% MUTUAL_INFORMATION_PT
% A temporal partial mutual information estimate from samples.
%
% I = mutual_information_pt(X, Y, Z, timeWindowRadius)
% I = mutual_information_pt(X, Y, Z, timeWindowRadius, 'key', value, ...)
%
% where
%
% X, Y, and Z are signal sets.
%
% TIMEWINDOWRADIUS is an integer which determines the temporal radius
% around each point that will be used by the estimator.
%
% I is the estimated temporal partial mutual information.
%
% Optional input arguments in 'key'-value pairs:
%
% XLAG, YLAG, and ZLAG ('xLag', 'yLag', 'zLag') are integers which
% denote the amount of lag to apply to signal X, Y, and Z,
% respectively. Default 0.
%
% FILTER ('filter') is an arbitrary-dimensional real-array, whose
% linearization contains temporal weighting coefficients.
% Default: 1 (i.e. no temporal weighting is performed)
%
% Type 'help tim' for more documentation.
% Description: Temporal partial mutual information estimation
% Documentation: mutual_information.txt
function I = mutual_information_pt(X, Y, Z, timeWindowRadius, varargin)
import([tim_package, '.*']);
concept_check(nargin, 'inputs', 4);
concept_check(nargout, 'outputs', 0 : 1);
% Optional input arguments.
xLag = 0;
yLag = 0;
zLag = 0;
k = 1;
filter = 1;
eval(process_options(...
{'k', 'xLag', 'yLag', 'zLag', 'filter'}, ...
varargin));
if isnumeric(X)
X = {X};
end
if isnumeric(Y)
Y = {Y};
end
if isnumeric(Z)
Z = {Z};
end
if ~iscell(X) || ~iscell(Y) || ~iscell(Z)
error('X, Y, or Z is not a cell-array.');
end
if numel(X) ~= numel(Y) || numel(X) ~= numel(Z)
error('The number of trials in X, Y, and Z differ.');
end
% Pass parameter error checking to entropy_combination.
I = entropy_combination_t(...
[X(:)'; Z(:)'; Y(:)'], ...
[1, 2, 1; 2, 3, 1; 2, 2, -1], timeWindowRadius, ...
'lagSet', {xLag, zLag, yLag}, ...
'k', k, ...
'filter', filter);