final case class Real2FFT(in: D, rows: I, columns: I = 0, mode: I = 0) extends FFT2HalfUGen with Product with Serializable
Forward short-time Fourier transform UGen for a real-valued input signal.
The FFT size is equal to rows * columns. The output is a succession
of complex half-spectra, i.e. from DC to Nyquist.
XXX TODO: Depending on mode,
the output window size is either size + padding or size + padding + 2.
Warning: window parameter modulation is currently not working correctly (issue #30)
- in
the real signal to transform. If overlapping windows are desired, a
Slidingshould already have been applied to this signal, as well as multiplication with a window function.- rows
the input matrix number of rows
- columns
the input matrix number of columns
- mode
packing mode.
0(default) is standard "packed" mode, whereby the real part of the bin at Nyquist is stored in the imaginary slot of the DC. This mode allows perfect reconstruction with aReal2IFFTusing the same mode.1is "unpacked" mode, whereby the output windows are made two samples longer, so that the Nyquist bin is included in the very end. By definition, the imaginary parts of DC and Nyquist are zero. This mode allows perfect reconstruction with aReal2IFFTusing the same mode.2is "discarded" mode, whereby the Nyquist bin is omitted. While it doesn't allow a perfect reconstruction, this mode is useful for analysis, because the output window size is equal to the fft-size, and the imaginary part of DC is correctly zero'ed.
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- new Real2FFT(in: D, rows: I, columns: I = 0, mode: I = 0)
- in
the real signal to transform. If overlapping windows are desired, a
Slidingshould already have been applied to this signal, as well as multiplication with a window function.- rows
the input matrix number of rows
- columns
the input matrix number of columns
- mode
packing mode.
0(default) is standard "packed" mode, whereby the real part of the bin at Nyquist is stored in the imaginary slot of the DC. This mode allows perfect reconstruction with aReal2IFFTusing the same mode.1is "unpacked" mode, whereby the output windows are made two samples longer, so that the Nyquist bin is included in the very end. By definition, the imaginary parts of DC and Nyquist are zero. This mode allows perfect reconstruction with aReal2IFFTusing the same mode.2is "discarded" mode, whereby the Nyquist bin is omitted. While it doesn't allow a perfect reconstruction, this mode is useful for analysis, because the output window size is equal to the fft-size, and the imaginary part of DC is correctly zero'ed.
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- def apply(in: OutD, rows: OutI, columns: OutI, mode: OutI)(implicit b: Builder): OutD
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- final def makeUGens(implicit b: Builder): UGenInLike[Double]
Abstract method which must be implemented by creating the actual
UGens during expansion.Abstract method which must be implemented by creating the actual
UGens during expansion. This method is at most called once during graph expansion- returns
the expanded object (depending on the type parameter
U)
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- val rows: I
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- Real2FFT → FFT2HalfUGen
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