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annotate m-toolbox/classes/+utils/@helper/plot_gauss_hist.m @ 0:f0afece42f48

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Import.
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
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Daniele Nicolodi <nicolodi@science.unitn.it>
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1 function plot_gauss_hist(varargin)
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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 % Check if this is a call for parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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4 if utils.helper.isinfocall(varargin{:})
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Daniele Nicolodi <nicolodi@science.unitn.it>
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5 varargout{1} = getInfo(varargin{3});
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Daniele Nicolodi <nicolodi@science.unitn.it>
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6 return
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Daniele Nicolodi <nicolodi@science.unitn.it>
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7 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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8
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Daniele Nicolodi <nicolodi@science.unitn.it>
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9 % Collect input variable names
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Daniele Nicolodi <nicolodi@science.unitn.it>
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10 in_names = cell(size(varargin));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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11 for ii = 1:nargin,in_names{ii} = inputname(ii);end
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12
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Daniele Nicolodi <nicolodi@science.unitn.it>
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13 % Collect all AOs
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Daniele Nicolodi <nicolodi@science.unitn.it>
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14 [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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15 [pli, pl_invars, rest] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
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16 pl = parse(pli, getDefaultPlist());
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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 % Decide on a deep copy or a modify
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Daniele Nicolodi <nicolodi@science.unitn.it>
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19 bs = copy(as, nargout);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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20 % get parameters
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Daniele Nicolodi <nicolodi@science.unitn.it>
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21 timestring = find(pl, 'timestring');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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22 % We filter out the data3D objects here since we don't know what to do
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Daniele Nicolodi <nicolodi@science.unitn.it>
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23 % with them so far.
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Daniele Nicolodi <nicolodi@science.unitn.it>
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24 aos = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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25 inhists = [];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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26 for kk=1:numel(bs)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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27 if isa(bs(kk).data, 'data3D')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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28 warning('!!! Skipping ao [%s] - can''t operate on data3D objects at the moment.', bs(kk).name);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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29 else
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Daniele Nicolodi <nicolodi@science.unitn.it>
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30 aos = [aos bs(kk)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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31 inhists = [inhists bs(kk).hist];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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32 end
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33 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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34 if isempty(aos)
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35 error('### Please give at least one AO of type cdata or data2D');
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36 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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37 x = aos(2).y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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38 gauss_value = aos(1).y;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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39 stdev = aos(1).dy;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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40 mean_val = mean(aos(2));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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41 miny = find(aos(1).procinfo,'min');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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42 maxy = find(aos(1).procinfo,'max');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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43 n = find(aos(1).procinfo,'bins');
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44
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Daniele Nicolodi <nicolodi@science.unitn.it>
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45 [ny,nx]=hist(x,n,miny,maxy);
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Daniele Nicolodi <nicolodi@science.unitn.it>
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46 max_val = max(ny);
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47
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Daniele Nicolodi <nicolodi@science.unitn.it>
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48 yunit = aos(2).yunits.strs;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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49 % figure,
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Daniele Nicolodi <nicolodi@science.unitn.it>
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50 hist(x,n)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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51 % xlabel(sprintf(' [%s]',yunit{1}));
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Daniele Nicolodi <nicolodi@science.unitn.it>
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52 ylabel('Counts');
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Daniele Nicolodi <nicolodi@science.unitn.it>
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53 hold on
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Daniele Nicolodi <nicolodi@science.unitn.it>
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54 plot(nx,max_val*gauss_value,'r')
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55 hold off
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Daniele Nicolodi <nicolodi@science.unitn.it>
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56 v = axis;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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57 mean_value=['Mean: ',num2str(mean_val.y)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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58 std_value=['Sigma: ',num2str(stdev)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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59 max_value=['Max: ',num2str(max_val)];
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Daniele Nicolodi <nicolodi@science.unitn.it>
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60 xper=.27;yper=.05;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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61 text(v(1)*xper+v(2)*(1-xper),v(3)*yper+v(4)*(1-yper),mean_value)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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62 yper=yper+.05;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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63 text(v(1)*xper+v(2)*(1-xper),v(3)*yper+v(4)*(1-yper),std_value)
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Daniele Nicolodi <nicolodi@science.unitn.it>
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64 yper=yper+.05;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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65 text(v(1)*xper+v(2)*(1-xper),v(3)*yper+v(4)*(1-yper),max_value)
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66
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67 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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68 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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69 % Get Info Object
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70 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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71 function ii = getInfo(varargin)
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72 if nargin == 1 && strcmpi(varargin{1}, 'None')
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Daniele Nicolodi <nicolodi@science.unitn.it>
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73 sets = {};
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74 pl = [];
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75 else
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76 sets = {'Default'};
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Daniele Nicolodi <nicolodi@science.unitn.it>
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77 pl = getDefaultPlist;
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Daniele Nicolodi <nicolodi@science.unitn.it>
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78 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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79 % Build info object
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Daniele Nicolodi <nicolodi@science.unitn.it>
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80 ii = minfo(mfilename, 'ao', 'ltpda', utils.const.categories.op, '$Id: plot_gauss_hist.m,v 1.2 2011/03/28 12:45:45 hewitson Exp $', sets, pl);
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81 end
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82
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Daniele Nicolodi <nicolodi@science.unitn.it>
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83 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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84 % Get Default Plist
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Daniele Nicolodi <nicolodi@science.unitn.it>
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85 %--------------------------------------------------------------------------
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Daniele Nicolodi <nicolodi@science.unitn.it>
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86 function pl_default = getDefaultPlist()
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Daniele Nicolodi <nicolodi@science.unitn.it>
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87 pl_default = plist('timestring','');
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88 end
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Daniele Nicolodi <nicolodi@science.unitn.it>
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89
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90 % END