completed function to check pulse parameter influence

MATLAB/+qc/check_pulse_4chan_parameter_dependency.m

@@ -1,16 +1,36 @@
 function check_pulse_4chan_parameter_dependency(pulse, check_parameter, check_values, varargin)
+% plot function to visualize the influence of one pulse parameter on the
+% pulse shape:
+% ----------------------------------------------------------------------
+% input:
+% pulse               : loaded qctoolkit pulse
+% check_paramter      : name of the paramter under investigation
+% check_values        : values the parameter is set to, array []
+% varargin            : standard varargin that one also uses for
+%                       qc.plot_pulse
+% ----------------------------------------------------------------------
+% written by Marcel Meyer 08|2018 (marcel.meyer1@rwth-aachen.de)
+
+global plsdata
 
 defaultArgs = struct(...
   'sample_rate',         plsdata.awg.sampleRate, ... % in 1/s, converted to 1/ns below
   'channel_mapping',     py.None, ...
   'window_mapping' ,     py.None, ...
-  'parameters',          struct() ...
+  'parameters',          struct(), ...
+  'removeTrigChans',     true, ...
+  'figID',               2018 ...
   );
 
 args = util.parse_varargin(varargin, defaultArgs);
+
+if isempty(args.channel_mapping) || args.channel_mapping == py.None
+		args.channel_mapping = py.dict(py.zip(pulse.defined_channels, pulse.defined_channels));
+end
+
 args.sample_rate = args.sample_rate * 1e-9; % convert to 1/ns
 
-figure();
+figure(args.figID);
 
 for k = 1:numel(check_values)
   args.parameters.(check_parameter) = check_values(k);
@@ -19,8 +39,24 @@ function check_pulse_4chan_parameter_dependency(pulse, check_parameter, check_va
   data = util.py.py2mat(py.qctoolkit.pulses.plotting.render(instantiatedPulse, pyargs('sample_rate', args.sample_rate, 'render_measurements', true)));
 
   subplot(1, numel(check_values), k);
-  plot(data)
 
+  hold on;
+
+  if args.removeTrigChans
+    data{2} = rmfield(data{2}, 'MTrig');
+    data{2} = rmfield(data{2}, 'M1');
+    data{2} = rmfield(data{2}, 'M2');
+  end
+
+  channelNames = fieldnames(data{2});
+
+  for channelInd = 1:numel(channelNames)
+    plot(data{1}*1e-9, data{2}.(channelNames{channelInd}));
+  end
+  hold off;
+  legend(channelNames);
+  xlabel('t(s)');
+  title(sprintf('%s = %.2d', check_parameter, check_values(k)));
 end
 
 end