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Heavily simplified scipy.signal.spectral module which only depends on NumPy and supports pyFFTW

Project description

Heavily simplified scipy.signal.spectral module which only depends on NumPy and supports pyFFTW

Requirements

  • Python 3
  • NumPy
  • Optional: pyFFTW (for fastest FFT calculations with FFTW library)
  • Optional: SciPy (for faster FFT calculations with scipy.fftpack library)

SimpleSpectral preferably uses pyfftw for FFT calculations, then scipy.fftpack and numpy.fft as a last resort.

You should always install SciPy or pyFFTW, because numpy.fft has horrible memory usage and is also much slower.

Differences

You can use scipy.signal tutorial and reference guide in most cases, but there are some important differences:

  • input data is assumed to be complex and two-sided spectrum is always returned (return_onesided argument is not implemented)
  • length of FFT is always same as length of segment (nfft argument is not implemented)
  • functions work always over last axis of array (axis argument is not implemented)
  • if you want to have best FFT performance with pyFFTW, you should create arrays with empty, zeros or ones functions from SimpleSpectral instead of generic versions from NumPy (arrays will be byte aligned for your CPU)

Implemented functions:

  • empty
  • zeros
  • ones
  • fft
  • get_window
  • get_detrend
  • extend_boundaries
  • welch
  • periodogram
  • spectrogram
  • stft

Supported windows:

  • boxcar
  • hann
  • hamming
  • bartlett
  • blackman
  • kaiser
  • tukey

Supported boundary extensions:

  • even
  • odd
  • constant
  • zeros

Supported detrending functions:

  • constant

Credits

Based on code from excellent SciPy project.

Project details


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1.0.0

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Filename, size & hash SHA256 hash help File type Python version Upload date
SimpleSpectral-1.0.0.tar.gz (6.1 kB) Copy SHA256 hash SHA256 Source None Mar 17, 2017

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