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📄 plot_wcor.m

📁 时间序列分析中很用的源码,书的原名为时间序列分析的小波方法.
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function plot_wcor(wcor, CI, ylabel_str, title_str)% plot_wcor -- Plot the wavelet correlation and (optionally) confidence intervals.%%****f* wmtsa.dwt/plot_wcor%% NAME%   plot_wcor -- Plot the wavelet correlation and (optionally) confidence intervals.%% SYNOPSIS%   plot_wcor(wcor, [CI], [ylabel_str], [title_str])%% INPUTS%   wcor          = vector containing wavelet corrrelation for J levels.%   CI            = Jx2 matrix containing 95% confidence intervals,%                   lower bound (column 1) and upper bound (column 2)%   ylabel_str   = string containing first line of ylabel for plot%   title_str    = string containing title for the plot%% OUTPUTS%%% SIDE EFFECTS%   %% DESCRIPTION%   %% EXAMPLE%%% NOTES%%% REFERENCES%%% SEE ALSO%% AUTHOR%   Charlie Cornish%% CREATION DATE%   2003/04/24%% COPYRIGHT%%% CREDITS%%% REVISION%   $Revision: 612 $%%***% $Id: plot_wcor.m 612 2005-10-28 21:42:24Z ccornish $  usage_str = ['Usage:  ', mfilename, ...               '(wcor, [CI], [ylabel_str], [title_str])'];  %%  Check input arguments and set defaults.  error(nargerr(mfilename, nargin, [1:4], nargout, '', 1, usage_str, 'struct'));  plot_ci = 0;    if (nargin > 1)    if ~isempty(CI)      plot_ci = 1;    end  end    nlevels = length(wcor);  x_axis = (1:1:nlevels);    plot(x_axis, wcor, 'r');  hold on;    if (plot_ci)     plot(x_axis, CI(:,1), 'k--');     plot(x_axis, CI(:,2), 'k--');  end    axis_values = axis;  xmin = 0;  xmax = max(x_axis);  if (mod(xmax,2) == 1)    xmax = xmax +1;   end    ymin = -1.5;  ymax =  1.5;    axis_values(1) = xmin;  axis_values(2) = xmax;  axis_values(3) = ymin;  axis_values(4) = ymax;    axis(axis_values);    default_ylabel_str = 'wavelet correlation';  if exist('ylabel_str', 'var')    ylabel_str2(1) = {ylabel_str};    ylabel_str2(2) = {default_ylabel_str};   else    ylabel_str2 = default_ylabel_str;  end    ylabel(ylabel_str2);    xlabel('level');    if exist('title_str', 'var')    title(title_str);  end  return

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