/usr/share/octave/packages/tisean-0.2.3/spikeauto.m is in octave-tisean 0.2.3-3.
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 | ## Copyright (C) 1996-2015 Piotr Held
##
## This file is part of Octave.
##
## Octave 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.
##
## Octave 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 Octave; see the file COPYING. If not,
## see <http://www.gnu.org/licenses/>.
## -*- texinfo -*-
## @deftypefn{Function File} {output =} spikeauto (@var{X}, @var{bin}, @var{bintot})
## @deftypefnx{Function File} {output =} spikeauto (@dots{}, '@var{inter}')
##
## Computes the binned autocorrelation function of a series of event times.
##
## The data is assumed to represent a sum of delta functions centered at the
## times given. The autocorrelation function is then a double sum of delta
## functions which must be binned to be representable. Therfore, you have to
## choose the duration of a single bin (with argument @var{bin}) and the maximum
## time lag (argument @var{bintot}) considered.
##
## @strong{Inputs}
##
## @table @var
## @item S
## This function always assumes that each time series is along the longer
## dimension of matrix @var{S}. It also assumes that every dimension
## (counting along the shorter dimension) of @var{S} is considered a
## component of the time series.
## @item bin
## The duration of a single bin.
## @item bintot
## The maximum lag considered.
## @end table
##
## @strong{Switch}
##
## @table @var
## @item inter
## Treat the input as inter-event intervals instead of the time at which the event
## occured.
## @end table
##
## @strong{Output}
##
## The output is alligned with the input. If the input was a column vector the
## output will consist of two columns, the first holds information about which
## bin did the autocorellation fit into, and the second the number of
## autocorellations that fit into that bin.
##
## @strong{Algorithms}
##
## The algorithms for this functions have been taken from the TISEAN package.
## @end deftypefn
## Author: Piotr Held <pjheld@gmail.com>.
## This function is based on spikeauto of TISEAN 3.0.1
## https://github.com/heggus/Tisean"
function output = spikeauto (X, bin, totbin, varargin)
# Initial input validation
if (nargin < 3 || nargin > 4)
print_usage;
endif
# Check if X is real vector
if ((isvector (X) == false) || (isreal (X) == false))
error ('Octave:invalid-input-arg', "X must be a real vector");
endif
# Check if X has at least 2 different elements
if (min (X) == max (X))
error ('Octave:invalid-input-arg',
"X must contain at least 2 differing elements");
endif
inter = false;
if (nargin == 4)
if (strcmpi (varargin{1}, "inter"))
inter = true;
else
error ('Octave:invalid-input-arg', "additional parameter is not 'inter'");
endif
endif
# Correct X to always have more rows than columns
trnspsd = false;
if (rows (X) < columns (X))
X = X.';
trnspsd = true;
endif
# If the input is interval change to times
if (inter)
X = cumsum (X);
endif
X = sort (X);
# Number of bins
nbin = floor (totbin / bin) + 1;
# The oct file is used for optimization (using a for loop in Octave is about 100
# times slower and not using the for loop uses a lot of memory,
# e.g. when lenght (X) == 2000 it uses 500 MB).
ihist = __spikeauto__ (X, bin, nbin);
idx = (1:nbin).';
idx = (idx - 0.5) .* bin;
output = [idx, ihist];
if (trnspsd)
output = output.';
endif
endfunction
%% Test against TISEAN output
%!test
%! spikeauto_res = [0.25 403965;0.75 376230;1.25 331311;1.75 274509;2.25 209767;2.75 153597;3.25 104075;3.75 65683;4.25 39030;4.75 21812;5.25 10745;5.75 5090;6.25 2064;6.75 792;7.25 245;7.75 70;8.25 14;8.75 1;9.25 0;9.75 0;10.25 0];
%! rand ("seed", 1);
%! x = zeros (2000,1);
%! for i = 2:2000
%! x(i) = 0.7*x(i-1) + (-6 + sum (rand ([size(1), 12]), 3));
%! endfor
%! res = spikeauto (x, 0.5, 10);
%! assert (res, spikeauto_res, 1);
%% Testing input validation
%!error <Invalid call> spikeauto (1)
%!error <2 differing elements> spikeauto (ones (10,1), 1,3);
%!error <vector> spikeauto ([(1:10);(1:10)],1,2);
|