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    Metadata details:
    filename: EN_rpde.m
    path of file: ./repos/hctsa/Operations
    
    the code of the file until where you have to start completion: function out = EN_rpde(x, m, tau, epsilon, T_max)
% EN_rpde   Recurrence period density entropy (RPDE).
%
% Fast RPDE analysis on an input signal to obtain an estimate of the H_norm value
% and other related statistics.
%
% Based on Max Little's code rpde (see below)
%
%---USAGE:
% [H_norm, rpd] = rpde(x, m, tau)
% [H_norm, rpd] = rpde(x, m, tau, epsilon)
% [H_norm, rpd] = rpde(x, m, tau, epsilon, T_max)
%
%---INPUTS:
%    x       - input signal: must be a row vector
%    m       - embedding dimension
%    tau     - embedding time delay
%
%---OPTIONAL INPUTS:
%    epsilon - recurrence neighbourhood radius
%              (If not specified, then a suitable value is chosen automatically)
%    T_max   - maximum recurrence time
%              (If not specified, then all recurrence times are returned)
%---OUTPUTS:
%    H_norm  - Estimated RPDE value
%    rpd     - Estimated recurrence period density

% ------------------------------------------------------------------------------
% (c) 2007 Max Little.
% ------------------------------------------------------------------------------
% If you use this code, please cite:
% Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice
% Disorder Detection
% M. Little, P. McSharry, S. Roberts, D. Costello, I. Moroz (2007),
% BioMedical Engineering OnLine 2007, 6:23
% ------------------------------------------------------------------------------
% Minor tweaks and additional outputs added by Ben Fulcher, 2015-05-15, for use
% with the hctsa package.

    
function out = EN_rpde(x, m, tau, epsilon, T_max)
% EN_rpde   Recurrence period density entropy (RPDE).
%
% Fast RPDE analysis on an input signal to obtain an estimate of the H_norm value
% and other related statistics.
%
% Based on Max Little's code rpde (see below)
%
%---USAGE:
% [H_norm, rpd] = rpde(x, m, tau)
% [H_norm, rpd] = rpde(x, m, tau, epsilon)
% [H_norm, rpd] = rpde(x, m, tau, epsilon, T_max)
%
%---INPUTS:
%    x       - input signal: must be a row vector
%    m       - embedding dimension
%    tau     - embedding time delay
%
%---OPTIONAL INPUTS:
%    epsilon - recurrence neighbourhood radius
%              (If not specified, then a suitable value is chosen automatically)
%    T_max   - maximum recurrence time
%              (If not specified, then all recurrence times are returned)
%---OUTPUTS:
%    H_norm  - Estimated RPDE value
%    rpd     - Estimated recurrence period density

% ------------------------------------------------------------------------------
% (c) 2007 Max Little.
% ------------------------------------------------------------------------------
% If you use this code, please cite:
% Exploiting Nonlinear Recurrence and Fractal Scaling Properties for Voice
% Disorder Detection
% M. Little, P. McSharry, S. Roberts, D. Costello, I. Moroz (2007),
% BioMedical Engineering OnLine 2007, 6:23
% ------------------------------------------------------------------------------
% Minor tweaks and additional outputs added by Ben Fulcher, 2015-05-15, for use
% with the hctsa package.
% If you use this code for your research, please cite the following two papers:
%
% (1) B.D. Fulcher and N.S. Jones, "hctsa: A Computational Framework for Automated
% Time-Series Phenotyping Using Massive Feature Extraction, Cell Systems 5: 527 (2017).
% DOI: 10.1016/j.cels.2017.10.001
%
% (2) B.D. Fulcher, M.A. Little, N.S. Jones, "Highly comparative time-series
% analysis: the empirical structure of time series and their methods",
% J. Roy. Soc. Interface 10(83) 20130048 (2013).
% DOI: 10.1098/rsif.2013.0048
% ------------------------------------------------------------------------------

% ------------------------------------------------------------------------------
% Check inputs and set defaults
% ------------------------------------------------------------------------------
if nargin < 2 || isempty(m)
    m = 2;
end