diff m-toolbox/classes/@ao/hist.m @ 0:f0afece42f48

Import.
author Daniele Nicolodi <nicolodi@science.unitn.it>
date Wed, 23 Nov 2011 19:22:13 +0100
parents
children
line wrap: on
line diff
--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/m-toolbox/classes/@ao/hist.m	Wed Nov 23 19:22:13 2011 +0100
@@ -0,0 +1,167 @@
+% HIST overloads the histogram function (hist) of MATLAB for Analysis Objects.
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+%
+% DESCRIPTION: HIST overloads the histogram function (hist) of MATLAB for
+%              Analysis Objects.
+%
+% CALL:        b = hist(a)
+%              b = hist(a, pl)
+%
+% INPUTS:      a  - input analysis object(s)
+%              pl - a parameter list
+%
+% OUTPUTS:     b  - xydata type analysis object(s) containing the
+%                   histogrammed data
+%
+% <a href="matlab:utils.helper.displayMethodInfo('ao', 'hist')">Parameters Description</a>
+%
+% WARNING: the '.' method of calling hist() doesn't work since AOs have a
+% property called 'hist'. Use the standard function call instead:
+%
+%    >> a.hist  % returns the history object and doesn't call ao/hist
+%    >> hist(a) % calls ao/hist
+%
+% VERSION:     $Id: hist.m,v 1.42 2011/04/08 08:56:12 hewitson Exp $
+%
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+function varargout = hist(varargin)
+
+  % Check if this is a call for parameters
+  if utils.helper.isinfocall(varargin{:})
+    varargout{1} = getInfo(varargin{3});
+    return
+  end
+
+  import utils.const.*
+  utils.helper.msg(msg.PROC3, 'running %s/%s', mfilename('class'), mfilename);
+  
+  % Collect input variable names
+  in_names = cell(size(varargin));
+  for ii = 1:nargin,in_names{ii} = inputname(ii);end
+
+  % Collect all AOs and plists
+  [as, ao_invars] = utils.helper.collect_objects(varargin(:), 'ao', in_names);
+  [pli, pl_invars, rest] = utils.helper.collect_objects(varargin(:), 'plist', in_names);
+
+  pl = parse(pli, getDefaultPlist('Number of bins'));
+  normalize = utils.prog.yes2true(find(pl, 'norm'));
+   
+  % Decide on a deep copy or a modify
+  bs = copy(as, nargout);
+
+
+  % Get parameters
+  N = find(pl, 'N');
+  X = find(pl, 'X');
+
+  %---------------- Loop over input AOs
+
+  % start looping
+  for jj=1:numel(bs)
+    % Histogram this data
+    if isempty(X)
+      [n,x] = hist(bs(jj).data.y, N);
+    else
+      [n,x] = hist(bs(jj).data.y, X);
+    end
+    % Keep the data shape of the input AO
+    if size(bs(jj).data.y, 1) ~= 1
+      x = x.';
+      n = n.';
+    end
+    % In the case of equally spaced bins, introduce normalization
+    if normalize && isempty(X)
+      dx = mean(diff(x)); 
+      n = n / sum(n) / dx;
+      yunits = (bs(jj).data.yunits)^(-1);
+      dy = sqrt(n);
+    else
+      yunits = 'Count';
+      dy = sqrt(n);
+    end
+    % make a new xydata object
+    xy = xydata(x, n);
+    xy.setXunits(bs(jj).data.yunits);
+    xy.setYunits(yunits);
+    xy.setDy(dy);
+    % make output analysis object
+    bs(jj).data = xy;
+    % name for this object
+    bs(jj).name = sprintf('hist(%s)', ao_invars{jj});
+    % Add history
+    bs(jj).addHistory(getInfo('None'), pl, ao_invars(jj), bs(jj).hist);
+    % Add to outputs
+    % clear errors
+    bs(jj).clearErrors;
+  end % end of AO loop
+
+  % Set output
+  if nargout == numel(bs)
+    % List of outputs
+    for ii = 1:numel(bs)
+      varargout{ii} = bs(ii);
+    end
+  else
+    % Single output
+    varargout{1} = bs;
+  end
+end
+
+%--------------------------------------------------------------------------
+% Get Info Object
+%--------------------------------------------------------------------------
+function ii = getInfo(varargin)
+  if nargin == 1 && strcmpi(varargin{1}, 'None')
+    sets = {};
+    pls   = [];
+  elseif nargin == 1 && ~isempty(varargin{1}) && ischar(varargin{1})
+    sets{1} = varargin{1};
+    pls = getDefaultPlist(sets{1});
+  else
+    sets = {'Number Of Bins', 'Bin Centres'};
+    pls = [];
+    for kk=1:numel(sets)
+      pls = [pls getDefaultPlist(sets{kk})];
+    end
+  end
+  % Build info object
+  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);
+end
+
+%--------------------------------------------------------------------------
+% Get Default Plist
+%--------------------------------------------------------------------------
+
+function plout = getDefaultPlist(set)
+  persistent pl;
+  persistent lastset;
+  if exist('pl', 'var')==0 || isempty(pl) || ~strcmp(lastset, set)
+    pl = buildplist(set);
+    lastset = set;
+  end
+  plout = pl;
+end
+
+function plo = buildplist(set)
+  switch lower(set)
+    case 'number of bins'
+      plo = plist;
+      
+      % N number of bins
+      p = param({'N', ['The number of bins to compute the histogram on.']}, {1, {10}, paramValue.OPTIONAL});
+      plo.append(p);
+      
+      % normalized output
+      p = param({'norm', ['Normalized output. If set to true, it will give the output comparable <br>', ...
+        'to the normal distrubution PDF. <br>']}, paramValue.FALSE_TRUE);             
+      plo.append(p);
+      
+    case 'bin centres'
+      plo = plist({'X', 'A vector of bin centers.'}, paramValue.EMPTY_DOUBLE);
+    otherwise
+      error('### Unknown default plist for the set [%s]', set);
+  end
+end
+
+