Changeset 209

Timestamp:

09/23/08 18:50:44 (4 months ago)

Author:

pierre

Message:

Bugs and errors, like always. Implement the activity_movie function in a faster way, clean also all the AnalogSignal? part. Should work. To enhance compatibility, it would be good if pyNN could save, in the header, dimensions=[x,y,z] instead of dimensions=x\ty\z\. I will change it, hope nobody will be too affected. Add some functions to the AnalogSignal? object, like append, time_slice, id_slice, ...

Files:

• branches/cleanup/src/analysis.py (modified) (2 diffs)
• branches/cleanup/src/io.py (modified) (4 diffs)
• branches/cleanup/src/signals.py (modified) (21 diffs)

branches/cleanup/src/analysis.py

@@ -8 +8 @@
-
-import os, numpy
-
-
-def ccf(x, y, axis=None):
@@ -60 +59 @@
-    return iFxy/varxy
-
-
-
-
-
-
-
-
-
-
-def record(output, cfilename = 'SpikeTrainPlay.wav', fs=44100, enc = 'pcm26'):
-    """ record the 'sound' produced by a neuron. Takes a spike train as the
-    output.
-    >>> record(my_spike_train)
-    """
-
-
-    # from the spike list
-    simtime_seconds = (output.t_stop - output.t_start)/1000.
-    #time = numpy.linspace(0, simtime_seconds , fs*simtime_seconds)
-    (trace,time) = numpy.histogram(output.spike_times*1000., fs*simtime_seconds)
-
-    # TODO convolve with proper spike...
-    spike = numpy.ones((fs/1000.,)) # one ms
-    trace = numpy.convolve(trace, spike, mode='same')#/2.0
-    trace /= numpy.abs(trace).max() * 1.1
-    try:
-        from scikits.audiolab import wavwrite
-    except ImportError:
-        print "You need the scikits.audiolab package to produce sounds !"
-    wavwrite(trace, cfilename, fs = fs, enc = enc)
-
-
-
-def play(output):
-    """
-    plays a spike list to the audio output
-    play(spike_list) where spike_list is a spike_list object
-    see playing_with_simple_single_neuron.py for a sample use
-    >>> play(my_spike_train)
-    TODO: make it possible to play multiple spike trains in stereo
-    """
-
-
-    from tempfile import mkstemp
-    fd, cfilename   = mkstemp('SpikeListPlay.wav')
-    try:
-        record(output, cfilename)
-        import pyaudio
-        import wave
-
-        chunk = 1024
-        wf = wave.open(cfilename, 'rb')
-        p = pyaudio.PyAudio()
-
-        # open stream
-        stream = p.open(format =
-                        p.get_format_from_width(wf.getsampwidth()),
-                        channels = wf.getnchannels(),
-                        rate = wf.getframerate(),
-                        output = True)
-
-        # read data
-        data = wf.readframes(chunk)
-
-        # play stream
-        while data != '':
-            stream.write(data)
-            data = wf.readframes(chunk)
-
-        stream.close()
-        p.terminate()
-    except:
-        print "Error playing the SpikeTrain "
-        # finally
-        os.remove(cfilename)
-
-    # Python 2.4 compatibility
-    # finally:
-    os.remove(cfilename)
-
-def _dict_max(D):

branches/cleanup/src/io.py

@@ -54 +54 @@
-        # The simplest way to do that, for the moment, is to supposed that you have
-        # numpy 1.0.4 :-)
-
+, delimiter="\t"
-
-
@@ -73 +73 @@
-        the SpikeList object, if saved in a text file
-        """
-
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+
-    def write_header(self, spikelist, filename):
-        """
@@ -97 +88 @@
-        f = open(filename,"w")
-        f.write("# dimensions = %s\n" % spikelist.dimensions)
-
-
+
+
+
-        f.write("# dt = %g\n" % spikelist.dt)
-        f.close()
@@ -161 +153 @@
-    
-    def parse_header(self):
-
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-
-    def write_header(self, analogsignal, filename):
-        f = open(filename,"w")
-        f.write("# dimensions = %s\n" % analogsignal.dimensions)
-
-
+
+
+
-        f.write("# dt = %g\n" % analogsignal.dt)
-        f.close()

branches/cleanup/src/signals.py

@@ -459 +459 @@
-        result[idx] = -(vec_2[idx]/vec_1[idx] -1)
-        return numpy.sum(numpy.abs(result))
+    
+    
+    def record(self, filename = 'SpikeTrain.wav', fs=44100):
+        """ 
+        Fancy tool, not really useful but still...
+        Record the 'sound' produced by a SpikeTrain. Need the scikits.audiolab
+        package
+        
+        Inputs:
+            filename - the name of the output file (should have .wav extension)
+            fs       - the sampling rate
+        
+        Examples:
+            >>> spktrain.record("my_sound.wav")
+        """
+        # from the spike list
+        simtime_seconds = (self.t_stop - self.t_start)/1000.
+        (trace,time) = numpy.histogram(self.spike_times*1000., fs*simtime_seconds)
+        # TODO convolve with proper spike...
+        spike = numpy.ones((fs/1000.,)) # one ms
+        trace = numpy.convolve(trace, spike, mode='same')#/2.0
+        trace /= numpy.abs(trace).max() * 1.1
+        try:
+            from scikits.audiolab import wavwrite
+        except ImportError:
+            print "You need the scikits.audiolab package to produce sounds !"
+        wavwrite(trace, filename, fs = fs, enc = 'pcm26')
-
-    ####################################################################
@@ -551 +578 @@
-class SpikeList(object):
-    """
-, label=''
+
-    
-    Return a SpikeList object which will be a list of SpikeTrain objects.
@@ -562 +589 @@
-        t_stop  - end of the SpikeList, in ms. If None, will be infered from the data
-        dims    - dimensions of the recorded population, if not 1D population
-        label   - optionnal name to identify the SpikeList
-    
-    dt, t_start and t_stop are shared for all SpikeTrains object within the SpikeList
@@ -704 +730 @@
-            self.spiketrains[id] = spktrain.time_slice(self.t_start, self.t_stop)
-            self.id_list.append(id)
+            self.N += 1
-
-    def get_time_parameters(self):
@@ -1122 +1149 @@
-        if len(self.dimensions) == 1:
-            return id
-dim
+self.dimension
-            x = numpy.floor(id/self.dimensions[0])
-            y = id % self.dimensions[1]
@@ -1136 +1163 @@
-            t_start         - if not defined, the one of the SpikeList is used
-            t_stop          - if not defined, the one of the SpikeList is used
-
-
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+
-
-        The 'dimensions' attribute of the SpikeList is used to turn ids into 2d positions. It should
@@ -1407 +1436 @@
-
-
-fps=10
+bounds=(0,5), fps=10, display = True, kwargs={}
-        """
-        Generate a movie of the activity between t_start and t_stop.
@@ -1413 +1442 @@
-        
-        Inputs:
-
+
+
-            t_start         - if not defined, the one of the SpikeList is used, in ms
-            t_stop          - if not defined, the one of the SpikeList is used, in ms
@@ -1421 +1451 @@
-                              (2, nb_cells) with the x (first line) and y (second line) coordinates of
-                              the cells
-
+
+
+
-                              of values (min, max), in spikes per frame.
-display         - if True, a new figure is created. Could also be a subplot. The averaged
-                  spike_histogram over the whole population is then plotted
+fps             - The number of frame per second in the final movie
+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
@@ -1438 +1470 @@
-        """
-        subplot = self.__getdisplay__(display)
-pk
-pk
+elf
+elf
-        if not subplot or not ENABLE_PLOTS:
-            print MATPLOTLIB_ERROR
-        else:
-
+
+
+
+
+
-            count     = 0
-manager   = get_current_fig_manager()
-t         = t_start
-pk.t_start or t_stop != spk
+idx       = 0
+manager   = pylab.get_current_fig_manager()
+elf.t_start or t_stop != self
-                spk   = spk.time_slice(t_start, t_stop)
-            else:
@@ -1453 +1489 @@
-            time, pos = spk.convert("times, ids")
-            # We sort the spikes to allow faster process later
-
-
-
+
+
+
+
-            if float_positions is None:
-                if self.dimensions is None:
-                    raise Exception("Dimensions of the population are not defined ! Set spikelist.dims")
-
-s = 
-count] < 
+_start
+ = numpy.
+idx] < t_star
-                    addr = spk.id2position(pos[idx])
-s[addr] = activity_maps[addr] +
-count
-s
-title("time = %d ms" %
+[addr] +=
+idx
+
+subplot.title("time = %d ms" %t_star
-                manager.canvas.draw()
-
+im.set_
-                fname = "_tmp_spikes_%05d.png" %count
-                print " Saving Frame", fname
-
+pylab.
-                files.append(fname)
-     += dt
+_start += time_bin
-                count += 1
-            print 'Making movie %s - this make take a while' %output
@@ -1482 +1519 @@
-            print "Clean up...."
-            for fname in files: os.remove(fname)
-
+
-
-    ####################################################################
@@ -1644 +1681 @@
-    def __getslice__(self, i, j):
-        """
-pike_times vector of the SpikeTrain
+ignal vector of the AnalogSignal
-        """
-        return self.signal[i:j]
@@ -1661 +1698 @@
-
-    def time_axis(self):
+        """
+        Return the time axis of the AnalogSignal
+        """
-        return numpy.arange(self.t_start, self.t_stop, self.dt)
-
@@ -1672 +1712 @@
-
-        """
-ignal[t_start/self.dt,
+elf.signal[t_start/self.dt:
-        return AnalogSignal(signal, self.dt, t_start, t_stop)
-        
@@ -1690 +1730 @@
-        t_stop  - end of the SpikeList, in ms. If None, will be infered from the data
-        dims    - dimensions of the recorded population, if not 1D population
-        label   - optionnal name to identify the SpikeList
-    
-    dt, t_start and t_stop are shared for all SpikeTrains object within the SpikeList
-    
-    Examples:
-        >>> sl = SpikeList(3, [(0, 0.1), (1, 0.1), (0, 0.2)])
-        >>> type( sl[0] )
-        >>> <type SpikeTrain>
-    
-    See also
-CurrentTraces, loadMembraneTrace, loadConductanceTraces
+_currentlist load_vmlist, load_conductancelist
-
-    """
@@ -1800 +1834 @@
-
-    def append(self, id, signal):
+        """
+        Add an AnalogSignal object to the AnalogSignalList
+        
+        Inputs:
+            id     - the id of the new cell
+            signal - the AnalogSignal object representing the new cell
+        
+        The AnalogSignal object is sliced according to the t_start and t_stop times
+        of the AnalogSignallist object
+        
+        See also
+            __setitem__
+        """
-        assert isinstance(signal, AnalogSignal), "An AnalogSignalList object can only contain AnalogSignal objects"
-        if id in self.id_list:
-
+ 
-        else:
-            self.analog_signals[id] = signal
@@ -1810 +1857 @@
-
-    def time_axis(self):
+        """
+        Return the time axis of the AnalogSignalList object
+        """
-        return numpy.arange(self.t_start,self.t_stop,self.dt)
-
-    def id_slice(self, id_list):
-
-
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-    def save(self, filename, method="text"):
-        """
@@ -1834 +1921 @@
-        
-    
-    def time_slice(self, t_start, t_stop):
-        pass
-    
-
-
-
-class VmList(AnalogSignalList):
-
-    def plot(self, id_list=None, v_thresh=None, display=True, kwargs={}):
+        """
+        Plot all cells in the AnalogSignalList defined by id_list
+        
+        Inputs:
+            id_list - can be a integer (and then N cells are randomly selected) or a 
+                      list of ids. If None, we use all the ids of the SpikeList
+            v_thresh- For graphical purpose, plot a spike when Vm > V_thresh. If None, 
+                      just plot the raw Vm
+            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:
+            >>> z = subplot(221)
+            >>> aslist.plot(5, v_thresh = -50, display=z, kwargs={'color':'r'})
+        """
-        subplot   = self.__getdisplay__(display)
-        id_list   = self._AnalogSignalList__get_id_list(id_list)
@@ -1864 +1962 @@
-
-    def plot(self, id_list=None, v_thresh=None, display=True, kwargs={}):
+        """
+        Plot all cells in the AnalogSignalList defined by id_list
+        
+        Inputs:
+            id_list - can be a integer (and then N cells are randomly selected) or a 
+                      list of ids. If None, we use all the ids of the SpikeList
+            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:
+            >>> z = subplot(221)
+            >>> aslist.plot(5, display=z, kwargs={'color':'r'})
+        """
-        subplot   = self.__getdisplay__(display)
-        id_list   = self._AnalogSignalList__get_id_list(id_list)
@@ -1881 +1993 @@
-
-    def plot(self, id_list=None, v_thresh=None, display=True, kwargs={}):
+        """
+        Plot all cells in the AnalogSignalList defined by id_list
+        
+        Inputs:
+            id_list - can be a integer (and then N cells are randomly selected) or a 
+                      list of ids. If None, we use all the ids of the SpikeList
+            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:
+            >>> z = subplot(221)
+            >>> aslist.plot(5, display=z, kwargs={'color':'r'})
+        """
-        subplot   = self.__getdisplay__(display)
-        id_list   = self._AnalogSignalList__get_id_list(id_list)