[Pybrainsim-activity] SF.net SVN: pybrainsim:[111] trunk/src/Experiment.py

[<rg...@us...>]

Revision: 111
          http://pybrainsim.svn.sourceforge.net/pybrainsim/?rev=111&view=rev
Author:   rgoj
Date:     2009-08-15 14:54:55 +0000 (Sat, 15 Aug 2009)

Log Message:
-----------
* Moved the matplotlib functions responsible for multiple axes, plotting, etc. to a new plotChannels() method.
* The plotChannels() method is now called from plotRecording() to plot both ongoing and event-related activity.

Modified Paths:
--------------
    trunk/src/Experiment.py

Modified: trunk/src/Experiment.py
===================================================================
--- trunk/src/Experiment.py	2009-08-15 11:32:34 UTC (rev 110)
+++ trunk/src/Experiment.py	2009-08-15 14:54:55 UTC (rev 111)
@@ -118,28 +118,21 @@
         
         return channelERPs        
 
-    def plotRecording(self):
-        # Creating a new matplotlib figure for the plots
-        fig = figure()
+    def plotChannels(self, channelData, time, stimuli, fig, bottom, height):
+        # Multiple axes will be created, all sharing the same properties
+        axes = []
+        axesProperties = dict([])
         
         # Each channel will have a plot of the same width and height
         plotWidth = 0.8
-        plotHeight = 0.4/len(self.recording)
+        plotHeight = height/len(self.recording)
         
-        #
-        # Ongoing activity
-        #
-
-        # Multiple axes will be created, all sharing the same properties
-        axes = []
-        axesProperties = dict([])
-        
-        for channel in range(len(self.recording)):
+        for channel in range(len(channelData)):
             # Plotting the recording for each channel
-            axes.append(fig.add_axes([0.1, 0.55 + plotHeight * channel,
+            axes.append(fig.add_axes([0.1, bottom + plotHeight * channel,
                                           plotWidth, plotHeight],
                                          **axesProperties))
-            axes[channel].plot(self.timePoints, self.recording[channel])
+            axes[channel].plot(time, channelData[channel])
             axes[channel].set_ylabel("CH " + str(channel+1))
             
             # All channels must be zoomed in/out and moved at the same time
@@ -148,25 +141,32 @@
                 axesProperties['sharey'] = axes[0]
                 
             # Plotting vertical lines to indicate times of stimuli
-            for i in range(len(self.stimulusTimes[0])):
-                axvline(self.stimulusTimes[0][i], color='r')
+            if isinstance(stimuli, float):
+                axvline(stimuli, color='r')
+            else:
+                for i in range(len(stimuli)):
+                    axvline(stimuli[i], color='r')
         
         # Time values will be printed only for the lowest axis
         axes[0].set_xlabel("Time")
         for axis in axes[1:]:
             setp(axis.get_xticklabels(), visible=False)
+    
+    def plotRecording(self):
+        # Creating a new matplotlib figure for the plots
+        fig = figure()
+
+        # Ongoing activity
+        self.plotChannels(self.recording, self.timePoints,
+                          self.stimulusTimes[0], fig, 0.55, 0.4)
+        figtext( 0.93, 0.75, 'Ongoing activity', rotation = 'vertical', 
+                verticalalignment = 'center')
         
-        #
         # Event-related activity
-        #
+        self.plotChannels(self.getERP(), self.epochTimePoints, 
+                          0.0, fig, 0.075, 0.4)
+        figtext( 0.93, 0.275, 'Event-related activity', rotation = 'vertical',
+                verticalalignment = 'center' )
         
-        print self.getERP()
-
-        #subplot(212)
-        #plot(self.epochTimePoints, self.getERP(), linewidth=1.0)
-        #axvline( 0.0, color='r' )
-        #xlabel('Time (s)')
-        #ylabel('Amplitude')
-        #title('Simulated ERP')
-
+        # Showing the prepared figure
         show()


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