BaseSpectra¶

class acoular.spectra.BaseSpectra¶

Bases: traits.has_traits.HasPrivateTraits

source = Trait(SamplesGenerator)¶

Data source; SamplesGenerator or derived object.

sample_freq = Delegate('source')¶

Sampling frequency of output signal, as given by source.

numchannels = Delegate('source')¶

Number of time data channels

window = Trait('Rectangular', …¶

Window function for FFT, one of: * ‘Rectangular’ (default) * ‘Hanning’ * ‘Hamming’ * ‘Bartlett’ * ‘Blackman’

overlap = Trait('None', {'None':1, '50%':2, '75%':4, '87.5%':8}, …¶

Overlap factor for averaging: ‘None’(default), ‘50%’, ‘75%’, ‘87.5%’.

block_size = Trait(1024, 128, 256, 512, 1024, 2048, 4096, 8192, 16384, 32768, 65536, …¶

FFT block size, one of: 128, 256, 512, 1024, 2048 … 65536, defaults to 1024.

precision = Trait('complex128', 'complex64', …¶

The floating-number-precision of entries of csm, eigenvalues and eigenvectors, corresponding to numpy dtypes. Default is 64 bit.

fftfreq()¶

Return the Discrete Fourier Transform sample frequencies.

Returns

fndarray

Array of length block_size/2+1 containing the sample frequencies.