%---------------------------------------------------------------------------
%
%    PROJECT:        -
%    PACKAGE:        (signal processing / general tools)
%    FILE:           'resampl1.m'
%
%    PURPOSE:        Provide 1-pass fixed-rate linear resampling
%    VERSION:        1.0
%
%    STAGE:          BETA
%    UPDATED:        05-Jan-2017/10:00
%
%    HISTORY:        version 1.0: implemented core functionality (05-Jan-2017/10:00)
%
%    DESCRIPTION:    This is a template stand-alone code (no externals required) for a 
%                    simple 1-pass fixed rate linear resampler. Specifically, the script
%                    can be used as-is or as base for a function, which take a series of
%                    pairs <t,x> and a requested fixed resampling rate and it produces
%                    a new series of <t',x'> using stepwise linear regressors.
%                    The script includes a data sorting step against <t>, which is not
%                    implemented here internally and can be removed if the input data
%                    are already expected to be sorted. In case of no sorting step here,
%                    the script is completely 1-pass, which means that all elements of
%                    the two input vectors (ref. points) are read only once for the 
%                    entire resampling process. This is particularly useful when this
%                    implementation is to be applied directly to extremely large input 
%                    files (e.g. columns in .csv) with only minimal memory usage for
%                    the calculations and only sequential read mode for speed.
%
%    INPUT:          Tt : [Nx1] column vector with timestamps (e.g. secs)
%                    Xt : [Nx1] column vector with data series (ref. points)
%                    Trate : (scalar) arbitrary fixed-rate for resampling
%
%    OUTPUT:         Nr : (scalar) length of new column vectors
%                    D  : [Nr x2] two column vectors with resampled points
%                            D(Nr,1) : new timestamps
%                            D(Nr,2) : new data series
%
%    NOTE:           This work is supported by the DART project (H2020): "Data-Driven 
%                    Aircraft Trajectory Prediction Research" (http://dart-research.eu) 
%                    and the Data Science Lab (http://www.datastories.org) at the 
%                    University of Piraeus, Greece (http://www.unipi.gr).
%
%    AUTHOR:         Harris Georgiou (MSc,PhD) - IS/IT Engineer (R&D)
%    COPYRIGHT:      Data Science Lab @ UniPi (c) 2017 - http://datastories.org
%    LICENCE:        Creative Commons (CC-BY-SA) 4.0/I - http://creativecommons.org
%
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