/usr/share/octave/packages/signal-1.3.2/pyulear.m is in octave-signal 1.3.2-1+b1.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | ## Copyright (C) 2006 Peter V. Lanspeary <pvl@mecheng.adelaide.edu.au>
##
## This program is free software; you can redistribute it and/or modify it under
## the terms of the GNU General Public License as published by the Free Software
## Foundation; either version 3 of the License, or (at your option) any later
## version.
##
## This program is distributed in the hope that it will be useful, but WITHOUT
## ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
## FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more
## details.
##
## You should have received a copy of the GNU General Public License along with
## this program; if not, see <http://www.gnu.org/licenses/>.
## usage:
## [psd,f_out] = pyulear(x,poles,freq,Fs,range,method,plot_type)
##
## Calculates a Yule-Walker autoregressive (all-pole) model of the data "x"
## and computes the power spectrum of the model. This is a wrapper for
## functions "aryule" and "ar_psd" which perform the argument checking.
## See "help aryule" and "help ar_psd" for further details.
##
## ARGUMENTS:
## All but the first two arguments are optional and may be empty.
## x %% [vector] sampled data
##
## poles %% [integer scalar] required number of poles of the AR model
##
## freq %% [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]
##
## Fs %% [real scalar] sampling frequency (Hertz) [default=1]
##
##
## CONTROL-STRING ARGUMENTS -- each of these arguments is a character string.
## Control-string arguments can be in any order after the other arguments.
##
##
## range %% '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'.
##
## method %% 'fft': use FFT to calculate power spectrum.
## %% 'poly': calculate power spectrum 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_type %% '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.
##
## RETURNED VALUES:
## If return values are not required by the caller, the spectrum
## is plotted and nothing is returned.
## psd %% [real vector] power-spectrum estimate
## f_out %% [real vector] frequency values
##
## HINTS
## This function is a wrapper for aryule and ar_psd.
## See "help aryule", "help ar_psd".
function [psd,f_out]=pyulear(x,poles,varargin)
##
if ( nargin<2 )
error( 'pburg: need at least 2 args. Use "help pburg"' );
endif
##
[ar_coeffs,residual,k]=aryule(x,poles);
if ( nargout==0 )
ar_psd(ar_coeffs,residual,varargin{:});
elseif ( nargout==1 )
psd = ar_psd(ar_coeffs,residual,varargin{:});
elseif ( nargout>=2 )
[psd,f_out] = ar_psd(ar_coeffs,residual,varargin{:});
endif
endfunction
%!demo
%! rand ("seed", 2038014164);
%! a = [1.0 -1.6216505 1.1102795 -0.4621741 0.2075552 -0.018756746];
%! Fs = 25;
%! n = 16384;
%! signal = detrend (filter (0.70181, a, rand (1, n)));
%! % frequency shift by modulating with exp(j.omega.t)
%! skewed = signal .* exp (2*pi*i*2/Fs*[1:n]);
%! hold on
%! pyulear (signal, 3, [], Fs);
%! pyulear (signal, 4, [], Fs, "whole");
%! pyulear (signal, 5, 128, Fs, "shift", "semilogy");
%! pyulear (skewed, 7, 128, Fs, "shift", "semilogy");
%! user_freq = [-0.2:0.02:0.2]*Fs;
%! pyulear (skewed, 7, user_freq, Fs, "semilogy");
%! hold off
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