[psd,f_out] = pyulear(x,poles,freq,Fs,range,method,plot_type) All but the first two arguments are optional and may be empty.
[vector] sampled data
[integer scalar] required number of poles of the AR model
[real vector] frequencies at which power spectral density is calculated [integer scalar] number of uniformly distributed frequency values at which spectral density is calculated. [default=256]
[real scalar] sampling frequency (Hertz) [default=1]
'half', 'onesided' : frequency range of the spectrum is from zero up to but not including sample_f/2. Power from negative frequencies is added to the positive side of the spectrum. 'whole', 'twosided' : frequency range of the spectrum is -sample_f/2 to sample_f/2, with negative frequencies stored in "wrap around" order after the positive frequencies; e.g. frequencies for a 10-point 'twosided' spectrum are 0 0.1 0.2 0.3 0.4 0.5 -0.4 -0.3 -0.2 -0.1 'shift', 'centerdc' : same as 'whole' but with the first half of the spectrum swapped with second half to put the zero-frequency value in the middle. (See "help fftshift". If "freq" is vector, 'shift' is ignored. If model coefficients "ar_coeffs" are real, the default range is 'half', otherwise default range is 'whole'.
'fft': use FFT to calculate power spectral density. 'poly': calculate spectral density as a polynomial of 1/z N.B. this argument is ignored if the "freq" argument is a vector. The default is 'poly' unless the "freq" argument is an integer power of 2.
'plot', 'semilogx', 'semilogy', 'loglog', 'squared' or 'db' specifies the type of plot. The default is 'plot', which means linear-linear axes. 'squared' is the same as 'plot'. 'dB' plots "10*log10(psd)". This argument is ignored and a spectrum is not plotted if the caller requires a returned value.