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FilterKernel

Namespace: RTPROCESSINGLIB  ·  Library: DSP Library

Python equivalent

mne.filter.create_filter in MNE-Python.

#include <dsp/filterkernel.h>

class UTILSLIB::FilterKernel

The FilterKernel class provides methods to create/design a FIR filter kernel.

The FilterKernel class provides methods to create/design a FIR filter kernel

Public Methods​

FilterKernel()​

FilterKernel creates a default FilterKernel object.

FilterKernel(sFilterName, iFilterType, iOrder, dCenterfreq, dBandwidth, dParkswidth, dSFreq, iDesignMethod)​

Constructs a FilterKernel object.

Parameters:

  • sFilterName : const QString & Defines the name of the generated filter.

  • type Tyep of the filter: LPF, HPF, BPF, NOTCH (from enum FilterType).

  • iOrder : int Represents the order of the filter, the higher the higher is the stopband attenuation.

  • dCenterfreq : double Determines the center of the frequency - normed to sFreq/2 (nyquist).

  • dBandwidth : double Ignored if FilterType is set to LPF,HPF. if NOTCH/BPF: bandwidth of stop-/passband - normed to sFreq/2 (nyquist).

  • dParkswidth : double Determines the width of the filter slopes (steepness) - normed to sFreq/2 (nyquist).

  • dSFreq : double The sampling frequency.

  • designMethod Specifies the design method to use. Choose between Cosind and Tschebyscheff.

prepareFilter(iDataSize)​

Prepares a filter kernel to be used wiht a specific data block length.

This is favorable to call before filtering, in order to avoid transforming the filter coefficients anew during filtering. This functions was introduced since one does not always know the data length of the data blocks to be filtered when designing the filter.

Parameters:

  • iDataSize : int The data size to setup the filters to.

applyConvFilter(vecData, bKeepOverhead)​

Applies the current filter to the input data using convolution in time domain.

Parameters:

  • vecData : const Eigen::RowVectorXd & Holds the data to be filtered.

  • bKeepOverhead : bool Whether the result should still include the overhead information in front and back of the data. Default is set to false.

Returns:

  • Eigen::RowVectorXd — the filtered data in form of a RowVectorXd.

applyFftFilter(vecData, bKeepOverhead)​

Applies the current filter to the input data using multiplication in frequency domain.

Parameters:

  • vecData : Eigen::RowVectorXd & Holds the data to be filtered. Gets overwritten with its filtered result.

  • bKeepOverhead : bool Whether the result should still include the overhead information in front and back of the data. Default is set to false.

Returns:

  • void — the filtered data in form of a RowVectorXd.

getName()​

setName(sFilterName)​

getSamplingFrequency()​

setSamplingFrequency(dSFreq)​

getFilterOrder()​

setFilterOrder(iOrder)​

getCenterFrequency()​

setCenterFrequency(dCenterFreq)​

getBandwidth()​

setBandwidth(dBandwidth)​

getParksWidth()​

setParksWidth(dParksWidth)​

getHighpassFreq()​

setHighpassFreq(dHighpassFreq)​

getLowpassFreq()​

setLowpassFreq(dLowpassFreq)​

getCoefficients()​

setCoefficients(vecCoeff)​

getFftCoefficients()​

setFftCoefficients(vecFftCoeff)​

getDesignMethod()​

setDesignMethod(iDesignMethod)​

getFilterType()​

setFilterType(iFilterType)​

getShortDescription()​

Example​

Source: src/examples/ex_filtering/main.cpp

#include <iostream>
#include <vector>
#include <math.h>

#include <fiff/fiff.h>

#include <dsp/filterkernel.h>
#include <utils/generics/mne_logger.h>

#include <dsp/rt/rt_filter.h>

//=============================================================================================================
// QT INCLUDES
//=============================================================================================================

#include <QtCore/QCoreApplication>
#include <QFile>
#include <QCommandLineParser>

//=============================================================================================================
// USED NAMESPACES
//=============================================================================================================

using namespace FIFFLIB;
using namespace UTILSLIB;
using namespace RTPROCESSINGLIB;
using namespace Eigen;

//=============================================================================================================
// MAIN
//=============================================================================================================

//=============================================================================================================
/**
 * The function main marks the entry point of the program.
 * By default, main has the storage class extern.
 *
 * @param[in] argc (argument count) is an integer that indicates how many arguments were entered on the command line when the program was started.
 * @param[in] argv (argument vector) is an array of pointers to arrays of character objects. The array objects are null-terminated strings, representing the arguments that were entered on the command line when the program was started.
 * @return the value that was set to exit() (which is 0 if exit() is called via quit()).
 */
int main(int argc, char *argv[])
{
    qInstallMessageHandler(MNELogger::customLogWriter);
    QCoreApplication a(argc, argv);

    // Command Line Parser
    QCommandLineParser parser;
    parser.setApplicationDescription("Read Write Raw Example");
    parser.addHelpOption();

    QCommandLineOption inputOption("fileIn", "The input file <in>.", "in", QCoreApplication::applicationDirPath() + "/../resources/data/MNE-sample-data/MEG/sample/sample_audvis_raw.fif");
    QCommandLineOption outputOption("fileOut", "The output file <out>.", "out", QCoreApplication::applicationDirPath() + "/../resources/data/MNE-sample-data/MEG/sample/sample_audvis_filt_raw.fif");

    parser.addOption(inputOption);
    parser.addOption(outputOption);

    parser.process(a);

    // Init data loading and writing
    QFile fileIn(parser.value(inputOption));
    QFile fileOut(parser.value(outputOption));

    FiffRawData::SPtr pRaw = FiffRawData::SPtr::create(fileIn);

    // Only filter MEG and EEG channels
    RowVectorXi picks = pRaw->info.pick_types(true, false, false);

    // Filtering
    printf("Filtering...");
    if(RTPROCESSINGLIB::filterFile(fileOut,
                                   pRaw,
                                   FilterKernel::m_filterTypes.indexOf(FilterParameter("BPF")),
                                   10,
                                   10,
                                   0.1,
                                   pRaw->info.sfreq,
                                   1024,
                                   UTILSLIB::FilterKernel::m_designMethods.indexOf(FilterParameter("Cosine")),
                                   picks)) {
        printf("[done]\n");
    } else {
        printf("[failed]\n");
    }

    return 0;
}

Authors of this file​