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Timeseries2WCO.m
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Timeseries2WCO.m
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%% DESCRIPTION
% just returns a WCO from two input time series
function varargout = Timeseries2WCO(ts_x1, ts_x2, varargin)
disp = false; % display options
source = 'J'; % use Matlab for Matlab implementation of the CWT
%% continious wavelet transform
% [cwt_1,scales,periods,coi,time] = CWT(ts_x1, ...
% 'wave_normalization', char(parameter_space.wave_normalization),...
% 'morse_space', char(parameter_space.morse_space),...
% 'K', 1, ...
% 'be', parameter_space.be,...
% 'ga', parameter_space.ga,...
% 'disp_cwt', false,...
% 'wavelet_type', char(parameter_space.wavelet_type),...
% 'source', source...
% );
% cwt_2 = CWT(ts_x2,...
% 'wave_normalization', char(parameter_space.wave_normalization),...
% 'morse_space', char(parameter_space.morse_space),...
% 'K', 1, ...
% 'be', parameter_space.be,...
% 'ga', parameter_space.ga,...
% 'disp_cwt', false,...
% 'wavelet_type', char(parameter_space.wavelet_type),...
% 'source', source...
% );
[cwt_1,scales,periods,coi,time] = CWT(ts_x1,varargin);
cwt_2 = CWT(ts_x2,varargin);
%% wavelet coherence
% Input_WCO = WCO(cwt_1,cwt_2,scales,periods,...
% 'smoothing', char(parameter_space.smoothing),...
% 'ws_size', parameter_space.ws_size,...
% 'wt_size', parameter_space.wt_size,...
% 'disp_coherence', false,...
% 'coi',cwt_1,...
% 'time_series',[ts_x1 ts_x2],...
% 'y_axis', 'scale',...
% 'coherence', char(parameter_space.coherence)...
% );
Input_WCO = WCO(cwt_1,cwt_2,scales,periods,varargin);
varargout = {Input_WCO, periods};
end