Mercurial > hg > ltpda

annotate m-toolbox/classes/@ao/hist.m @ 1:2014ba5b353a database-connection-manager

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Remove old code
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Sat, 03 Dec 2011 18:13:55 +0100
parents f0afece42f48
children
Ignore whitespace changes - Everywhere: Within whitespace: At end of lines:
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0
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Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
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1 % HIST overloads the histogram function (hist) of MATLAB for Analysis Objects.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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2 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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Daniele Nicolodi <nicolodi@science.unitn.it>
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3 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 % DESCRIPTION: HIST overloads the histogram function (hist) of MATLAB for
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 % Analysis Objects.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 % CALL: b = hist(a)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8 % b = hist(a, pl)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 % INPUTS: a - input analysis object(s)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 % pl - a parameter list
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Daniele Nicolodi <nicolodi@science.unitn.it>
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12 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % OUTPUTS: b - xydata type analysis object(s) containing the
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 % histogrammed data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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15 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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16 % <a href="matlab:utils.helper.displayMethodInfo('ao', 'hist')">Parameters Description</a>
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Daniele Nicolodi <nicolodi@science.unitn.it>
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17 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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18 % WARNING: the '.' method of calling hist() doesn't work since AOs have a
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 % property called 'hist'. Use the standard function call instead:
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 % >> a.hist % returns the history object and doesn't call ao/hist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % >> hist(a) % calls ao/hist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 % VERSION: $Id: hist.m,v 1.42 2011/04/08 08:56:12 hewitson Exp $
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 %
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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27
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 function varargout = hist(varargin)
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29
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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33 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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35
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Daniele Nicolodi <nicolodi@science.unitn.it>
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36 import utils.const.*
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 % Collect all AOs and plists
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Daniele Nicolodi <nicolodi@science.unitn.it>
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44 [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 [pli, pl_invars, rest] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46
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Daniele Nicolodi <nicolodi@science.unitn.it>
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47 pl = parse(pli, getDefaultPlist('Number of bins'));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 normalize = utils.prog.yes2true(find(pl, 'norm'));
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49
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 bs = copy(as, nargout);
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52
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53
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 % Get parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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55 N = find(pl, 'N');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 X = find(pl, 'X');
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57
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 %---------------- Loop over input AOs
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59
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 % start looping
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 for jj=1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 % Histogram this data
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 if isempty(X)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 [n,x] = hist(bs(jj).data.y, N);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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66 [n,x] = hist(bs(jj).data.y, X);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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67 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 % Keep the data shape of the input AO
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 if size(bs(jj).data.y, 1) ~= 1
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Daniele Nicolodi <nicolodi@science.unitn.it>
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70 x = x.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 n = n.';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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72 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 % In the case of equally spaced bins, introduce normalization
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Daniele Nicolodi <nicolodi@science.unitn.it>
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74 if normalize && isempty(X)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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75 dx = mean(diff(x));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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76 n = n / sum(n) / dx;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 yunits = (bs(jj).data.yunits)^(-1);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 dy = sqrt(n);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 else
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80 yunits = 'Count';
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Daniele Nicolodi <nicolodi@science.unitn.it>
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81 dy = sqrt(n);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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82 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 % make a new xydata object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 xy = xydata(x, n);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 xy.setXunits(bs(jj).data.yunits);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 xy.setYunits(yunits);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 xy.setDy(dy);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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88 % make output analysis object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89 bs(jj).data = xy;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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90 % name for this object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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91 bs(jj).name = sprintf('hist(%s)', ao_invars{jj});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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92 % Add history
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Daniele Nicolodi <nicolodi@science.unitn.it>
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93 bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), bs(jj).hist);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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94 % Add to outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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95 % clear errors
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Daniele Nicolodi <nicolodi@science.unitn.it>
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96 bs(jj).clearErrors;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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97 end % end of AO loop
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Daniele Nicolodi <nicolodi@science.unitn.it>
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98
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Daniele Nicolodi <nicolodi@science.unitn.it>
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99 % Set output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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100 if nargout == numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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101 % List of outputs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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102 for ii = 1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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103 varargout{ii} = bs(ii);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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104 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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105 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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106 % Single output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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107 varargout{1} = bs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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108 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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109 end
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110
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Daniele Nicolodi <nicolodi@science.unitn.it>
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111 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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112 % Get Info Object
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113 %--------------------------------------------------------------------------
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114 function ii = getInfo(varargin)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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115 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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116 sets = {};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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117 pls = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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118 elseif nargin == 1 && ~isempty(varargin{1}) && ischar(varargin{1})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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119 sets{1} = varargin{1};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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120 pls = getDefaultPlist(sets{1});
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121 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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122 sets = {'Number Of Bins', 'Bin Centres'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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123 pls = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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124 for kk=1:numel(sets)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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125 pls = [pls getDefaultPlist(sets{kk})];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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126 end
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127 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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128 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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129 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.sigproc, '$Id: hist.m,v 1.42 2011/04/08 08:56:12 hewitson Exp $', sets, pls);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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130 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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131
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Daniele Nicolodi <nicolodi@science.unitn.it>
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132 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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133 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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134 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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135
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Daniele Nicolodi <nicolodi@science.unitn.it>
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136 function plout = getDefaultPlist(set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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137 persistent pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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138 persistent lastset;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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139 if exist('pl', 'var')==0 || isempty(pl) || ~strcmp(lastset, set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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140 pl = buildplist(set);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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141 lastset = set;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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142 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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143 plout = pl;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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144 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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145
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Daniele Nicolodi <nicolodi@science.unitn.it>
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146 function plo = buildplist(set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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147 switch lower(set)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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148 case 'number of bins'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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149 plo = plist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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150
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Daniele Nicolodi <nicolodi@science.unitn.it>
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151 % N number of bins
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Daniele Nicolodi <nicolodi@science.unitn.it>
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152 p = param({'N', ['The number of bins to compute the histogram on.']}, {1, {10}, paramValue.OPTIONAL});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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153 plo.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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154
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Daniele Nicolodi <nicolodi@science.unitn.it>
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155 % normalized output
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Daniele Nicolodi <nicolodi@science.unitn.it>
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156 p = param({'norm', ['Normalized output. If set to true, it will give the output comparable <br>', ...
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Daniele Nicolodi <nicolodi@science.unitn.it>
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157 'to the normal distrubution PDF. <br>']}, paramValue.FALSE_TRUE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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158 plo.append(p);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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159
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Daniele Nicolodi <nicolodi@science.unitn.it>
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160 case 'bin centres'
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Daniele Nicolodi <nicolodi@science.unitn.it>
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161 plo = plist({'X', 'A vector of bin centers.'}, paramValue.EMPTY_DOUBLE);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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162 otherwise
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Daniele Nicolodi <nicolodi@science.unitn.it>
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163 error('### Unknown default plist for the set [%s]', set);
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
164 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
165 end
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
166
f0afece42f48 Import.
Daniele Nicolodi <nicolodi@science.unitn.it>
parents:
diff changeset
167