Changeset 54

Timestamp:

05/11/07 16:00:49 (2 years ago)

Author:

apdavison

Message:

Merged trunk changes r48:53 into pyNN-0.3 branch

Files:

• branches/0.3/common.py (modified) (3 diffs)
• branches/0.3/facetsml.py (modified) (8 diffs)
• branches/0.3/nest.py (modified) (16 diffs)
• branches/0.3/neuron.py (modified) (8 diffs)
• branches/0.3/oldneuron.py (modified) (6 diffs)
• branches/0.3/pcsim.py (modified) (15 diffs)
• branches/0.3/test/facetsmltest.py (copied) (copied from trunk/test/facetsmltest.py)
• branches/0.3/test/pyNNPcsimLowLevelTest.py (modified) (3 diffs)
• branches/0.3/test/pyNNPcsimPopulationTest.py (modified) (6 diffs)

branches/0.3/common.py

@@ -186 +186 @@
-# ==============================================================================
-
-
-
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-    dt = timestep
-    pass
@@ -365 +369 @@
-    def printSpikes(self,filename,gather=True, compatible_output=True):
-        """
-
-
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+
-        This allows easy plotting of a `raster' plot of spiketimes, with one
-        line for each cell.
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-        pass
-    
@@ -381 +390 @@
-        """
-        Write membrane potential traces to file.
+        If compatible_output is True, the format is "v cell_id",
+        where cell_id is the index of the cell counting along rows and down
+        columns (and the extension of that for 3-D).
+        This allows easy plotting of a `raster' plot of spiketimes, with one
+        line for each cell.
+        The timestep and number of data points per cell is written as a header,
+        indicated by a '#' at the beginning of the line.
+        
+        If compatible_output is False, the raw format produced by the simulator
+        is used. This may be faster, since it avoids any post-processing of the
+        voltage files.
-        """
-        pass

branches/0.3/facetsml.py

@@ -38 +38 @@
-    #if the <neuroml> markup is not yet created
-    if(neuromlNodes.length == 0):
-seems createElementNS doesn't create the xmlns attribut
+neuroml has no prefix, namespace http://morphml.org/neuroml/schema is the default on
-        neuromlNode = xmldoc.createElementNS('http://morphml.org/neuroml/schema','neuroml')
-        xmldoc.appendChild(neuromlNode)
@@ -44 +44 @@
-        neuromlNode = neuromlNodes[0]
-    parentElementNodes = neuromlNode.getElementsByTagNameNS(parentElementNS,parentElementName)
+    #if the <parentElementName> markup is not yet created
-    if(parentElementNodes.length == 0):
+        #if no prefix has been defined and the namespace of the new parent element is not the default
+        # namespace, a new namespace is associated to null prefix, which is not good 
-        if(prefix == ''):
-            parentElementNode = xmldoc.createElementNS(parentElementNS,parentElementName)
@@ -53 +56 @@
-        parentElementNode = parentElementNodes[0]
-    return parentElementNode
+
+def writeDocument(url):
+    """
+    write the xmldoc created to a file specified by the url
+    """
+    file = open(url,'w')
+    PrettyPrint(xmldoc, file)
+    file.close()
+    
-
-
@@ -306 +318 @@
-    </net:populations>
-    
-    
-    
-        """
-        
@@ -317 +327 @@
-    
-    
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+    
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+    
+    
+    
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+    
+    
+    
-            self.celltype = cellclass(cellparams)
-            self.cellparams = self.celltype.parameters
@@ -332 +342 @@
-            hoc_name = cellclass
-        #end of coming
-
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-        #raise "Not yet implemented."
-        
-        
-        Population.nPop += 1
-
+    
-    
-        
@@ -515 +524 @@
-        than within methodParameters, particularly since some methods also use
-        random numbers to give variability in the number of connections per cell.
+        
+        
+        
+        
+        example of NeuroML for projections :
+        <projections units="Physiological Units" xmlns="http://morphml.org/networkml/schema">
+           <projection name="NetworkConnection">
+               <source>CellGroupA</source>
+               <target>CellGroupB</target>
+               <synapse_props>
+                   <synapse_type>DoubExpSynA</synapse_type>
+                   <default_values internal_delay="5" weight="1" threshold="-20"/>
+               </synapse_props>
+               <connections>
+                   <connection id="0">
+                       <pre cell_id="0" segment_id = "0" fraction_along="0.5"/>
+                       <post cell_id="1" segment_id = "1"/>
+                   </connection>
+                   <connection id="1">
+                       <pre cell_id="2" segment_id = "0"/>
+                       <post cell_id="1" segment_id = "0"/>
+                   </connection>
+                   <connection id="1">
+                       <pre cell_id="3" segment_id = "0"/>
+                       <post cell_id="1" segment_id = "1"/>
+                       <properties internal_delay="10" weight="0.5"/>                    <!-- adjusted value -->
+                   </connection>
+               </connections>
+           </projection>
+           <projection name="2">
+               <source>CellGroupA</source>
+               <target>CellGroupB</target>
+               <synapse_props>
+                   <synapse_type>DoubExpSynA</synapse_type>
+                   <default_values/>
+               </synapse_props>
+               <connectivity_pattern>
+                   <all_to_all/>
+               </connectivity_pattern>
+           </projection>
+       </projections>
-        """
-        common.Projection.__init__(self,presynaptic_population,postsynaptic_population,method,methodParameters,source,target,label,rng)
@@ -520 +570 @@
-        self._targets = []
-        self._sources = []
-
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-        
-    # --- Connection methods ---------------------------------------------------

branches/0.3/nest.py

@@ -109 +109 @@
-            'v_thresh'  : ('Theta'       , "parameters['v_thresh']"),
-            'i_offset'  : ('I0'          , "parameters['i_offset']*1000.0"), # I0 is in pA, i_offset in nA
-       
+        
-            'e_rev_I'   : ('V_reversal_I', "parameters['e_rev_I']"),
-            'v_init'    : ('u'           , "parameters['v_init']"),
@@ -154 +154 @@
-# ==============================================================================
-
-
-
+
+
+
+
+
+
-    if min_delay > max_delay:
-        raise Exception("min_delay has to be less than or equal to max_delay.")
@@ -244 +248 @@
-    both be individual cells or lists of cells, in which case all possible
-    connections are made with probability p, using either the random number
-
+
+
-    global dt
-    if weight is None:
@@ -332 +337 @@
-    pynest.sr('%s close' %tempfilename) 
-    if (compatible_output):
-       
+        
-        # desired format :
-       
-       
+        
+        
-        result = open(filename,'w',100)
-        g = open(tempfilename,'r',100)
@@ -344 +349 @@
-            neuron = int(single_line[0][1:len(single_line[0])])
-            spike_time = dt*float(single_line[1])
-       
+        
-        result.close()
-    else:
@@ -364 +369 @@
-    if (compatible_output):
-        f = open(tempfilename.replace('/','_'),'r',100)
-       
+        
-        f.close()
-
-       
+        
-        # desired format :
-       
-       
+        
+        
-        for line in lines:
-            line = line.rstrip()
@@ -376 +381 @@
-            if (len(single_line) > 1) and (single_line[1] != '-'):
-               neuron = int(single_line[0])
-       
+        
-    else:
-        f = open(tempfilename.replace('/','_'),'r',100)
-       
+        
-        f.close()
-        for line in lines:
@@ -620 +625 @@
-                                            'withpath':True}) # record which neuron spiked
-        
-       
+        
-
-        if record_from:
-            if type(record_from) == types.ListType:
-               
-               
+                
+                
-            elif type(record_from) == types.IntType:
-                n_rec = record_from
@@ -634 +639 @@
-        pynest.resCons(self.spike_detector[0],n_rec)
-
-       
-       
+        
+        
-                pynest.connect(pynest.getAddress(neuron),self.spike_detector[0])
-        else:
-       
+        
-                pynest.connect(pynest.getAddress(neuron),self.spike_detector[0])
-
-       
+
+        
-        # This should be redone now that Eilif has implemented the pythondatum datum type
-        # pynest.sr('/tmpfile_%s (tmpfile_%s) (w) file def' % (self.label,self.label)) # old
@@ -658 +663 @@
-        """
-        global hl_v_files
-
-       
-
-       
+
+        
+
+        
-        if record_from:
-            if type(record_from) == types.ListType:
-               
+                
-                n_rec = len(record_from)
-            elif type(record_from) == types.IntType:
@@ -673 +678 @@
-            n_rec = self.size
-
-       
+        
-        filename    = '%s.v' % self.label
-        record_file = tempdir+'/'+filename
-       
-       
-       
-       
-               
+        
+        
+        
+        
+                
-        hl_v_files.append(filename)
-        pynest.record_v(tmp_list, record_file.replace('/','_'))
@@ -687 +692 @@
-    def printSpikes(self,filename,gather=True, compatible_output=True):
-        """
-
-
-
-
-
-
+
+
+
+
-        This allows easy plotting of a `raster' plot of spiketimes, with one
-        line for each cell.
-
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-        global hl_spike_files
-        tempfilename = '%s.spikes' % self.label
@@ -710 +714 @@
-            pynest.sr('%s close' % tempfilename)
-            hl_spike_files.remove(tempfilename)
-
-
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+
+
-            result = open(filename,'w',1)
-            g = open("%s/%s" %(tempdir, tempfilename),'r',1)
-
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-            padding = numpy.reshape(self.cell,self.cell.size)[0]
-            lines = g.readlines()
@@ -731 +730 @@
-                neuron = int(single_line[0][1:len(single_line[0])]) - padding
-                spike_time = dt*float(single_line[1])
-       
+        
-            result.close()
-        else:
-            shutil.move(tempdir+'/'+tempfilename,filename)
-
+
-
-    def meanSpikeCount(self,gather=True):
@@ -760 +759 @@
-        """
-        Write membrane potential traces to file.
-
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-        """
-        global hl_v_files
-
-       
+
+        
-        if hl_v_files.__contains__(tempfilename):
-            pynest.sr('%s close' % tempfilename.replace('/','_'))
-            hl_v_files.remove(tempfilename)
-
-       
+
+        
-        dt = pynest.getNESTStatus()['resolution']
-        n = int(pynest.getNESTStatus()['time']/dt)
-        result.write("# dt = %f\n# n = %d\n" % (dt,n))
-
-       
-       
-       
+        
+        
+        
-            f.close()
-
-
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+
-            padding = numpy.reshape(self.cell,self.cell.size)[0]
-
-       
+        
-            # desired format :
-       
-       
+        
+        
-            for line in lines:
-                line = line.rstrip()
@@ -809 +799 @@
-                if (len(single_line) > 1) and (single_line[1] != '-'):
-                    neuron = int(single_line[0]) - padding
-       
-       
+        
+        
-            f = open(tempfilename.replace('/','_'),'r',1)
-       
+        
-            f.close()
-            for line in lines:

branches/0.3/neuron.py

@@ -62 +62 @@
-    # creation of networks
-    def setHocName(self, name):
-   
+    
-
-    def getHocName(self):
-   
+    
-    
-
@@ -208 +208 @@
-        errorstr = '"raise HocError(\'caused by HocToPy.get(%s,return_type=\\"%s\\")\')"' % (name,return_type)
-        hoc_commands = ['success = sprint(cmd,"HocToPy.hocvar = %s",%s)' % (HocToPy.fmt_dict[return_type],name),
-               
+                
-        hoc_execute(hoc_commands)
-        return HocToPy.hocvar
@@ -343 +343 @@
-# ==============================================================================
-
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-    global dt, nhost, myid, _min_delay, logger
-    dt = timestep
@@ -486 +490 @@
-    both be individual cells or lists of cells, in which case all possible
-    connections are made with probability p, using either the random number
-
+
+
-    global ncid, gid, gidlist, _min_delay
-    if type(source) != types.ListType:
@@ -960 +965 @@
-            if gather:
-                hoc_commands += ['objref gatheredvec']
-       
+        
-            for id in self.record_from[print_what]:
-                addr = self.locate(id)
-                #hoc_commands += ['fmt = "%s\\t%s\\n"' % (num_format, "\\t".join([str(j) for j in addr]))]
-               
+                
-                if id in self.gidlist:
-                    hoc_commands += ['tmp = %s.object(%d).%s.printf(fileobj,fmt)' % (self.label,self.gidlist.index(id),print_what)]
@@ -976 +981 @@
-    def printSpikes(self,filename,gather=True, compatible_output=True):
-        """
-
-
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+
+
-        This allows easy plotting of a `raster' plot of spiketimes, with one
-
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-        If gather is True, the file will only be created on the master node,
-        otherwise, a file will be written on each node.
-
+        
-        hoc_comment("--- Population[%s].__printSpikes()__ ---" %self.label)
-       
-       
-       
+        
+        
+        
-        self.__print('spiketimes',filename,"%.2f",gather, header)
-
@@ -994 +1006 @@
-        """
-        Write membrane potential traces to file.
+        If compatible_output is True, the format is "v cell_id",
+        where cell_id is the index of the cell counting along rows and down
+        columns (and the extension of that for 3-D).
+        This allows easy plotting of a `raster' plot of spiketimes, with one
+        line for each cell.
+        The timestep and number of data points per cell is written as a header,
+        indicated by a '#' at the beginning of the line.
+        
+        If compatible_output is False, the raw format produced by the simulator
+        is used. This may be faster, since it avoids any post-processing of the
+        voltage files.
-        """
-        tstop = HocToPy.get('tstop','float')
@@ -999 +1022 @@
-        header = "%s# %d" %(header,self.dim[0])
-        for dimension in list(self.dim)[1:]:
-       
+        
-        hoc_comment("--- Population[%s].__print_v()__ ---" %self.label)
-        self.__print('vtrace',filename,"%.4g",gather,header)

branches/0.3/oldneuron.py

@@ -335 +335 @@
-# ==============================================================================
-
-
-
+
+
+
+
+
+
-    global logfile, dt, _min_delay
-    dt = timestep
@@ -355 +359 @@
-    return 0
-
-
+compatible_output=True
-    """Do any necessary cleaning up before exiting."""
-    global logfile, vfilelist, spikefilelist
@@ -428 +432 @@
-    both be individual cells or lists of cells, in which case all possible
-    connections are made with probability p, using either the random number
-
+
+
-    global hoc_netcons, _min_delay
-    if type(source) != types.ListType:
@@ -741 +746 @@
-        self.__record('_v',record_from,rng)
-        
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-        This allows easy plotting of a `raster' plot of spiketimes, with one
-
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-        hoc_commands = ['objref spikefile',
-                        'spikefile = new File()',
@@ -776 +792 @@
-        self._tcall('memb_init',rvals)
-        
-
+,compatible_output=True
-        """
-        Write membrane potential traces to file.
+        If compatible_output is True, the format is "v cell_id",
+        where cell_id is the index of the cell counting along rows and down
+        columns (and the extension of that for 3-D).
+        This allows easy plotting of a `raster' plot of spiketimes, with one
+        line for each cell.
+        The timestep and number of data points per cell is written as a header,
+        indicated by a '#' at the beginning of the line.
+        
+        If compatible_output is False, the raw format produced by the simulator
+        is used. This may be faster, since it avoids any post-processing of the
+        voltage files.
-        """
-        hoc_commands = ['objref vfile',
@@ -1160 +1187 @@
-    
-# ==============================================================================
-    

branches/0.3/pcsim.py

@@ -19 +19 @@
-import numpy
-from pypcsim im