56f74c8cc71cd8b387446e451fa5ff4e4 --- /dev/null +++ b/plugins/processing/signal-processing/src/algorithms/entropy/SampleEntropyCalculator.hpp @@ -0,0 +1,81 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file SampleEntropyCalculator.hpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "AbstractEntropyCalculator.hpp" + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + +/// <summary> The class SampleEntropyCalculator describes one implementation of the Entropy Calculator abstract class that computes sample entropy. </summary> +class SampleEntropyCalculator : public EntropyCalculator { +public: + SampleEntropyCalculator(int m, double r, int scale = 1); + + void initialize(size_t slidingWindowSize, size_t intervalTimeSize, size_t nbChannels) override; + + /** + * @brief Updates m_univariateEntropy so it contains, for each channel, the values of the corresponding sample entropy + */ + void calculateUnivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) override; + /** + * @brief Updates m_multivariateEntropy so it contains the values of the multivariate sample entropy + */ + void calculateMultivariate(double* &buffer, size_t nbSamplesPerChannel, size_t nbChannels, std::vector<CMatrix*> outputMatrices) override; + + + +private: + int m_m; + double m_r; + + std::vector<std::vector<SlidingWindowCounter>> m_countM; + std::vector<std::vector<SlidingWindowCounter>> m_countM1; + + std::vector<std::vector<size_t>> m_leftOffIndexes; + double m_maxTheoriticalEntropy; + + enum SimilarityLevel {NOT_SIMILAR, SIMILAR_LENGTH_M, SIMILAR_LENGTH_M_PLUS_1}; + /** + * @brief Checks if vectors of channel chanIdx that start at startIdx1 and startIdx2 and have length m_m have a distance lower that m_r, for scale scale + */ + int similarVectors(size_t chanIdx, int startIdx1, int startIdx2, int scale); + int similarVectorsMultivariate(size_t chanIdx1, size_t chanIdx2, int startIdx1, int startIdx2, int scale); + + /** + * @brief Updates the values of the univariate entropy so they can be added to the output buffer + */ + void updateUnivariate(size_t scaleIdx, size_t chanIdx); + /** + * @brief Updates the values of the multivariate entropy so they can be added to the output buffer + */ + void updateMultivariate(size_t scaleIdx, size_t nbChannels); + +}; + +} +} +} \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.cpp b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.cpp new file mode 100644 index 0000000000000000000000000000000000000000..4c7ab6e47059aa02221441c2ba37730d2d3aea58 --- /dev/null +++ b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.cpp @@ -0,0 +1,71 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file SlidingWindowHelper.cpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "SlidingWindowHelper.hpp" + + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + +// ----------------- SlidingWindowChannel class ----------------- +SlidingWindowChannel::SlidingWindowChannel(size_t maxLength): SlidingWindowQueue<double>(maxLength) {} + +void SlidingWindowChannel::add(double value) { + if (m_data.size() > m_maxLength) { + m_data.pop_front(); // Remove the oldest element if at max length + } + m_data.push_back(value); // Add the new value +} + +// -----------------SlidingWindowCounter class ----------------- +SlidingWindowCounter::SlidingWindowCounter(size_t maxLength): SlidingWindowQueue<int>(maxLength), m_total(0) {} + +void SlidingWindowCounter::add(int value) { + if (m_data.size() > m_maxLength) { + m_total -= m_data.front(); + m_data.pop_front(); + } + m_data.push_back(value); + m_total += value; +} + +void SlidingWindowCounter::incrementAt(size_t index) { + if(index >= m_data.size()) { + throw std::invalid_argument("Index out of bounds"); + } else { + m_data[index]++; + m_total++; + } +} + +int SlidingWindowCounter::getTotal() const { + return m_total; +} + +} +} +} \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.hpp b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.hpp new file mode 100644 index 0000000000000000000000000000000000000000..d28fbe621c3735e0cc23b4f5e9fd1a9a26c24944 --- /dev/null +++ b/plugins/processing/signal-processing/src/algorithms/entropy/SlidingWindowHelper.hpp @@ -0,0 +1,75 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file SlidingWindowHelper.hpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "../../defines.hpp" +#include <toolkit/ovtk_all.h> + +#include <queue> + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + + +// SlidingWindowQueue abstract class +template <typename T> +class SlidingWindowQueue { +public: + SlidingWindowQueue(size_t maxLength) : m_maxLength(maxLength) {} + + size_t size() const { return m_data.size(); } + const std::deque<T>& getData() const { return m_data; } + + virtual void add(T value) = 0; + +protected: + size_t m_maxLength; + std::deque<T> m_data; +}; + +// SlidingWindowChannel class +class SlidingWindowChannel : public SlidingWindowQueue<double> { +public: + explicit SlidingWindowChannel(size_t maxLength); + + void add(double value) override; +}; + +// SlidingWindowCounter class +class SlidingWindowCounter : public SlidingWindowQueue<int> { +public: + explicit SlidingWindowCounter(size_t maxLength); + + void add(int value) override; + void incrementAt(size_t index); + int getTotal() const; +private: + int m_total; +}; + +} +} +} \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.cpp b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.cpp new file mode 100644 index 0000000000000000000000000000000000000000..06d2a6dddd46c23a87457a0552da46ce255045b7 --- /dev/null +++ b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.cpp @@ -0,0 +1,147 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file CBoxAlgorithmEntropyMeasure.cpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + + +#include <iomanip> +#include "CBoxAlgorithmEntropyMeasure.hpp" + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + +bool CBoxAlgorithmEntropyMeasure::initialize() { + m_timeWindow = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 0); + m_timeInterval = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 1); + m_m = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 2); + m_r = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 3); + m_scale = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 4); + m_isMultivariate = FSettingValueAutoCast(*this->getBoxAlgorithmContext(), 5); + + m_inputDecoder.initialize(*this, 0); + m_outputMatrices.resize(m_scale); + m_outputEncoders.resize(m_scale); + + for(int scale = 0; scale < m_scale; scale++) { + m_outputMatrices[scale] = new CMatrix(); + + m_outputEncoders[scale].initialize(*this, scale); + m_outputEncoders[scale].getInputMatrix().setReferenceTarget(m_outputMatrices[scale]); + m_outputEncoders[scale].getInputSamplingRate().setReferenceTarget(m_inputDecoder.getOutputSamplingRate()); + } + + m_entropyCalculator = new SampleEntropyCalculator(m_m, m_r, m_scale); + + std::cout << std::fixed; + std::cout << std::setprecision(16); + + + return true; +} + +bool CBoxAlgorithmEntropyMeasure::uninitialize() +{ + m_inputDecoder.uninitialize(); + for(int scale = 0; scale < m_scale; scale++) { + m_outputEncoders[scale].uninitialize(); + } + return true; +} + +bool CBoxAlgorithmEntropyMeasure::processInput(const size_t index) +{ + getBoxAlgorithmContext()->markAlgorithmAsReadyToProcess(); + return true; +} + + + +bool CBoxAlgorithmEntropyMeasure::process() +{ + IDynamicBoxContext& dynamicBoxContext = this->getDynamicBoxContext(); + + for (size_t i = 0; i < dynamicBoxContext.getInputChunkCount(0); ++i) { + + m_inputDecoder.decode(i); + + const uint64_t tStart = dynamicBoxContext.getInputChunkStartTime(0, i); + const uint64_t tEnd = dynamicBoxContext.getInputChunkEndTime(0, i); + + CMatrix* iMatrix = m_inputDecoder.getOutputMatrix(); + + const size_t nbChannels = iMatrix->getDimensionSize(0); + const size_t nbSamplesPerChannel = iMatrix->getDimensionSize(1); + + + if (m_inputDecoder.isHeaderReceived()) { + + m_samplingRate = m_inputDecoder.getOutputSamplingRate(); + size_t maxChanSize = floor(m_samplingRate * m_timeWindow); + size_t timeIntervalSize = floor(m_samplingRate * m_timeInterval); + + // initialize entropy calculator + m_entropyCalculator->initialize(maxChanSize, timeIntervalSize, nbChannels); + + // Pass the header to the next boxes, by encoding a header: + for(int scale = 0; scale < m_scale; scale++) { + if(!m_isMultivariate) { + m_outputMatrices[scale]->resize(nbChannels,nbSamplesPerChannel); + } else { + m_outputMatrices[scale]->resize(1, nbSamplesPerChannel); + } + m_outputEncoders[scale].encodeHeader(); + } + } + + if (m_inputDecoder.isBufferReceived()) { + + double* inputBuffer = iMatrix->getBuffer(); + + if(!m_isMultivariate) { + m_entropyCalculator->calculateUnivariate(inputBuffer, nbSamplesPerChannel, nbChannels, m_outputMatrices); + } else { + m_entropyCalculator-> calculateMultivariate(inputBuffer, nbSamplesPerChannel, nbChannels, m_outputMatrices); + } + + for(int scale = 0; scale < m_scale; scale++) { + m_outputEncoders[scale].encodeBuffer(); + } + + } + + if (m_inputDecoder.isEndReceived()) { + for(int scale = 0; scale < m_scale; scale++) + m_outputEncoders[scale].encodeEnd(); + } + + for(int scale = 0; scale < m_scale; scale++) { + dynamicBoxContext.markOutputAsReadyToSend(scale, tStart, tEnd); + } + } + + return true; +} + +} // namespace SignalProcessing +} // namespace Plugins +} // namespace OpenViBE \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.hpp b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.hpp new file mode 100644 index 0000000000000000000000000000000000000000..2f9b55694ee4a289a84aba5d1ba880333fa1afaa --- /dev/null +++ b/plugins/processing/signal-processing/src/box-algorithms/CBoxAlgorithmEntropyMeasure.hpp @@ -0,0 +1,169 @@ +///------------------------------------------------------------------------------------------------- +/// +/// \file CBoxAlgorithmEntropyMeasure.hpp +/// \brief Classes of the Box Entropy Measures. +/// \author Axel Bouneau (Inria). +/// \version 1.0. +/// \date Mon Jan 29 10:00:00 2024. +/// \Copyright (C) 2024 Inria +/// +/// This program is free software: you can redistribute it and/or modify +/// it under the terms of the GNU Affero General Public License as published by +/// the Free Software Foundation, either version 3 of the License, or +/// (at your option) any later version. +/// +/// This program is distributed in the hope that it will be useful, +/// but WITHOUT ANY WARRANTY; without even the implied warranty of +/// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +/// GNU Affero General Public License for more details. +/// +/// You should have received a copy of the GNU Affero General Public License +/// along with this program. If not, see <http://www.gnu.org/licenses/>. +/// +///------------------------------------------------------------------------------------------------- + +#pragma once + +#include "../defines.hpp" +#include <toolkit/ovtk_all.h> + +#include "../algorithms/entropy/SampleEntropyCalculator.hpp" + + +// The unique identifiers for the box and its descriptor. +// Identifier are randomly chosen by the skeleton-generator. +#define OV_AttributeId_Box_FlagIsUnstable OpenViBE::CIdentifier(0x666FFFFF, 0x666FFFFF) + +namespace OpenViBE { +namespace Plugins { +namespace SignalProcessing { + + +/// <summary> The class CBoxAlgorithmEntropyMeasure describes the box Entropy Measure. </summary> +class CBoxAlgorithmEntropyMeasure final : virtual public Toolkit::TBoxAlgorithm<IBoxAlgorithm> +{ +public: + void release() override { delete this; } + + bool initialize() override; + bool uninitialize() override; + + bool processInput(const size_t index) override; + + bool process() override; + + + // As we do with any class in openvibe, we use the macro below to associate this box to an unique identifier. + // The inheritance information is also made available, as we provide the superclass Toolkit::TBoxAlgorithm < IBoxAlgorithm > + _IsDerivedFromClass_Final_(Toolkit::TBoxAlgorithm<IBoxAlgorithm>, OVP_ClassId_BoxAlgorithm_EntropyMeasure) + +protected: + // Input decoder: + Toolkit::TSignalDecoder<CBoxAlgorithmEntropyMeasure> m_inputDecoder; + // Output decoder: + std::vector<Toolkit::TSignalEncoder<CBoxAlgorithmEntropyMeasure>> m_outputEncoders; + std::vector<CMatrix*> m_outputMatrices; + +private: + double m_samplingRate = 0.0; + + + // box parameters + double m_timeWindow = 0.0; + double m_timeInterval = 0.0; + + // m is the length of the pattern vectors + int m_m = 0; + + // r is the range below which two vectors are considered similar + double m_r = 0; + + // m_scale is the scale wanted for entropy calculation. 1 for normal entropy ; >1 for multiscale entropy + int m_scale = 1; + + bool m_isMultivariate = false; + + EntropyCalculator* m_entropyCalculator; +}; + +/// <summary> The class CBoxAlgorithmEntropyMeasureListener allows to change the amount of outputs of the entropy measure box, depending on the scale parameter chosen by the user. </summary> +class CBoxAlgorithmEntropyMeasureListener final : public Toolkit::TBoxListener<IBoxListener> +{ +public: + bool onSettingValueChanged(Kernel::IBox& box, const size_t index) override + { + if (index == 4) { + CString scaleStr; + box.getSettingValue(index, scaleStr); + + int wantedScale = atoi(scaleStr); + int currentScale = box.getOutputCount(); + + if(wantedScale < 1) wantedScale = 1; + if(wantedScale > 20) wantedScale = 20; + + if (wantedScale > currentScale) { + for (int i = currentScale; i < wantedScale; ++i) { + char name[50]; + std::sprintf(name, "Entropy scale %d", i+1); + + box.addOutput(name, OV_TypeId_Signal); + } + // If wantedScale is less than currentScale, remove outputs + } else if (wantedScale < currentScale) { + for (int i = currentScale; i > wantedScale && i > 1; --i) { + box.removeOutput(box.getOutputCount() - 1); + } + } + } + + return true; + } +private: + _IsDerivedFromClass_Final_(Toolkit::TBoxListener<IBoxListener>, CIdentifier::undefined()) +}; + +/// <summary> Descriptor of the box Entropy Measure. </summary> +class CBoxAlgorithmEntropyMeasureDesc final : virtual public IBoxAlgorithmDesc +{ +public: + void release() override { } + + CString getName() const override { return CString("Entropy Measure"); } + CString getAuthorName() const override { return CString("Axel Bouneau"); } + CString getAuthorCompanyName() const override { return CString("Inria"); } + CString getShortDescription() const override { return CString("Computes the Entropy of an EEG signal."); } + CString getDetailedDescription() const override { return CString("Computes the sample entropy of the input signal. Can be set to compute multivariate and/or multiscale sample entropy."); } + CString getCategory() const override { return CString("Measures"); } + CString getVersion() const override { return CString("1.0"); } + CString getStockItemName() const override { return CString("gtk-remove"); } + + CIdentifier getCreatedClass() const override { return OVP_ClassId_BoxAlgorithm_EntropyMeasure; } + IPluginObject* create() override { return new CBoxAlgorithmEntropyMeasure; } + IBoxListener* createBoxListener() const override { return new CBoxAlgorithmEntropyMeasureListener; } + + + bool getBoxPrototype(Kernel::IBoxProto& prototype) const override + { + prototype.addInput("Signal", OV_TypeId_Signal); + + prototype.addOutput("Entropy", OV_TypeId_Signal); + + prototype.addSetting("Time window (s)", OV_TypeId_Float, "10.0"); + prototype.addSetting("Time interval (s)", OV_TypeId_Float, "0.0"); + prototype.addSetting("m (pattern length)", OV_TypeId_Integer, "2"); + prototype.addSetting("r (tolerance)", OV_TypeId_Float, "0.2"); + + prototype.addSetting("Scale", OV_TypeId_Integer, "1"); + prototype.addSetting("Multivariate", OV_TypeId_Boolean, "false"); + + + return true; + } + _IsDerivedFromClass_Final_(IBoxAlgorithmDesc, OVP_ClassId_BoxAlgorithm_EntropyMeasureDesc) +}; + + +} // namespace SignalProcessing +} // namespace Plugins +} // namespace OpenViBE \ No newline at end of file diff --git a/plugins/processing/signal-processing/src/defines.hpp b/plugins/processing/signal-processing/src/defines.hpp index e893a4bc88af8570b9950362ccb52c5253015ea9..96f70ac186e0bbe7a1f5a852acf886a46b701963 100644 --- a/plugins/processing/signal-processing/src/defines.hpp +++ b/plugins/processing/signal-processing/src/defines.hpp @@ -56,6 +56,8 @@ #define OVP_ClassId_BoxAlgorithm_ConnectivitySpectrumExtractDesc OpenViBE::CIdentifier(0xb6e4b7c1, 0x7331662d) #define OVP_ClassId_BoxAlgorithm_PulseRateCalculator OpenViBE::CIdentifier(0x034466a7, 0x8059bcf3) #define OVP_ClassId_BoxAlgorithm_PulseRateCalculatorDesc OpenViBE::CIdentifier(0x04d32034, 0x096c0b42) +#define OVP_ClassId_BoxAlgorithm_EntropyMeasure OpenViBE::CIdentifier(0x46911275, 0xEC146FA3) +#define OVP_ClassId_BoxAlgorithm_EntropyMeasureDesc OpenViBE::CIdentifier(0xC7482EBA, 0x31772D60) #define Box_EpochVariance OpenViBE::CIdentifier(0x335384EA, 0x88C917D0) #define Box_EpochVarianceDesc OpenViBE::CIdentifier(0xA15EAEC5, 0xAB0CE730) diff --git a/plugins/processing/signal-processing/src/main.cpp b/plugins/processing/signal-processing/src/main.cpp index 2b27d3d3de1439a3e31761e7f933f28108baf13a..28a96bcf1bd1b77d574e7eaf458574c23a7762aa 100644 --- a/plugins/processing/signal-processing/src/main.cpp +++ b/plugins/processing/signal-processing/src/main.cpp @@ -24,7 +24,7 @@ #include "box-algorithms/connectivity/CBoxAlgorithmConnectivitySpectrumExtract.hpp" #include "box-algorithms/CBoxAlgorithmPulseRateCalculator.hpp" - +#include "box-algorithms/CBoxAlgorithmEntropyMeasure.hpp" namespace OpenViBE { namespace Plugins { @@ -52,7 +52,8 @@ OVP_Declare_Begin() OVP_Declare_New(CBoxAlgorithmHilbertDesc) OVP_Declare_New(CBoxIFFTDesc) - OVP_Declare_New(CBoxAlgorithmPulseRateCalculatorDesc); + OVP_Declare_New(CBoxAlgorithmPulseRateCalculatorDesc) + OVP_Declare_New(CBoxAlgorithmEntropyMeasureDesc) #if defined(TARGET_HAS_ThirdPartyFFTW3) diff --git a/plugins/processing/signal-processing/test/DartTestfile.txt b/plugins/processing/signal-processing/test/DartTestfile.txt index 5d100a81069107a077bdb85fe74914eb1569efc9..d479e2f9948223cacd7c66d6d43e2942f28d8d0d 100644 --- a/plugins/processing/signal-processing/test/DartTestfile.txt +++ b/plugins/processing/signal-processing/test/DartTestfile.txt @@ -17,4 +17,5 @@ validation_test_with_csv(scenarios-tests Discrete-Wavelet-Transform) validation_test_with_csv(scenarios-tests Discrete-Wavelet-Transform-Inverse) validation_test_with_csv(scenarios-tests ConnectivityWelch) validation_test_with_csv(scenarios-tests ConnectivityMVAR) -validation_test_with_csv(scenarios-tests Pulse-Rate-Calculator) \ No newline at end of file +validation_test_with_csv(scenarios-tests Pulse-Rate-Calculator) +validation_test_with_csv(scenarios-tests Entropy-Measure) \ No newline at end of file diff --git a/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-input.csv b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-input.csv new file mode 100644 index 0000000000000000000000000000000000000000..b75a774cf0c0ab39d796c09f8fe3e961fc7c1e28 --- /dev/null +++ b/plugins/processing/signal-processing/test/scenarios-tests/Entropy-Measure-input.csv @@ -0,0 +1,5001 @@ +Time:500Hz,Epoch,FP1,Event Id,Event Date,Event Duration +0,0,0.53766714,,, +0.002,0,1.833885,,, +0.004,0,-2.2588469,,, +0.006,0,0.86217332,,, +0.008,0,0.31876524,,, +0.01,0,-1.3076883,,, +0.012,0,-0.43359202,,, +0.014,0,0.34262447,,, +0.016,0,3.5783969,,, +0.018,0,2.769437,,, +0.02,0,-1.3498869,,, +0.022,0,3.0349235,,, 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<Value>Entropy-Measure</Value> + </Setting> + </Settings> + <Inputs></Inputs> + <Outputs></Outputs> + <Boxes> + <Box> + <Identifier>(0x00000cd2, 0x0000577b)</Identifier> + <Name>Entropy Measure</Name> + <AlgorithmClassIdentifier>(0x46911275, 0xec146fa3)</AlgorithmClassIdentifier> + <Inputs> + <Input> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Signal</Name> + </Input> + </Inputs> + <Outputs> + <Output> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Entropy</Name> + </Output> + <Output> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Entropy scale 2</Name> + </Output> + <Output> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Entropy scale 3</Name> + </Output> + <Output> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Entropy scale 4</Name> + </Output> + </Outputs> + <Settings> + <Setting> + <TypeIdentifier>(0x512a166f, 0x5c3ef83f)</TypeIdentifier> + <Name>Time window (s)</Name> + <DefaultValue>10.0</DefaultValue> + <Value>10</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x512a166f, 0x5c3ef83f)</TypeIdentifier> + <Name>Time interval (s)</Name> + <DefaultValue>0.0</DefaultValue> + <Value>0</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier> + <Name>m (pattern length)</Name> + <DefaultValue>2</DefaultValue> + <Value>2</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x512a166f, 0x5c3ef83f)</TypeIdentifier> + <Name>r (tolerance)</Name> + <DefaultValue>0.2</DefaultValue> + <Value>0.2</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier> + <Name>Scale</Name> + <DefaultValue>1</DefaultValue> + <Value>4</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier> + <Name>Multivariate</Name> + <DefaultValue>false</DefaultValue> + <Value>false</Value> + <Modifiability>false</Modifiability> + </Setting> + </Settings> + <Attributes> + <Attribute> + <Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier> + <Value>-128</Value> + </Attribute> + <Attribute> + <Identifier>(0x207c9054, 0x3c841b63)</Identifier> + <Value>144</Value> + </Attribute> + <Attribute> + <Identifier>(0x4e7b798a, 0x183beafb)</Identifier> + <Value>(0x0c0e7894, 0xa8094f4f)</Value> + </Attribute> + <Attribute> + <Identifier>(0xc80ce8af, 0xf699f813)</Identifier> + <Value>1</Value> + </Attribute> + <Attribute> + <Identifier>(0xce18836a, 0x9c0eb403)</Identifier> + <Value>6</Value> + </Attribute> + <Attribute> + <Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier> + <Value>1</Value> + </Attribute> + </Attributes> + </Box> + <Box> + <Identifier>(0x0000290e, 0x00005050)</Identifier> + <Name>Timeout</Name> + <AlgorithmClassIdentifier>(0x24fcd292, 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<Value>OVTK_StimulationId_Label_00</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0xcc14d8d6, 0xf27ecb73)</TypeIdentifier> + <Name>Action to perform</Name> + <DefaultValue>Pause</DefaultValue> + <Value>Stop</Value> + <Modifiability>false</Modifiability> + </Setting> + </Settings> + <Attributes> + <Attribute> + <Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier> + <Value>-16</Value> + </Attribute> + <Attribute> + <Identifier>(0x207c9054, 0x3c841b63)</Identifier> + <Value>320</Value> + </Attribute> + <Attribute> + <Identifier>(0x4e7b798a, 0x183beafb)</Identifier> + <Value>(0x568d148e, 0x650792b3)</Value> + </Attribute> + <Attribute> + <Identifier>(0xce18836a, 0x9c0eb403)</Identifier> + <Value>2</Value> + </Attribute> + <Attribute> + <Identifier>(0xcfad85b0, 0x7c6d841c)</Identifier> + <Value>1</Value> + </Attribute> + </Attributes> + </Box> + <Box> + <Identifier>(0x000042fc, 0x00005161)</Identifier> + <Name>CSV File Writer</Name> + <AlgorithmClassIdentifier>(0x428375e8, 0x325f2db9)</AlgorithmClassIdentifier> + <Inputs> + <Input> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Input stream</Name> + </Input> + <Input> + <TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier> + <Name>Stimulations stream</Name> + </Input> + </Inputs> + <Settings> + <Setting> + <TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier> + <Name>Filename</Name> + <DefaultValue>record-[$core{date}-$core{time}].csv</DefaultValue> + <Value>${Player_ScenarioDirectory}/$var{I-O File Names}-output.csv</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x007deef9, 0x2f3e95c6)</TypeIdentifier> + <Name>Precision</Name> + <DefaultValue>10</DefaultValue> + <Value>10</Value> + <Modifiability>false</Modifiability> + </Setting> + <Setting> + <TypeIdentifier>(0x2cdb2f0b, 0x12f231ea)</TypeIdentifier> + <Name>Append data</Name> + <DefaultValue>false</DefaultValue> + <Value>false</Value> + 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0x000007af)</Identifier> + <Name>CSV File Reader</Name> + <AlgorithmClassIdentifier>(0x336a3d9a, 0x753f1ba4)</AlgorithmClassIdentifier> + <Outputs> + <Output> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Output stream</Name> + </Output> + <Output> + <TypeIdentifier>(0x6f752dd0, 0x082a321e)</TypeIdentifier> + <Name>Output stimulation</Name> + </Output> + </Outputs> + <Settings> + <Setting> + <TypeIdentifier>(0x330306dd, 0x74a95f98)</TypeIdentifier> + <Name>Filename</Name> + <DefaultValue></DefaultValue> + <Value>${Player_ScenarioDirectory}/$var{I-O File Names}-input.csv</Value> + <Modifiability>false</Modifiability> + </Setting> + </Settings> + <Attributes> + <Attribute> + <Identifier>(0x1fa7a38f, 0x54edbe0b)</Identifier> + <Value>-192</Value> + </Attribute> + <Attribute> + <Identifier>(0x207c9054, 0x3c841b63)</Identifier> + <Value>144</Value> + </Attribute> + <Attribute> + <Identifier>(0x30a4e5c9, 0x83502953)</Identifier> + <Value></Value> + </Attribute> + <Attribute> + <Identifier>(0x4e7b798a, 0x183beafb)</Identifier> + <Value>(0xa9cdc629, 0xb153eb33)</Value> + </Attribute> + <Attribute> + <Identifier>(0xc80ce8af, 0xf699f813)</Identifier> + <Value>2</Value> + </Attribute> + <Attribute> + <Identifier>(0xce18836a, 0x9c0eb403)</Identifier> + <Value>1</Value> + </Attribute> + </Attributes> + </Box> + <Box> + <Identifier>(0x00006878, 0x000009e3)</Identifier> + <Name>Signal Merger</Name> + <AlgorithmClassIdentifier>(0x4bf9326f, 0x75603102)</AlgorithmClassIdentifier> + <Inputs> + <Input> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Input 1</Name> + </Input> + <Input> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Input 2</Name> + </Input> + <Input> + <Identifier>(0xe991e469, 0x79d3635c)</Identifier> + <TypeIdentifier>(0x5ba36127, 0x195feae1)</TypeIdentifier> + <Name>Input 3</Name> + </Input> + <Input> + <Identifier>(0xe1d0f6d2, 0x9f7af780)</Identifier> + <TypeIdentifier>(0x5ba36127, 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<BoxOutputIndex>0</BoxOutputIndex> + </Source> + <Target> + <BoxIdentifier>(0x000041a1, 0x00003606)</BoxIdentifier> + <BoxInputIndex>0</BoxInputIndex> + </Target> + </Link> + <Link> + <Identifier>(0x0000565b, 0x00006a8c)</Identifier> + <Source> + <BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier> + <BoxOutputIndex>2</BoxOutputIndex> + </Source> + <Target> + <BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier> + <BoxInputIdentifier>(0xe991e469, 0x79d3635c)</BoxInputIdentifier> + </Target> + </Link> + <Link> + <Identifier>(0x00006367, 0x000006ec)</Identifier> + <Source> + <BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier> + <BoxOutputIndex>1</BoxOutputIndex> + </Source> + <Target> + <BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier> + <BoxInputIndex>1</BoxInputIndex> + </Target> + </Link> + <Link> + <Identifier>(0x00006bf4, 0x000069ea)</Identifier> + <Source> + <BoxIdentifier>(0x00000cd2, 0x0000577b)</BoxIdentifier> + <BoxOutputIndex>0</BoxOutputIndex> + </Source> + <Target> + <BoxIdentifier>(0x00006878, 0x000009e3)</BoxIdentifier> + <BoxInputIndex>0</BoxInputIndex> + </Target> + </Link> + </Links> + <Comments></Comments> + <Metadata> + <Entry> + <Identifier>(0x00007a14, 0x000060c9)</Identifier> + <Type>(0x3bcce5d2, 0x43f2d968)</Type> + <Data>[{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"height":320,"identifier":"(0x0000381e, 0x000065b2)","name":"Default window","parentIdentifier":"(0xffffffff, 0xffffffff)","type":1,"width":480},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":1,"identifier":"(0x00002f66, 0x000056ec)","index":0,"name":"Default tab","parentIdentifier":"(0x0000381e, 0x000065b2)","type":2},{"boxIdentifier":"(0xffffffff, 0xffffffff)","childCount":0,"identifier":"(0x00001e9c, 0x00006839)","index":0,"name":"Empty","parentIdentifier":"(0x00002f66, 0x000056ec)","type":0}]</Data> + </Entry> + </Metadata> +</OpenViBE-Scenario> \ No newline at end of file