Mathematical library for calculating the signal spectrum
The main functionality is the calculation of raw spectrum values and the calculation of EEG spectrum values.
Working with the library is possible in iterative mode (adding new data to the internal buffer, calculating spectrum values) and in one-time spectrum calculation mode for a given array. When working in the iterative mode, the spectrum is calculated with the frequency set during initialization.
Download from [GitHub](https://github.com/BrainbitLLC/spectrum-lib-cpp) all folders and add .dll to your project by your preferred way.
Download from [GitHub](https://github.com/BrainbitLLC/spectrum-lib-cpp) and add .so from folder `linux_x86_64` to your project by your preferred way.
Library buit on Astra Linux CE 2.12.46, kernel 5.15.0-70-generic. Arch: x86_64 GNU/Linux
```
user@astra:~$ ldd --version
ldd (Debian GLIBC 2.28-10+deb10u1) 2.28
Copyright (C) 2018 Free Software Foundation, Inc.
This is free software; see the source for copying conditions. There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.
Written by Roland McGrath and Ulrich Drepper.
```
That library depends from others library, for instance:
```
linux-vdso.so.1
libblkid.so.1
libc++.so.1
libc++abi.so.1
libc.so.6
libdl.so.2
libffi.so.6
libgcc_s.so.1
libgio-2.0.so.0
libglib-2.0.so.0
libgmodule-2.0.so.0
libgobject-2.0.so.0
libm.so.6
libmount.so.1
libpcre.so.3
libpthread.so.0
libresolv.so.2
librt.so.1
libselinux.so.1
libstdc++.so.6
libudev.so.1
libuuid.so.1
libz.so.1
ld-linux-x86-64.so.2
```
If you are using a OS other than ours, these dependencies will be required for the library. You can download dependencies from [here](https://github.com/BrainbitLLC/linux_neurosdk2/tree/main/dependencies).
The Android version is designed for APIs >= 21.
Neurosdk for android is distributed using JitPack as an aar library. Here is an example of adding SDK to an AndroidStudio project using gradle:
Add to `build.gradle` of project:
```
allprojects {
repositories {
...
maven { url 'https://jitpack.io' }
}
}
```
and to `build.gradle` of app:
```
dependencies {
implementation 'com.github.BrainbitLLC:SpectrumLib:version'
}
```
To prevent build errors add to build.gradle this settings:
```groovy
android {
packagingOptions {
pickFirst 'lib/x86_64/libc++_shared.so'
pickFirst 'lib/x86_64/libfilters.so'
pickFirst 'lib/x86/libc++_shared.so'
pickFirst 'lib/x86/libfilters.so'
pickFirst 'lib/arm64-v8a/libc++_shared.so'
pickFirst 'lib/arm64-v8a/libfilters.so'
pickFirst 'lib/armeabi-v7a/libfilters.so'
pickFirst 'lib/armeabi-v7a/libc++_shared.so'
}
...
}
```
The iOS version is designed for OS >= 12.0.
By Pods:
Add to Podspec file:
```
pod 'spectrumlib', '1.0.1'
```
And run `pod install` command.
You can install framework manually:
1. dowload `spectrumlib.xcframework` from [GitHub](https://github.com/BrainbitLLC/apple_spectrumlib)
2. add `spectrumlib.xcframework` to `Frameworks, Libraries, and Embedded Content` section of your project
3. set `Embedded` to `Embed & Sign`
Latest version: `1.0.1`
> Python package available only for Windows
By pip:
```
pip install pyspectrum_lib
```
The package has the following structure:
- spectrum_lib - the main package with the implementation of methods
- libs - contain dll library files
SpectrumMath - one main module contains all methods of library
```python
from spectrum_lib import SpectrumMath
```
Coming soon...
Coming soon...
Install latest version `SpectrumLib` package from NuGet Gallery in your preferred way.
int sampling_rate = 250; // raw signal sampling frequency
int fft_window = 1000; // spectrum calculation window length
int process_win_rate = 5; // spectrum calculation frequency
SpectrumMath* tSpectMathPtr = createSpectrumMath(sampling_rate, fft_window, process_win_rate);
int samplingRate = 250; // raw signal sampling frequency
int fftWindow = 1000; // spectrum calculation window length
int processWinRate = 5; // spectrum calculation frequency
SpectrumMath math = new SpectrumMath(samplingRate, fftWindow, processWinRate);
int samplingRate = 250; // raw signal sampling frequency
int fftWindow = 1000; // spectrum calculation window length
int processWinRate = 5; // spectrum calculation frequency
SpectrumMath math = new SpectrumMath(samplingRate, fftWindow, processWinRate);
sampling_rate = 250 # raw signal sampling frequency
fft_window = sampling_rate * 4 # spectrum calculation window length
process_win_rate = 5 # spectrum calculation frequency
spectrum_math = SpectrumMath(sampling_rate, fft_window, process_win_rate)
let samplingRate: Int32 = 250 // raw signal sampling frequency
let fftWindow = samplingRate * 4 // spectrum calculation window length
let processWinRate: Int32 = 10 // spectrum calculation frequency
var math = SMSpectrumMath(sampleRate: samplingRate, andFftWindow: fftWindow, andProcessWinFreq: processWinRate)
int sampling_rate = 250; // raw signal sampling frequency
int fft_window = 1000; // spectrum calculation window length
int process_win_rate = 5; // spectrum calculation frequency
SMSpectrumMath* math = [[SMSpectrumMath alloc] initWithSampleRate:sampling_rate andFftWindow:fft_window andProcessWinFreq:process_win_rate];
int bord_frequency = 50; // upper bound of frequencies for spectrum calculation
bool normalize_spect_by_bandwidth = true; // normalization of the EEG spectrum by the width of the wavebands
SpectrumMathInitParams(tSpectMathPtr, bord_frequency, normalize_spect_by_bandwidth);
int bordFrequency = 50; // upper bound of frequencies for spectrum calculation
bool normalizeSpectByBandwidth = true; // normalization of the EEG spectrum by the width of the wavebands
math.InitParams(bordFrequency, normalizeSpectByBandwidth);
int bordFrequency = 50; // upper bound of frequencies for spectrum calculation
boolean normalizeSpectByBandwidth = true; // normalization of the EEG spectrum by the width of the wavebands
math.initParams(bordFrequency, normalizeSpectByBandwidth);
bord_frequency = 50 # upper bound of frequencies for spectrum calculation
normalize_spect_by_bandwidth = True # normalization of the EEG spectrum by the width of the wavebands
pectrum_math.init_params(bord_frequency, normalize_spect_by_bandwidth)
let bordFrequency = 50 // upper bound of frequencies for spectrum calculation
let normalze = true // normalization of the EEG spectrum by the width of the wavebands
math.initParams(withUpBorderFreq: bordFrequency, andNormilize: normalze)
int bord_frequency = 50; // upper bound of frequencies for spectrum calculation
bool normalize_spect_by_bandwidth = true; // normalization of the EEG spectrum by the width of the wavebands
[math initParamsWithUpBorderFreq:bord_frequency andNormilize:normalize_spect_by_bandwidth];
double delta_coef = 0.0;
double theta_coef = 1.0;
double alpha_coef = 1.0;
double beta_coef = 1.0;
double gamma_coef = 0.0;
SpectrumMathSetWavesCoeffs(tSpectMathPtr, delta_coef, theta_coef, alpha_coef, beta_coef, gamma_coef);
double alphaCoef = 1.0;
double betaCoef = 1.0;
double deltaCoef = 0.0;
double gammaCoef = 0.0;
double thetaCoef = 1.0;
math.SetWavesCoeffs(deltaCoef, thetaCoef, alphaCoef, betaCoef, gammaCoef);
double alphaCoef = 1.0;
double betaCoef = 1.0;
double deltaCoef = 0.0;
double gammaCoef = 0.0;
double thetaCoef = 1.0;
math.setWavesCoeffs(deltaCoef, thetaCoef, alphaCoef, betaCoef, gammaCoef);
delta_coef = 0.0
theta_coef = 1.0
alpha_coef = 1.0
beta_coef = 1.0
gamma_coef = 0.0
spectrum_math.set_waves_coeffs(delta_coef, theta_coef, alpha_coef, beta_coef, gamma_coef)
let alphaCoeff = 1.0
let betaCoeff = 1.0
let deltaCoeff = 0.0
let thetaCoeff = 1.0
let gammaCoeff = 0.0
math.setWavesCoeffsWithDelta(deltaCoeff, andTheta: thetaCoeff, andAlpha: alphaCoeff, andBeta: betaCoeff, andGamma: gammaCoeff)
double delta_coef = 0.0;
double theta_coef = 1.0;
double alpha_coef = 1.0;
double beta_coef = 1.0;
double gamma_coef = 0.0;
[math setWavesCoeffsWithDelta:delta_coef andTheta:theta_coef andAlpha:alpha_coef andBeta:beta_coef andGamma:gamma_coef];
SpectrumMathSetHanningWinSpect(tSpectMathPtr); // by Hanning (by default)
SpectrumMathSetHammingWinSpect(tSpectMathPtr); // by Hamming
math.SetHanningWinSpect(); // by Hanning (by default)
math.SetHammingWinSpect(); // by Hamming
math.setHanningWinSpect(); // by Hanning (by default)
math.setHammingWinSpect(); // by Hamming
spectrum_math.set_hanning_win_spect() # by Hanning (by default)
spectrum_math.set_hamming_win_spect() # by Hamming
math.setHammingWinSpect() // by Hanning (by default)
math.setHanningWinSpect() // by Hamming
[math setHammingWinSpect]; // by Hanning (by default)
[math setHanningWinSpect]; // by Hamming
Array of double values with length less or equals then 15 * signal sampling frequency.
Structure containing the raw spectrum values (with boundary frequency taken into library).
Fields:
Structure containing the waves values.
Absolute frequency values (double type):
Relative (percent) values (double type):
The library automatically matches the optimal buffer length (degree 2) to calculate the FFT during initialization, depending on the specified window length. Receiving resolution for the FFT bands (number of FFT bands per 1 Hz):
double fftBinsFor1Hz = SpectrumMathGetFFTBinsFor1Hz(tSpectMathPtr);
double fftBinsFor1Hz = math.GetFFTBinsFor1Hz();
double numberBinsFor1Hz = math.getFFTBinsFor1Hz();
fft_bins = spectrum_math.get_fft_bins_for_1_hz()
let fftBins = math.getFFTBinsFor1Hz()
[math getFFTBinsFor1Hz];
double* raw_data = new double[SIGNAL_SAMPLES_COUNT];
SpectrumMathPushData(tSpectMathPtr, raw_data, SIGNAL_SAMPLES_COUNT);
SpectrumMathProcessData(tSpectMathPtr);
double[] samples = new double[SIGNAL_SAMPLES_COUNT];
math.PushData(samples);
// data processing into PushData method
double[] samples = new double[SIGNAL_SAMPLES_COUNT];
math.pushData(data);
samples = [0 for _ in range(sample_count)]
spectrum_math.push_data(samples)
spectrum_math.process_data()
var samples: [NSNumber] = []
math.pushAndProcessData(samples)
NSArray<NSNumber*>* samples = [NSArray new];
[math pushAndProcessData:samples];
uint32_t arr_sz = SpectrumMathReadSpectrumArrSize(tSpectMathPtr);
RawSpectrumData* raw_spect_data = new RawSpectrumData[arr_sz];
SpectrumMathReadRawSpectrumInfoArr(tSpectMathPtr, raw_spect_data, &arr_sz);
WavesSpectrumData* waves_spect_data = new WavesSpectrumData[arr_sz];
SpectrumMathReadWavesSpectrumInfoArr(tSpectMathPtr, waves_spect_data, &arr_sz);
var rawSpectrumData = _math.ReadRawSpectrumInfoArr();
var wavesSpectrumData = _math.ReadWavesSpectrumInfoArr();
RawSpectrumData[] rawSpectrumData = math.readRawSpectrumInfoArr();
WavesSpectrumData[] wavesSpectrumData = math.readWavesSpectrumInfoArr();
raw_spectrum_data = spectrum_math.read_raw_spectrum_info_arr()
waves_spectrum_data = spectrum_math.read_waves_spectrum_info_arr()
let rawSpectrumData = math.readWavesSpectrumInfoArr()
let wavesSpectrumData = math.readWavesSpectrumInfoArr()
NSArray<SMRawSpectrumData*>* rawSpectrumData = [math readRawSpectrumInfoArr];
NSArray<SMWavesSpectrumData*>* wavesSpectrumData = [math readWavesSpectrumInfoArr];
SpectrumMathSetNewSampleSize(tSpectMathPtr);
math.SetNewSampleSize();
math.setNewSampleSize();
spectrum_math.set_new_sample_size()
math.setNewSampleSize()
[math setNewSampleSize];
double* vals_arr = new double[arr_size];
SpectrumMathComputeSpectrum(tSpectMathPtr, vals_arr, arr_size);
double[] samples = new double[SIGNAL_SAMPLES_COUNT];
math.ComputeSpectrum(samples);
double[] samples = new double[SIGNAL_SAMPLES_COUNT];
math.computeSpectrum(samples);
samples = [0 for _ in range(sample_count)]
spectrum_math.compute_spectrum(samples)
var samples: [NSNumber] = []
math.computeSpectrum(samples)
NSArray<NSNumber*>* samples = [NSArray new];
[math computeSpectrum:samples];
RawSpectrumData raw_spect_data;
SpectrumMathReadRawSpectrumInfo(tSpectMathPtr, &raw_spect_data);
WavesSpectrumData waves_spect_data;
SpectrumMathReadWavesSpectrumInfo(tSpectMathPtr, &waves_spect_data)
RawSpectrumData data = math.ReadRawSpectrumInfo();
WavesSpectrumData waves = math.ReadWavesSpectrumInfo();
RawSpectrumData rawSpectrumData = math.readRawSpectrumInfo();
WavesSpectrumData wavesSpectrumData = math.readWavesSpectrumInfo();
raw_spectrum_data = spectrum_math.read_raw_spectrum_info()
waves_spectrum_data = spectrum_math.read_waves_spectrum_info()
let rawSpectrumData = value.readRawSpectrumInfo()
let wavesSpectrumData = value.readWavesSpectrumInfo()
SMRawSpectrumData* rawSpectrumData = [math readRawSpectrumInfo];
SMWavesSpectrumData* wavesSpectrumData = [math readWavesSpectrumInfo];
SpectrumMathClearData(tSpectMathPtr);
math.ClearData();
math.clearData();
del math
math = nil
math = nil;