Changeset 396 for trunk

Timestamp:

06/09/09 09:57:02 (3 years ago)

Author:

pierre

Message:

Force all the numpy arrays of the SpikeList, containing only int and dt rounded spike times to be 32 bits float in order to save some memory. Add also a psth method, test should follows...

Location:

trunk/src

Files:

• io.py (modified) (1 diff)
• signals/spikes.py (modified) (9 diffs)

trunk/src/io.py

@@ -172 +172 @@
                     data.append(id)
         logging.debug("Loaded %d lines of data from %s" % (len(data), self))
-        return data
+        return numpy.array(data, numpy.float32)
 
     def write(self, object):

trunk/src/signals/spikes.py

@@ -86 +86 @@
         self.t_start     = t_start
         self.t_stop      = t_stop
-        self.spike_times = numpy.array(spike_times, float)
+        self.spike_times = numpy.array(spike_times, numpy.float32)
 
         # If t_start is not None, we resize the spike_train keeping only
@@ -584 +584 @@
         """
         N              = (self.t_stop-self.t_start)/dt
-        vec_1          = numpy.zeros(N, float)
-        vec_2          = numpy.zeros(N, float)
+        vec_1          = numpy.zeros(N, numpy.float32)
+        vec_2          = numpy.zeros(N, numpy.float32)
         result         = numpy.zeros(N, float)
         idx_spikes     = numpy.array(self.spike_times/dt,int)
@@ -740 +740 @@
         
         if not hasattr(spikes, 'size'): # is an array:
-            spikes = numpy.array(spikes)
+            spikes = numpy.array(spikes, numpy.float32)
         N = len(spikes)
         
@@ -768 +768 @@
                 [0,1,2,3,....,9999]
         """
-        return numpy.array(self.spiketrains.keys())
+        return numpy.array(self.spiketrains.keys(), int)
 
     def copy(self):
@@ -787 +787 @@
         if len(self) > 0:
             if self.t_start is None:
-                start_times = numpy.array([self.spiketrains[idx].t_start for idx in self.id_list()])
+                start_times = numpy.array([self.spiketrains[idx].t_start for idx in self.id_list()], numpy.float32)
                 self.t_start = numpy.min(start_times)
                 logging.debug("Warning, t_start is infered from the data : %f" %self.t_start)
@@ -793 +793 @@
                     self.spiketrains[id].t_start = self.t_start
             if self.t_stop is None:
-                stop_times = numpy.array([self.spiketrains[idx].t_stop for idx in self.id_list()])
+                stop_times = numpy.array([self.spiketrains[idx].t_stop for idx in self.id_list()], numpy.float32)
                 self.t_stop  = numpy.max(stop_times)
                 logging.debug("Warning, t_stop  is infered from the data : %f" %self.t_stop)
@@ -1462 +1462 @@
         if newnum:
             M -= 1
-        spike_hist = numpy.zeros((N, M), float)
+        spike_hist = numpy.zeros((N, M), numpy.float32)
         subplot    = get_display(display)
         for idx,id in enumerate(self.id_list()):
@@ -1961 +1961 @@
             set_axis_limits(subplot, t_start-0.05*length, t_stop+0.05*length, min_id-2, max_id+2)
             pylab.draw()
+
+
+    def psth(self, events, average=True, time_bin=2, t_min=50, t_max=50, display = False, kwargs={}):
+        """
+        Return the psth of the cells contained in the SpikeList according to selected events, 
+        on a time window t_spikes - tmin, t_spikes + tmax
+        Can return either the averaged psth (average = True), or an array of all the
+        psth triggered by all the spikes.
+            
+        Inputs:
+            events  - Can be a SpikeTrain object (and events will be the spikes) or just a list 
+                      of times
+            average - If True, return a single vector of the averaged waveform. If False, 
+                      return an array of all the waveforms.
+            t_min   - Time (>0) to average the signal before an event, in ms (default 0)
+            t_max   - Time (>0) to average the signal after an event, in ms  (default 100)
+            display - if True, a new figure is created. Could also be a subplot.
+            kwargs  - dictionary contening extra parameters that will be sent to the plot 
+                      function
+            
+        Examples:
+            >> vm.psth(spktrain, average=False, t_min = 50, t_max = 150)
+            >> vm.psth(spktrain, average=True)
+            >> vm.psth(range(0,1000,10), average=False, display=True)
+            
+        See also
+            SpikeTrain.spike_histogram
+        """
+        
+        if isinstance(events, SpikeTrain):
+            events = events.spike_times
+        assert (t_min >= 0) and (t_max >= 0), "t_min and t_max should be greater than 0"
+        assert len(events) > 0, "events should not be empty and should contained at least one element"
+
+        spk_hist = self.spike_histogram(time_bin)
+        subplot  = get_display(display)
+        count    = 0
+        result   = numpy.zeros((len(self), (t_max+t_min)/time_bin), numpy.float32)
+        t_min_l  = numpy.floor(t_min/time_bin)
+        t_max_l  = numpy.floor(t_max/time_bin)
+        for ev in events:
+           ev = int((ev-self.t_start)/time_bin)
+           if (ev > self.t_start + t_min_l) and ev < self.t_stop-t_max_l:
+               count  += 1
+               result += spk_hist[:,(ev-t_min_l):ev+t_max_l]
+        result /= count
+        if average:
+           result = numpy.mean(result, 0)
+            
+        if not subplot or not HAVE_PYLAB:
+            return result
+        else:
+            xlabel = "Time (ms)"
+            ylabel = "PSTH"
+            time   = numpy.linspace(-t_min, t_max, (t_min+t_max)/time_bin)
+            set_labels(subplot, xlabel, ylabel)
+            if average:
+                subplot.plot(time, result, **kwargs)
+            else:
+                for idx in xrange(len(result)):
+                    subplot.plot(time, result[idx,:], c='0.5', **kwargs)
+                    subplot.hold(1)
+                result = numpy.mean(result, 0)
+                subplot.plot(time, result, c='k', **kwargs)
+            xmin, xmax, ymin, ymax = subplot.axis()
+            subplot.plot([0,0],[ymin, ymax], c='r')
+            set_axis_limits(subplot, -t_min, t_max, ymin, ymax)
+            pylab.draw()
+        return result
 
 
@@ -2182 +2251 @@
             convert()
         """
-        data = numpy.array(self.convert("[times, ids]"))
+        data = numpy.array(self.convert("[times, ids]"), numpy.float32)
         data = numpy.transpose(data)
         return data