Changeset 484 for trunk

Timestamp:

03/24/11 12:45:12 (14 months ago)

Author:

pierre

Message:

Fix some bugs in id_offset for negative offsets, and for the time_histogram. Rounding errors with int time bins.

Files:

• trunk/src/signals/spikes.py (modified) (8 diffs)

trunk/src/signals/spikes.py

@@ -563 +563 @@
         else:
             hist, edges = numpy.histogram(self.spike_times, bins)
-        if normalized and isinstance(time_bin, int): # what about normalization if time_bin is a sequence?
-            hist *= 1000.0/time_bin
+        hist = hist.astype(float)
+        if normalized: # what about normalization if time_bin is a sequence?
+            hist *= 1000.0/float(time_bin)
         return hist
 
@@ -769 +770 @@
         """
         hist       = self.time_histogram(time_bin, normalized=False)
+        from NeuroTools import analysis
         freq_spect = analysis.simple_frequency_spectrum(hist)
         freq_bin   = 1000.0/self.duration() # Hz
@@ -1192 +1194 @@
         id_list     = numpy.sort(self.id_list)
         N           = len(id_list)
-        
-        for idx in xrange(1,len(id_list)+1):
-            id  = id_list[N-idx]
-            spk = self.spiketrains.pop(id)
-            self.spiketrains[id + offset] = spk
+        if (offset > 0):        
+            for idx in xrange(1, len(id_list)+1):
+                id  = id_list[N-idx]
+                spk = self.spiketrains.pop(id)
+                self.spiketrains[id + offset] = spk
+        if (offset < 0):        
+            for idx in xrange(0, len(id_list)):
+                id  = id_list[idx]
+                spk = self.spiketrains.pop(id)
+                self.spiketrains[id + offset] = spk
     
     def first_spike_time(self):
@@ -1882 +1889 @@
             hist_2 = pairs_generator.spk2[pairs[idx,1]].time_histogram(time_bin)
             if not average:
+                from NeuroTools import analysis
                 results[idx,:] = analysis.ccf(hist_1,hist_2)
             else:
+                from NeuroTools import analysis
                 results += analysis.ccf(hist_1,hist_2)
         if not subplot or not HAVE_PYLAB:
@@ -2186 +2195 @@
         for ev in events:
            ev = numpy.floor(ev/time_bin)
-           if ((ev - t_min_l )> t_start) and (ev + t_max_l ) < t_stop:
+           if ((ev - t_min_l )> t_start) and (ev + t_max_l ) < t_stop:               
                count  += 1
-               result += spk_hist[:,(ev-t_min_l):ev+t_max_l]
+               result += spk_hist[:,(ev-t_start-t_min_l):ev-t_start+t_max_l]
         result /= count
         if average:
@@ -2256 +2265 @@
         else:
             files        = []
-            activity_map = numpy.zeros(self.dimensions)
-            im           = subplot.imshow(activity_map, **kwargs)
-            im.set_clim(bounds[0],bounds[1])
-            pylab.colorbar(im)
+            if float_positions is None:
+                activity_map = numpy.zeros(self.dimensions)
+                im           = subplot.imshow(activity_map, **kwargs)
+                im.set_clim(bounds[0],bounds[1])
+                pylab.colorbar(im)
+            else:
+                rates        = [0]*len(self)
+                im           = subplot.scatter(float_positions[0,:], float_positions[1,:], c=rates, **kwargs)
+                im.set_clim(bounds[0],bounds[1])
+                pylab.colorbar(im)
             count     = 0
             idx       = 0
@@ -2286 +2301 @@
                     im.set_array(activity_map)
                     subplot.title("time = %d ms" %t_start)
-                    manager.canvas.draw()
                     im.set_clim(bounds[0],bounds[1])
+                    manager.canvas.draw()                    
                     fname = "_tmp_spikes_%05d.png" %count
                     #logging.debug("Saving Frame %s", fname)
@@ -2294 +2309 @@
                     files.append(fname)
                     t_start += time_bin
-                    count += 1          
+                    count += 1   
+            elif isinstance(float_positions, numpy.ndarray):
+                if not len(self) == len(float_positions[0]):
+                    raise Exception("Error, the number of flotting positions does not match the number of cells in the SpikeList")
+                while (t_start < t_stop):
+                    rates = [0]*len(self)
+                    while ((time[idx] < t_start + time_bin) and (idx < max_idx)):                                                
+                        rates[pos[idx]] += 1
+                        idx += 1
+                    im = subplot.scatter(float_positions[0,:], float_positions[1,:], c=rates, **kwargs)
+                    subplot.title("time = %d ms" %t_start)
+                    im.set_clim(bounds[0],bounds[1])
+                    manager.canvas.draw()
+                    fname = "_tmp_spikes_%05d.png" %count
+                    #logging.debug("Saving Frame %s", fname)
+                    progress_bar(float(t_start)/t_stop)
+                    pylab.savefig(fname)
+                    files.append(fname)
+                    t_start += time_bin
+                    count += 1   
             command = "mencoder 'mf://_tmp_*.png' -mf type=png:fps=%d -ovc lavc -lavcopts vcodec=wmv2 -oac copy -o %s" %(fps,output)
             logging.debug(command)