Graphing in Matlab

The main purpose of this page is simply as a place to store the code that I've written to graph multiple paramaters on the one axes; it doesn't exist in github, and I'm hesitant to throw it away, as it may come in handy in the future.

Lining up time series data

function graphs = graphTimeSeries( ...
  parent, sample_data, cal_data, dimension, params )
%GRAPHTIMESERIES Graphs the given data in a time series style.
%
% Inputs:
%   parent       - handle to the parent container.
%   sample_data  - struct containing sample data.
%   cal_data     - struct containing sample metadata.
%   dimension    - index into the sample_data.dimensions vector, indicating
%                  which dimension should be the x axis.
%   params       - Optional. indices of parameters that should be graphed. 
%                  If omitted, all parameters are graphed.
%
% Outputs:
%   graphs      - handles to axes on which the data has been graphed.
%
% Author: Paul McCarthy <[email protected]>
%
  error(nargchk(4,5,nargin));
  
  if ~ishandle( parent),       error('parent must be a handle');            end
  if ~isstruct( sample_data),  error('sample_data must be a struct');       end
  if ~isstruct( cal_data),     error('cal_data must be a struct');          end
  if ~isnumeric(dimension)...
  || ~isscalar( dimension),    error('dimension must be a scalar numeric'); end

  if     nargin == 4         params = 1:length(sample_data.parameters); 
  elseif ~isnumeric(params), error('params must be a numeric'); 
  end
  
  % get rid of parameters that we should ignore
  sample_data.parameters = sample_data.parameters(params);
  cal_data   .parameters = cal_data   .parameters(params);
  
  offset = 0.02;
  
  graphs = [];
  lines  = [];

  for k = 1:length(sample_data.parameters)
    
    name = sample_data.parameters(k).name;
    uom  = imosParameters(name, 'uom');
    
    % create the axes
    graphs(k) = axes('Parent', parent,...
                     'Color', 'none', ...
                     'Units', 'normalized',...
                     'XTick', []);
    
    set(get(graphs(k), 'YLabel'), 'String', [name ' ' uom]);
    
    % make sure line colour alternates; because we are creating 
    % multiple axes, this is not done automatically for us
    col = get(graphs(k), 'ColorOrder');
    col = col(mod(k,length(col))+1,:);
    
    set(graphs(k), 'YColor', col);
    
    % create the data plot
    lines(k) = line(sample_data.dimensions(dimension).data, ...
                    sample_data.parameters(k)        .data,...
                    'Color', col);
    
    % set y ticks
    yLimits = get(graphs(k), 'YLim');
    yStep   = (yLimits(2) - yLimits(1)) / 5;
    yTicks  = yLimits(1):yStep:yLimits(2);
    set(graphs(k), 'YTick', yTicks);
    
    get(graphs(k), 'TightInset')
    get(graphs(k), 'Position')
           
    if k == 1, continue; end;
    
    % resize all previous axes to make 
    % room for the y axis for this axis
    for m = 1:k-1
      pos = get(graphs(m), 'Position');
      pos(1) = pos(1) + offset;
      pos(3) = pos(3) - offset;
      set(graphs(m), 'Position', pos);
    end
    
    % scale this axis' x limits so the data in this 
    % axis lines up horizontally with the data from 
    % the previous axes
    oldLim = get(graphs(1), 'XLim');
    pos    = get(graphs(1), 'Position');
    
    newLim(1) = oldLim(1) - (k-1) * offset * (oldLim(2) - oldLim(1)) / pos(3);
    newLim(2) = oldLim(2);
      
    set(graphs(k), 'XLim', newLim);
  end
  
  % set x labels and ticks on graph 1
  xLabel = sample_data.dimensions(dimension).name;
  set(get(graphs(1), 'XLabel'), 'String', xLabel);
  
  xLimits = get(graphs(1), 'XLim');
  xStep   = (xLimits(2) - xLimits(1)) / 5;
  xTicks = [xLimits(1):xStep:xLimits(2)];
  
  set(graphs(1), 'XTick', xTicks);
  
  % if the x dimension is time, convert 
  % the tick labels into strings
  if strcmpi(xLabel, 'time')
    xTicks = datestr(xTicks); 
    set(graphs(1), 'XTickLabel', xTicks);
  end
  
  % add a legend
  legend(lines, {sample_data.parameters.name});
  
end