Changeset 1022 for trunk

Timestamp:

12/02/11 01:26:26 (6 months ago)

Author:

pierre

Message:

Work with Dan and Andreas to fix last bugs in Brian and Nemo. For those that may use those backend, please report bugs, even if everything seems to look like normal. Nemo recording part should have been speed up

Location:

trunk/src

Files:

• brian/simulator.py (modified) (1 diff)
• nemo/__init__.py (modified) (4 diffs)
• nemo/recording.py (modified) (4 diffs)

trunk/src/brian/simulator.py

@@ -319 +319 @@
             dA_post/dt = -A_post/taum : 1''', taup=taup, taum=taum, wmax=wmax, mu_m=mu_m, mu_p=mu_p)
         pre   = 'A_pre += Ap'
-        pre  += '\nw += A_post*pow(w/wmax, mu_m)'
-        
-        post  = 'A_post += Am'        
-        post += '\nw += A_pre*pow(1-w/wmax, mu_p)'
+        pre  += '\nw += A_post*(w/wmax)**mu_m'
+        
+        post  = 'A_post += Am'       
+        post += '\nw += A_pre*(1-w/wmax)**mu_p'
         brian.STDP.__init__(self, C, eqs=eqs, pre=pre, post=post, wmin=wmin, wmax=wmax, delay_pre=None, delay_post=None, clock=None)
 

trunk/src/nemo/__init__.py

@@ -153 +153 @@
                         params['v_thresh'],
                         params['i_offset'],                        
-                        init['v'], 0., 0., -1.)
+                        init['v'], 0., 0., 1000.)
         else:            
             init = celltype.default_initial_values
@@ -228 +228 @@
         if self.synapse_model is "stdp_synapse":
             self._is_plastic = True
-        self._connections = None
+        self._connections = []
         
         method.connect(self)
@@ -249 +249 @@
 
     @property
-    def connections(self):
-        if self._connections is None:
-            self._connections = []
-            for source in numpy.unique(self._sources):
-                self._connections += list(simulator.state.sim.get_synapses_from(int(source)))
+    def connections(self):        
         return self._connections
 
@@ -288 +284 @@
         synapses = simulator.state.net.add_synapse(source, targets, delays, weights, self._is_plastic)
         self._sources.append(source)
+        self._connections += synapses
 
     def get(self, parameter_name, format, gather=True):

trunk/src/nemo/recording.py

@@ -22 +22 @@
         recording.Recorder.__init__(self, variable, population, file)
         self._simulator.recorder_list.append(self)
-        self.data  = {}    
-        self.times = []
+        if self.variable is "spikes":
+            self.data  = numpy.empty([0, 2])
+        elif self.variable is "v":
+            self.data  = numpy.empty([0, 3])
+        else:
+            raise Exception("Nemo can record only v and spikes for now !")    
 
     def write(self, file=None, gather=False, compatible_output=True, filter=None):
@@ -32 +36 @@
         """Add the cells in `ids` to the set of recorded cells."""
         self.recorded = self.recorded.union(ids)
-        for id in self.recorded:
-            self.data[id] = []
         
     def _reset(self):
@@ -39 +41 @@
 
     def _add_spike(self, fired, time):
-         idx   = list(self.recorded)
-         if len(fired > 0):
-             left  = numpy.searchsorted(fired, idx, 'left')
-             right = numpy.searchsorted(fired, idx, 'right')
-             for id, l, r in zip(idx, left, right):
-                if l != r:
-                    self.data[id] += [time]
+         ids       = self.recorded.intersection(fired)
+         self.data = numpy.vstack((self.data, numpy.array([list(ids), [time]*len(ids)]).T)) 
         ## To file or memory ? ###
 
     def _add_vm(self, time):
-        for id in list(self.recorded):
-            self.data[id] += [self._simulator.state.sim.get_membrane_potential(int(id))]
-        self.times += [time]
+        data      =  self._simulator.state.sim.get_membrane_potential(list(self.recorded))   
+        self.data = numpy.vstack((self.data, numpy.array([list(self.recorded), [time]*len(self.recorded), data]).T))
 
     def _get(self, gather=False, compatible_output=True, filter=None):
         """Return the recorded data as a Numpy array."""
         filtered_ids = self.filter_recorded(filter)
-        if self.variable == 'spikes':
-            data    = numpy.empty((0,2))
-            for id in filtered_ids:
-                times    = numpy.array(self.data[id])
-                new_data = numpy.array([numpy.ones(times.shape)*id, times]).T
-                data     = numpy.concatenate((data, new_data))
-        elif self.variable == 'v':
-            data   = numpy.empty((0,3))
-            N      = len(self.times)
-            for id in filtered_ids:
-                vm       = self.data[id]
-                new_data = numpy.array([numpy.ones(N)*id, self.times, vm]).T
-                data = numpy.concatenate((data, new_data))                    
+        if len(self.data) > 0:
+            mask = reduce(numpy.add, (self.data[:,0]==id for id in filtered_ids))                            
+            data = self.data[mask]
         return data
 
@@ -77 +63 @@
         filtered_ids = numpy.array(cells)   
         for id in filtered_ids:
-            N[id] = len(self.data[id])
+            N[id] = 0
+        spikes = self._get(gather=False, compatible_output=False, filter=filter)
+        ids   = numpy.sort(spikes[:,0].astype(int))
+        idx   = numpy.unique(ids)
+        left  = numpy.searchsorted(ids, idx, 'left')
+        right = numpy.searchsorted(ids, idx, 'right')
+        for id, l, r in zip(idx, left, right):
+            N[id] = r-l
         return N