denspp.offline.preprocessing.transformation#

Module Contents#

Functions#

transformation_window_method

Generating window for smoothing input of signal transformation method.

do_fft

Performing the Discrete Fast Fourier Transformation.

do_fft_withimag

Performing the Discrete Fast Fourier Transformation with imaginary part.

do_fft_inverse

Perform inverse real FFT.

API#

denspp.offline.preprocessing.transformation.transformation_window_method(window_size: int, method: str = 'hamming') → numpy.ndarray[source]#

Generating window for smoothing input of signal transformation method.

Parameters:

  • window_size – Integer number with size of the window

  • method – Selection of window method [‘’: Ones, ‘hamming’, ‘hanning’, ‘gaussian’, ‘bartlett’, ‘blackman’]

Returns:

Numpy array with window

denspp.offline.preprocessing.transformation.do_fft(y: numpy.ndarray, fs: float, method_window: str = 'hamming') → [numpy.ndarray, numpy.ndarray][source]#

Performing the Discrete Fast Fourier Transformation.

Parameters:

  • y – Transient input signal

  • fs – Sampling rate [Hz]

  • method_window – Selected window [‘’: None, ‘Hamming’, ‘hanning’, ‘guassian’, ‘bartlett’, ‘blackman’]

Returns:

Tuple with (1) freq - Frequency and (2) Y - Discrete output

denspp.offline.preprocessing.transformation.do_fft_withimag(y: numpy.ndarray, fs: float, method_window: str = '') → [numpy.ndarray, numpy.ndarray][source]#

Performing the Discrete Fast Fourier Transformation with imaginary part.

Parameters:

  • y – Transient input signal

  • fs – Sampling rate [Hz]

  • method_window – Selected window

Returns:

Tuple with (1) freq - Frequency and (2) Y - Discrete output

denspp.offline.preprocessing.transformation.do_fft_inverse(y: numpy.ndarray, len_original: int) → numpy.ndarray[source]#

Perform inverse real FFT.

Parameters:

  • y – Fourier domain signal

  • len_original – Length of original time domain signal

Returns:

Time domain signal