nymea-plugins/texasinstruments/sensorfilter.cpp

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/* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * *
*
* Copyright 2013 - 2020, nymea GmbH
* Contact: contact@nymea.io
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* reproduction, publication, editing and translation, are reserved. The use of
* this project is subject to the terms of a license agreement to be concluded
* with nymea GmbH in accordance with the terms of use of nymea GmbH, available
* under https://nymea.io/license
*
* GNU Lesser General Public License Usage
* Alternatively, this project may be redistributed and/or modified under the
* terms of the GNU Lesser General Public License as published by the Free
* Software Foundation; version 3. This project 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
* Lesser General Public License for more details.
*
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* along with this project. If not, see <https://www.gnu.org/licenses/>.
*
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#include "sensorfilter.h"
#include <QDebug>
SensorFilter::SensorFilter(Type filterType, QObject *parent) :
QObject(parent),
m_filterType(filterType)
{
}
float SensorFilter::filterValue(float value)
{
float resultValue = value;
switch (m_filterType) {
case TypeLowPass:
resultValue = lowPassFilterValue(value);
break;
case TypeHighPass:
resultValue = highPassFilterValue(value);
break;
case TypeAverage:
resultValue = averageFilterValue(value);
break;
default:
break;
}
return resultValue;
}
bool SensorFilter::isReady() const
{
// Note: filter is ready once 10% of window filled
return m_inputData.size() >= m_filterWindowSize * 0.1;
}
void SensorFilter::reset()
{
m_averageSum = 0;
m_inputData.clear();
}
SensorFilter::Type SensorFilter::filterType() const
{
return m_filterType;
}
QVector<float> SensorFilter::inputData() const
{
return m_inputData;
}
QVector<float> SensorFilter::outputData() const
{
return m_outputData;
}
uint SensorFilter::windowSize() const
{
return m_filterWindowSize;
}
void SensorFilter::setFilterWindowSize(uint windowSize)
{
Q_ASSERT_X(windowSize > 0, "value out of range", "The filter window size must be bigger than 0");
m_filterWindowSize = windowSize;
}
float SensorFilter::lowPassAlpha() const
{
return m_lowPassAlpha;
}
void SensorFilter::setLowPassAlpha(float alpha)
{
Q_ASSERT_X(alpha > 0 && alpha <= 1, "value out of range", "The alpha low pass filter value must be [ 0 < alpha <= 1 ]");
m_lowPassAlpha = alpha;
}
float SensorFilter::highPassAlpha() const
{
return m_highPassAlpha;
}
void SensorFilter::setHighPassAlpha(float alpha)
{
Q_ASSERT_X(alpha > 0 && alpha <= 1, "value out of range", "The alpha high pass filter value must be [ 0 < alpha <= 1 ]");
m_highPassAlpha = alpha;
}
void SensorFilter::addInputValue(float value)
{
m_inputData.append(value);
if (static_cast<uint>(m_inputData.size()) > m_filterWindowSize) {
m_inputData.removeFirst();
}
}
float SensorFilter::lowPassFilterValue(float value)
{
addInputValue(value);
// Check if we have enough data for filtering
if (m_inputData.size() < 2) {
return value;
}
QVector<float> outputData;
outputData.append(m_inputData.at(0));
for (int i = 1; i < m_inputData.size(); i++) {
// y[i] := y[i-1] + α * (x[i] - y[i-1])
outputData.append(outputData.at(i - 1) + m_lowPassAlpha * (m_inputData.at(i) - outputData.at(i - 1)));
}
m_outputData = outputData;
return m_outputData.last();
}
float SensorFilter::highPassFilterValue(float value)
{
addInputValue(value);
// Check if we have enough data for filtering
if (m_inputData.size() < 2) {
return value;
}
QVector<float> outputData;
outputData.append(m_inputData.at(0));
for (int i = 1; i < m_inputData.size(); i++) {
// y[i] := α * y[i-1] + α * (x[i] - x[i-1])
outputData.append(m_highPassAlpha * outputData.at(i - 1) + m_highPassAlpha * (m_inputData.at(i) - m_inputData.at(i - 1)));
}
m_outputData = outputData;
return m_outputData.last();
}
float SensorFilter::averageFilterValue(float value)
{
if (m_inputData.isEmpty()) {
addInputValue(value);
m_averageSum = value;
return value;
}
if (static_cast<uint>(m_inputData.size()) >= m_filterWindowSize) {
m_averageSum -= m_inputData.takeFirst();
}
addInputValue(value);
m_averageSum += value;
return m_averageSum / m_inputData.size();
}