annotate toolboxes/MIRtoolbox1.3.2/MIRToolbox/mirrms.m @ 0:e9a9cd732c1e tip

first hg version after svn
author wolffd
date Tue, 10 Feb 2015 15:05:51 +0000
parents
children
rev   line source
wolffd@0 1 function varargout = mirrms(x,varargin)
wolffd@0 2 % e = mirrms(x) calculates the root mean square energy.
wolffd@0 3 % Optional arguments:
wolffd@0 4 % mirrms(...,'Frame') computes the temporal evolution of the energy.
wolffd@0 5 % mirrms(...,'Root',0) does not apply the root operation to the mean
wolffd@0 6 % square energy.
wolffd@0 7
wolffd@0 8 normal.key = 'Normal';
wolffd@0 9 normal.type = 'Boolean';
wolffd@0 10 normal.default = 1;
wolffd@0 11 option.normal = normal;
wolffd@0 12
wolffd@0 13 root.key = 'Root';
wolffd@0 14 root.type = 'Boolean';
wolffd@0 15 root.default = 1;
wolffd@0 16 option.root = root;
wolffd@0 17
wolffd@0 18 specif.option = option;
wolffd@0 19
wolffd@0 20 specif.defaultframelength = 0.05;
wolffd@0 21 specif.defaultframehop = 0.5;
wolffd@0 22
wolffd@0 23 specif.eachchunk = @eachchunk;
wolffd@0 24 specif.combinechunk = @combinechunk;
wolffd@0 25 specif.afterchunk = @afterchunk;
wolffd@0 26
wolffd@0 27 varargout = mirfunction(@mirrms,x,varargin,nargout,specif,@init,@main);
wolffd@0 28
wolffd@0 29
wolffd@0 30 function [x type] = init(x,option)
wolffd@0 31 type = 'mirscalar';
wolffd@0 32
wolffd@0 33
wolffd@0 34 function e = main(x,option,postoption)
wolffd@0 35 if iscell(x)
wolffd@0 36 x = x{1};
wolffd@0 37 end
wolffd@0 38 d = get(x,'Data');
wolffd@0 39 v = mircompute(@algo,d,option);
wolffd@0 40 e = mirscalar(x,'Data',v,'Title','RMS energy');
wolffd@0 41
wolffd@0 42
wolffd@0 43 function e = algo(d,option)
wolffd@0 44 nl = size(d,1);
wolffd@0 45 nc = size(d,2);
wolffd@0 46 nch = size(d,3);
wolffd@0 47 e = zeros(1,nc,nch);
wolffd@0 48 for i = 1:nch
wolffd@0 49 for j = 1:nc
wolffd@0 50 if option.root
wolffd@0 51 e(1,j,i) = norm(d(:,j,i));
wolffd@0 52 else
wolffd@0 53 e(1,j,i) = d(:,j,i)'*d(:,j,i);
wolffd@0 54 end
wolffd@0 55 end
wolffd@0 56 end
wolffd@0 57 if option.normal
wolffd@0 58 e = e/sqrt(nl);
wolffd@0 59 end
wolffd@0 60
wolffd@0 61
wolffd@0 62 function [y orig] = eachchunk(orig,option,missing,postchunk)
wolffd@0 63 option.normal = 0;
wolffd@0 64 y = mirrms(orig,option);
wolffd@0 65
wolffd@0 66
wolffd@0 67 function y = combinechunk(old,new)
wolffd@0 68 do = get(old,'Data');
wolffd@0 69 do = do{1}{1};
wolffd@0 70 dn = get(new,'Data');
wolffd@0 71 dn = dn{1}{1};
wolffd@0 72 y = set(old,'ChunkData',sqrt(do^2+dn^2));
wolffd@0 73
wolffd@0 74
wolffd@0 75 function y = afterchunk(orig,length,postoption)
wolffd@0 76 d = get(orig,'Data');
wolffd@0 77 v = mircompute(@afternorm,d,length);
wolffd@0 78 y = set(orig,'Data',v);
wolffd@0 79
wolffd@0 80
wolffd@0 81 function e = afternorm(d,length)
wolffd@0 82 e = d/sqrt(length);