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1. final def !=(arg0: AnyRef): Boolean

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2. final def !=(arg0: Any): Boolean

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3. final def ##(): Int

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4. final def ==(arg0: AnyRef): Boolean

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5. final def ==(arg0: Any): Boolean

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6. final def asInstanceOf[T0]: T0

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7. def clone(): AnyRef

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8. def convolve(data: Array[Double], kernel: Array[Double]): Array[Double]

9. def correlate(data: Array[Double], kernel: Array[Double]): Array[Double]

10. final def eq(arg0: AnyRef): Boolean

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11. def equals(arg0: Any): Boolean

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12. def filterBP(data: Array[Double], omegaLow: Double, omegaHigh: Double): Array[Double]

    See filterBP

13. def filterBP(data: Array[Double], omegaLow: Double, omegaHigh: Double, sampleRate: Double): Array[Double]

    See filterBP

14. def filterBP(data: Array[Double], omegaLow: Double, omegaHigh: Double, sampleRate: Double, taps: Int): Array[Double]

    Bandpass filter the data using a windowed FIR filter.

    Bandpass filter the data using a windowed FIR filter. See/use breeze.signal.filterBP() for more details, and to set advanced options.

    data

    data to filter

    omegaLow

    low frequency (in units of Nyquist frequency or Hz if sampleRate is set to specific value other than 2d)

    omegaHigh

    high frequency (in units of Nyquist frequency or Hz if sampleRate is set to specific value other than 2d)

    sampleRate

    in Hz, default 2d (omegaLow/High will then be in units of Nyquist frequency)

    taps

    number of taps to use, default 512

    returns

15. def filterBS(data: Array[Double], omegaLow: Double, omegaHigh: Double): Array[Double]

    See filterBS

16. def filterBS(data: Array[Double], omegaLow: Double, omegaHigh: Double, sampleRate: Double): Array[Double]

    See filterBS

17. def filterBS(data: Array[Double], omegaLow: Double, omegaHigh: Double, sampleRate: Double, taps: Int): Array[Double]

    Bandstop filter the data using a windowed FIR filter.

    Bandstop filter the data using a windowed FIR filter. See/use breeze.signal.filterBS() for more details, and to set advanced options.

    data

    data to filter

    omegaLow

    low frequency (in units of Nyquist frequency or Hz if sampleRate is set to specific value other than 2d)

    omegaHigh

    high frequency (in units of Nyquist frequency or Hz if sampleRate is set to specific value other than 2d)

    sampleRate

    in Hz, default 2d (omegaLow/High will then be in units of Nyquist frequency)

    taps

    number of taps to use, default 512

    returns

18. def filterHP(data: Array[Double], omega: Double): Array[Double]

    See filterHP

19. def filterHP(data: Array[Double], omega: Double, sampleRate: Double): Array[Double]

    See filterHP

20. def filterHP(data: Array[Double], omega: Double, sampleRate: Double, taps: Int): Array[Double]

    High pass filter the data using a windowed FIR filter.

    High pass filter the data using a windowed FIR filter. See/use breeze.signal.filterHP() for more details, and to set advanced options.

    data

    data to filter

    omega

    cutoff frequency (in units of Nyquist frequency or Hz if sampleRate is set to specific value other than 2d)

    sampleRate

    in Hz, default 2d (omega will then be in units of Nyquist frequency)

    taps

    number of taps to use, default 512

    returns

21. def filterLP(data: Array[Double], omega: Double): Array[Double]

    See filterLP

22. def filterLP(data: Array[Double], omega: Double, sampleRate: Double): Array[Double]

    See filterLP

23. def filterLP(data: Array[Double], omega: Double, sampleRate: Double, taps: Int): Array[Double]

    Low pass filter the data using a windowed FIR filter.

    Low pass filter the data using a windowed FIR filter. See/use breeze.signal.filterLP() for more details, and to set advanced options.

    data

    data to filter

    omega

    cutoff frequency (in units of Nyquist frequency or Hz if sampleRate is set to specific value other than 2d)

    sampleRate

    in Hz, default 2d (omega will then be in units of Nyquist frequency)

    taps

    number of taps to use, default 512

    returns

24. def filterMedianD(data: Array[Double], windowLength: Int): Array[Double]

    Median filter the input data.

    Median filter the input data. Edge values are median-filtered with shorter windows, in order to preserve the total length of the input.

    windowLength

    only supports odd windowLength values, since even values would cause half-frame time shifts in one or the other direction, and would also lead to floating point values even for integer input

25. def finalize(): Unit

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26. def fourierFreqD(windowLength: Int, fs: Double): Array[Double]

    See fourierFreq.

    See fourierFreq. shifted = false

27. def fourierFreqD(windowLength: Int, fs: Double, shifted: Boolean): Array[Double]

    Returns the frequencies for each tap in a discrete Fourier transform, useful for plotting.

    Returns the frequencies for each tap in a discrete Fourier transform, useful for plotting. You must specify either an fs or a dt argument. If you specify both, which is redundant, fs == 1.0/dt must be true.

    f = [0, 1, ..., n/2-1, -n/2, ..., -1] / (dt*n) if n is even f = [0, 1, ..., (n-1)/2, -(n-1)/2, ..., -1] / (dt*n) if n is odd

    windowLength

    window length of discrete Fourier transform

    fs

    sampling frequency (Hz)

    shifted

    whether to return fourierShift'ed frequencies, default=false

28. def fourierShiftC(data: Array[Complex]): Array[Complex]

    See fourierShiftD

29. def fourierShiftD(data: Array[Double]): Array[Double]

    Shift the zero-frequency component to the center of the spectrum.

    Shift the zero-frequency component to the center of the spectrum. Use fourierShiftC instead for complex array input. This function swaps half-spaces for all axes listed (defaults to all). Note that y[0] is the Nyquist component only if len(x) is even.

    data

    input array

    returns

30. def fourierTr2C(data: Array[Array[Complex]]): Array[Array[Complex]]

    See fourierTrD

31. def fourierTrC(data: Array[Complex]): Array[Complex]

    See fourierTrD

32. def fourierTrD(data: Array[Double]): Array[Complex]

    Returns the discrete fourier transform.

    Returns the discrete fourier transform. Use fourierTrC instead for complex array imput. Use fourierTr2/2C instead for 2D Fourier tranform.

    returns

33. final def getClass(): Class[_]

    Definition Classes

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34. def haarTr2D(data: Array[Array[Double]]): Array[Array[Double]]

    See haarTrD

35. def haarTrD(data: Array[Double]): Array[Double]

    Return the padded fast haar transformation of a vector or matrix.

    Return the padded fast haar transformation of a vector or matrix. Note that the output will always be padded to a power of 2. A matrix will cause a 2D fht. The 2D haar transformation is defined for squared power of 2 matrices. A new matrix will thus be created and the old matrix will be placed in the upper-left part of the new matrix. Avoid calling this method with a matrix that has few cols / many rows or many cols / few rows (e.g. 1000000 x 3) as this will cause a very high memory consumption.

    data

    data to be transformed.

    See also

    https://en.wikipedia.org/wiki/Haar_wavelet

36. def hashCode(): Int

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37. def iFourierShiftC(data: Array[Complex]): Array[Complex]

    See iFourierShiftD

38. def iFourierShiftD(data: Array[Double]): Array[Double]

    Shift the zero-frequency component to the center of the spectrum.

    Shift the zero-frequency component to the center of the spectrum. Use fourierShiftC instead for complex array input. This function swaps half-spaces for all axes listed (defaults to all). Note that y[0] is the Nyquist component only if len(x) is even.

    data

    input array

    returns

39. def iFourierTrC(data: Array[Complex]): Array[Complex]

    See fourierTrD

40. final def isInstanceOf[T0]: Boolean

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41. final def ne(arg0: AnyRef): Boolean

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42. final def notify(): Unit

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43. final def notifyAll(): Unit

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44. def rootMeanSquareD(data: Array[Double]): Double

    Root mean square of a vector.

45. final def synchronized[T0](arg0: ⇒ T0): T0

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46. def toString(): String

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47. final def wait(): Unit

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48. final def wait(arg0: Long, arg1: Int): Unit

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49. final def wait(arg0: Long): Unit

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