Changeset 186

Timestamp:

01/28/08 17:45:43 (10 months ago)

Author:

apdavison

Message:

Merged changes from trunk r183 for common.py, nest2/__init.py__, nest2/cells.py and nest2/connectors.py and test directory. Merging largely done by hand since svn merge can't handle all the moving around/splitting of files (or if it can, I don't know how to do it). Merging of nest1, neuron and pcsim remains to be done.

Files:

• branches/multifile (modified) (1 prop)
• branches/multifile/src/common.py (modified) (16 diffs)
• branches/multifile/src/nest2/__init__.py (modified) (13 diffs)
• branches/multifile/src/nest2/cells.py (modified) (6 diffs)
• branches/multifile/src/nest2/connectors.py (modified) (6 diffs)
• branches/multifile/test (modified) (1 prop)
• branches/multifile/test/nest2tests.py (modified) (9 diffs)
• branches/multifile/test/pcsimtests_lowlevel.py (modified) (1 diff)
• branches/multifile/test/simple_STDP.py (modified) (1 diff)

branches/multifile/src/common.py

@@ -11 +11 @@
-import numpy
-from math import *
-
+
-
-class InvalidParameterValueError(Exception): pass
@@ -19 +19 @@
-
-dt = 0.1
+_min_delay = 0.1
-
-# ==============================================================================
@@ -189 +190 @@
-    
-    def checkParameters(self, supplied_parameters, with_defaults=False):
-
+
+
+
+
+
+
+
+
+
+
-        default_parameters = self.__class__.default_parameters
-        if with_defaults:
@@ -237 +247 @@
-        return translated_parameters
-
+    def update_parameters(self,parameters):
+        """
+        update self.parameters with those in parameters 
+        """
+        self.parameters.update(self.translate1(parameters, with_defaults=False))
+        
+
-    def __init__(self,parameters):
-        self.parameters = self.checkParameters(parameters, with_defaults=True)
@@ -312 +329 @@
-        'i_offset'   : 0.0,     # Offset current in nA
-        'v_init'     : -65.0,   # Membrane potential in mV at t = 0
+    }
+
+class IF_cond_exp_sfa_rr(StandardCellType):
+    """Linear leaky integrate and fire model with fixed threshold,
+    decaying-exponential post-synaptic conductance, conductance based spike-frequency adaptation,
+    and a conductance-based relative refractory mechanism.
+
+    See: Muller et al (2007) Spike-frequency adapting neural ensembles: Beyond mean-adaptation
+    and renewal theories. Neural Computation 19: 2958-3010.
+    """
+    
+    default_parameters = {
+        'v_rest'     : -65.0,   # Resting membrane potential in mV. 
+        'cm'         : 1.0,     # Capacity of the membrane in nF
+        'tau_m'      : 20.0,    # Membrane time constant in ms.
+        'tau_refrac' : 0.0,     # Duration of refractory period in ms.
+        'tau_syn_E'  : 5.0,     # Decay time of the excitatory synaptic conductance in ms.
+        'tau_syn_I'  : 5.0,     # Decay time of the inhibitory synaptic conductance in ms.
+        'e_rev_E'    : 0.0,     # Reversal potential for excitatory input in mV
+        'e_rev_I'    : -70.0,   # Reversal potential for inhibitory input in mV
+        'v_thresh'   : -50.0,   # Spike threshold in mV.
+        'v_reset'    : -65.0,   # Reset potential after a spike in mV.
+        'i_offset'   : 0.0,     # Offset current in nA
+        'v_init'     : -65.0,   # Membrane potential in mV at t = 0
+        'tau_sfa'    : 100.0,   # Time constant of spike-frequency adaptation in ms
+        'e_rev_sfa'  : -75.0,   # spike-frequency adaptation conductance reversal potential in mV
+        'q_sfa'      : 15.0,    # Quantal spike-frequency adaptation conductance increase in nS
+        'tau_rr'     : 2.0,     # Time constant of the relative refractory mechanism in ms
+        'e_rev_rr'   : -75.0,   # relative refractory mechanism conductance reversal potential in mV
+        'q_rr'       : 3000.0   # Quantal relative refractory conductance increase in nS
+        
+    }
+
+    
+class IF_facets_hardware1(StandardCellType):
+    """Leaky integrate and fire model with conductance-based synapses and fixed 
+    threshold as it is resembled by the FACETS Hardware Stage 1. For further 
+    details regarding the hardware model see the FACETS-internal Wiki:
+    https://facets.kip.uni-heidelberg.de/private/wiki/index.php/WP7_NNM
+    """
+    
+    default_parameters = {
+        'cm'                :    0.2,     # nF  
+        'g_leak'            :   20.0,     # nS
+        'tau_refrac'        :    1.0,     # ms
+        'tau_syn_E'         :   20.0,     # ms
+        'tau_syn_I'         :   20.0,     # ms
+        'v_reset'           :  -80.0,     # mV
+        'e_rev_I'           :  -75.0,     # mV,
+        'v_rest'            :  -70.0,     # mV
+        'v_thresh'          :  -57.0,     # mV
+        'e_rev_E'           :    0.0,     # mV        
-    }
-
@@ -370 +439 @@
-    }  
-
+class SpikeSourceInhGamma(StandardCellType):
+    """Spike source, generating realizations of an inhomogeneous gamma process, employing
+    the thinning method.
+
+    See: Muller et al (2007) Spike-frequency adapting neural ensembles: Beyond mean-adaptation
+    and renewal theories. Neural Computation 19: 2958-3010.
+    """
+
+    default_parameters = {
+        'a'     : numpy.array([1.0]),# time histogram of parameter a of a gamma distribution (dimensionaless)
+        'b'     : numpy.array([1.0]),# time histogram of parameter b of a gamma distribution (seconds)
+        'tbins' : numpy.array([0]),  # time bins of the time histogram of a,b in units of ms
+        'rmax' : 1.0,           # Rate (Hz) of the Poisson process to be thinned, usually set to max(1/b)
+        'start'    : 0.0,       # Start time (ms)
+        'duration' : 1e6        # Duration of spike sequence (ms)
+    }  
+
+
+
-class SpikeSourceArray(StandardCellType):
-    """Spike source generating spikes at the times given in the spike_times array."""
@@ -628 +716 @@
-        return _abstractMethod(self)
-    
+
+    def getSpikes(self):
+        """
+        returns a numpy array of the spikes of the population
+
+        Useful for small populations, for example for single neuron Monte-Carlo.
+
+        NOTE: getSpikes or printSpikes should be called only once per run,
+        because they mangle simulator recorder files.
+        """
+        
+        return _abstractMethod(self)
+
-    def print_v(self,filename,gather=True, compatible_output=True):
-        """
@@ -901 +1002 @@
-
-class Connector(object):
-
-
-
-
+
+
+
+
+
+
+
-    
-    def connect(self,projection):
-        """Connect all neurons in ``projection``"""
-        _abstractMethod(self)
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-class AllToAllConnector(Connector):
-    """
@@ -916 +1052 @@
-    """
-    
-
+
+
-        assert isinstance(allow_self_connections, bool)
-        self.allow_self_connections = allow_self_connections
-
-
-
-
+
-class FixedNumberPostConnector(Connector):
-    """
-
-
-
-
+
+
+
+
+
+
-        assert isinstance(allow_self_connections, bool)
-        self.allow_self_connections = allow_self_connections
-
-
-
-
+
+
+
+
+
+
+
+
+
-
-class FixedNumberPreConnector(Connector):
@@ -941 +1082 @@
-    cells in the presynaptic population, randomly choosen.
-    """
-
+
+
-        assert isinstance(allow_self_connections, bool)
-        self.allow_self_connections = allow_self_connections
-
-
-
+
+
+
+
+
+
+
+
+
-
-class OneToOneConnector(Connector):
@@ -959 +1107 @@
-    """
-    
-
-
-
-
+
+
-    
-class FixedProbabilityConnector(Connector):
@@ -969 +1115 @@
-    """
-    
-
+
+
-        assert isinstance(allow_self_connections, bool)
-        self.allow_self_connections = allow_self_connections
-        self.weights = weights
-        self.delays = delays
-        self.p_connect = float(p_connect)
-        assert 0 <= self.p_connect
@@ -986 +1131 @@
-    axes='xyz' is the same as axes=None.
-    It may be that the pre and post populations use different units for position, e.g.
-
+Â
-    to the positions in the post-synaptic population. An offset can also be included.
-    """
@@ -993 +1138 @@
-            'xy': [0,1], 'yz': [1,2], 'xz': [0,2], 'xyz': None, None: None}
-    
-
+
+
+
+
-        assert isinstance(allow_self_connections, bool)
-        assert isinstance(d_expression, str)
@@ -1004 +1152 @@
-        self.d_expression = d_expression
-        self.allow_self_connections = allow_self_connections
-        self.weights = weights
-        self.delays = delays
-        self.mask = DistanceDependentProbabilityConnector.AXES[axes]
-        self.periodic_boundaries = periodic_boundaries
@@ -1012 +1158 @@
-        self.scale_factor = scale_factor
-        self.offset = offset
+        
+
-        
-# ==============================================================================

branches/multifile/src/nest2/__init__.py

@@ -4 +4 @@
-$Id$
-"""
-ision:5 
+
-
-import nest
@@ -351 +351 @@
-                        nest.ConnectWD([src],[tgt],[weight],[delay])
-                        connect_id += [Connection(src,tgt)]
-
+
+
-        raise common.ConnectionError
-    return connect_id
@@ -447 +448 @@
-        os.remove(nest_filename)
-    if gather and len(node_list) > 1:
-
+
+
+
-        if nest.Rank() == 0: # only on the master node (?)
-            for node in node_list:
-
-
+
+
+
+
+
+
-    if compatible_output:
-        if gather == False or nest.Rank() == 0: # if we gather, only do this on the master node
@@ -465 +472 @@
-            ## Writing header info (e.g., dimensions of the population)
-            if population is not None:
-
+
+
+
-                padding = population.cell.flatten()[0]
-            else:
@@ -504 +513 @@
-        recorder_dict.pop(user_filename)    
-
+def _get(population=None, variable=None):
+    global recorder_dict
+
+    if population is None:
+        recorder = recorder_dict[user_filename]
+    else:
+        assert variable in ['spikes', 'v', 'conductance']
+        recorder = population.recorders[variable]
+
+    #print "Printing to %s from recorder %s (compatible_output=%s)" % (user_filename, recorder, compatible_output)
+
+    nest.FlushDevice(recorder)
+    status = nest.GetStatus([0])[0]
+    local_num_threads = status['local_num_threads']
+    node_list = range(nest.GetStatus([0], "num_processes")[0])
+
+    # Combine data from different threads to the zeroeth thread
+    nest.sps(recorder[0])
+    nest.sr("%i GetAddress %i append" % (recorder[0], 0))
+    nest.sr("GetStatus /filename get")
+    base_filename = nest.spp() #nest.GetStatus(recorder, "filename")
+
+    if local_num_threads>1:
+        for nest_thread in range(1,local_num_threads):
+            nest.sps(recorder[0])
+            nest.sr("%i GetAddress %i append" % (recorder[0], nest_thread))
+            nest.sr("GetStatus /filename get")
+            nest_filename = nest.spp() #nest.GetStatus(recorder, "filename")
+            system_line = 'cat %s >> %s' % (nest_filename, base_filename)
+            os.system(system_line)
+            os.remove(nest_filename)
+
+    # now we have the merged_filename
+
+    if population is not None:
+        padding = population.cell.flatten()[0]
+    else:
+        padding = 0
+
+
+    data = _readArray(base_filename, sepchar=None)
+    data[:,0] = data[:,0] - padding
+    os.remove(base_filename)
+
+    return data
+
+
-def _readArray(filename, sepchar=None, skipchar='#'):
-    logging.debug(filename)
@@ -625 +681 @@
-    def ids(self):
-        return self.__iter__()
-
+
-    def locate(self, id):
-        """Given an element id in a Population, return the coordinates.
@@ -656 +712 @@
-        return coords
-    
+    def index(self, n):
+        """Return the nth cell in the population."""
+        if hasattr(n, '__len__'):
+            n = numpy.array(n)
+        return self.cell[n]
+    
-    def set(self,param,val=None):
-        """
@@ -676 +738 @@
-        if isinstance(self.celltype, common.StandardCellType):
-            paramDict = self.celltype.translate1(paramDict)
-
-
+
-
-    def tset(self,parametername,valueArray):
@@ -702 +763 @@
-                        val = list(val) # tuples, arrays are all converted to lists, since this is what SpikeSourceArray expects. This is not very robust though - we might want to add things that do accept arrays.
-                    else:
-
-
+
+
+
+
-                    raise common.InvalidParameterValueError, "Error from SLI"
-        else:
@@ -720 +783 @@
-        else:
-            rarr = rand_distr.next(n=self.size)
-numpy.reshape(self.cell,self.cell.size)
+self.cell_local
-            assert len(rarr) == len(cells)
-            for cell,val in zip(cells,rarr):
-                try:
-                    nest.SetStatus([cell],{parametername: val})
-
+
+
-                    raise common.InvalidParameterValueError
-            
@@ -833 +897 @@
-        _print(filename, gather=gather, compatible_output=compatible_output,
-               population=self, variable="spikes")
-
+
+
+
+
+
+
+
+
+
+
+
+
-    def meanSpikeCount(self, gather=True):
-        """
@@ -1006 +1081 @@
-    def _fixedNumberPre(self,parameters):
-        """Each presynaptic cell makes a fixed number of connections."""
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
-    
-    def _fixedNumberPost(self,parameters):
-        """Each postsynaptic cell receives a fixed number of connections."""
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
-    
-    def _fromFile(self,parameters):
@@ -1261 +1266 @@
-        f = open(filename,'w',10000)
-        # Note unit change from pA to nA or nS to uS, depending on synapse type
-
-
+
+
+
+
+
+
+
+
+
+
-        fmt = "%s%s\t%s%s\t%s\t%s\n" % (self.pre.label,"%s",self.post.label,"%s","%g","%g")
-        for i in xrange(len(self)):

branches/multifile/src/nest2/cells.py

@@ -27 +27 @@
-        self.parameters = self.translate1(self.parameters)
-
+
-class IF_curr_exp(common.IF_curr_exp):
-    """Leaky integrate and fire model with fixed threshold and
@@ -49 +50 @@
-        self.parameters = self.translate1(self.parameters)
-
+
-class IF_cond_alpha(common.IF_cond_alpha):
-    """Leaky integrate and fire model with fixed threshold and alpha-function-
@@ -97 +99 @@
-                                                       # values for not-specified parameters.
-        self.parameters = self.translate1(self.parameters)
+        
+
+class IF_cond_exp_sfa_rr(common.IF_cond_exp_sfa_rr):
+    """Linear leaky integrate and fire model with fixed threshold,
+    decaying-exponential post-synaptic conductance, conductance based spike-frequency adaptation,
+    and a conductance-based relative refractory mechanism.
+
+    See: Muller et al (2007) Spike-frequency adapting neural ensembles: Beyond mean-adaptation
+    and renewal theories. Neural Computation 19: 2958-3010.
+    """
+    translations = common.build_translations(
+        ('v_rest',     'E_L')    ,
+        ('v_reset',    'V_reset'),
+        ('cm',         'C_m',        1000.0), # C_m is in pF, cm in nF
+        ('tau_m',      'g_L',        "cm/tau_m*1000.0", "C_m/g_L"),
+        ('tau_refrac', 't_ref',      "max(dt, tau_refrac)", "t_ref"),
+        ('tau_syn_E',  'tau_syn_ex'),
+        ('tau_syn_I',  'tau_syn_in'),
+        ('v_thresh',   'V_th'),
+        ('i_offset',   'I_e',        1000.0), # I_e is in pA, i_offset in nA
+        ('e_rev_E',    'E_ex'),
+        ('e_rev_I',    'E_in'),
+        ('v_init',     'V_m'),
+        ('tau_sfa',    'tau_sfa'),
+        ('e_rev_sfa',  'E_sfa'),
+        ('q_sfa',      'q_sfa'),
+        ('tau_rr',     'tau_rr'),
+        ('e_rev_rr',   'E_rr'),
+        ('q_rr',       'q_rr')
+    )
+    nest_name = "iaf_cond_exp_sfa_rr"
+    def __init__(self,parameters):
+        common.IF_cond_exp_sfa_rr.__init__(self,parameters) # checks supplied parameters and adds default
+                                                       # values for not-specified parameters.
+        self.parameters = self.translate1(self.parameters)
+
+
+class IF_facets_hardware1(common.IF_facets_hardware1):
+    """Leaky integrate and fire model with conductance-based synapses and fixed 
+    threshold as it is resembled by the FACETS Hardware Stage 1. For further 
+    details regarding the hardware model see the FACETS-internal Wiki:
+    https://facets.kip.uni-heidelberg.de/private/wiki/index.php/WP7_NNM
+    """
+    # in 'iaf_cond_exp_sfa_rr', the dimension of C_m is pF, 
+    # while in the pyNN context, cm is given in nF
+    translations = {
+        'v_reset'   : ('V_reset',        "parameters['v_reset']"),
+        'v_rest'    : ('E_L',            "parameters['v_rest']"),
+        'v_thresh'  : ('V_th',           "parameters['v_thresh']"),
+        'e_rev_E'   : ('E_ex',           "parameters['e_rev_E']"),
+        'e_rev_I'   : ('E_in',           "parameters['e_rev_I']"),
+        'cm'        : ('C_m',            "parameters['cm']*1000.0"), 
+        'tau_refrac': ('t_ref',          "max(dt,parameters['tau_refrac'])"),
+        'tau_syn_E' : ('tau_syn_ex',     "parameters['tau_syn_E']"),
+        'tau_syn_I' : ('tau_syn_in',     "parameters['tau_syn_I']"),                              
+        'g_leak'    : ('g_L',            "parameters['g_leak']")    
+    }
+    nest_name = "iaf_cond_exp_sfa_rr"
+
+    def __init__(self, parameters):
+        common.IF_facets_hardware1.__init__(self,parameters)
+        self.parameters = self.translate(self.parameters)
+        self.parameters['q_rr']     = 0.0
+        self.parameters['q_sfa']    = 0.0
-        
-
@@ -124 +190 @@
-                                                     # values for not-specified parameters.
-        self.parameters = self.translate(self.parameters)
+        
-        
-class AdaptiveExponentialIF_alpha(common.AdaptiveExponentialIF_alpha):
@@ -154 +221 @@
-        self.parameters = self.translate1(self.parameters)
-        
+        
-class SpikeSourcePoisson(common.SpikeSourcePoisson):
-    """Spike source, generating spikes according to a Poisson process."""
@@ -168 +236 @@
-        self.parameters = self.translate(self.parameters)
-        self.parameters['origin'] = 1.0
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-class SpikeSourceArray(common.SpikeSourceArray):
-    """Spike source generating spikes at the times given in the spike_times array."""

branches/multifile/src/nest2/connectors.py

@@ -7 +7 @@
-from pyNN.random import RandomDistribution, NativeRNG
-from math import *
+
+def get_target_ports(pre, target_list):
+    # The connection dict returned by NEST contains a list of target ids,
+    # so it is possible to obtain the target port by finding the index of
+    # the target in this list. For now, we stick with saving the target port
+    # in Python (faster, but more memory needed), but PyNEST should soon have
+    # a function to do the lookup, at which point we will switch to using that.
+    conn_dict = nest.GetConnections([pre], 'static_synapse')[0]
+    if conn_dict:
+        first_port = len(conn_dict['targets'])
+    else:
+        first_port = 0
+    return range(first_port, first_port+len(target_list))
-
-class AllToAllConnector(common.AllToAllConnector, WDManager):    
@@ -33 +46 @@
-            projection._targets += target_list
-            projection._sources += [pre]*N
-
-
+
-            nest.DivergentConnectWD([pre], target_list, weights, delays)
-        return len(projection._targets)
@@ -47 +59 @@
-            projection._sources = projection.pre.cell.flatten()
-            projection._targets = projection.post.cell.flatten()
-            projection._targetPorts = projection.post.cell.flatten()
-            N = len(projection._sources)
+            projection._targetPorts = range(N)
-            if isinstance(weight, RandomDistribution):
-                weights = list(weight.next(N))
@@ -90 +102 @@
-            projection._targets += target_list
-            projection._sources += [pre]*N
-target_list
+get_target_ports(pre, target_list)
-            nest.DivergentConnectWD([pre], target_list, weights, delays)
-        return len(projection._sources)
@@ -144 +156 @@
-            projection._targets += target_list
-            projection._sources += [pre]*N 
-target_list
+get_target_ports(pre, target_list)
-            nest.DivergentConnectWD([pre], target_list, weights, delays)
-        return len(projection._sources)
@@ -152 +164 @@
-    
-    def connect(self, projection):
-
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-
-class FixedNumberPostConnector(common.FixedNumberPostConnector):
-    
-    def connect(self, projection):
-
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+

branches/multifile/test/nest2tests.py

@@ -10 +10 @@
-import numpy
-import os
+
+def get_weight(src, port):
+    conn_dict = nest.nest.GetConnection([src], 'static_synapse', port)
+    if isinstance(conn_dict, dict):
+        return conn_dict['weight']
+    else:
+        raise Exception("Either the source id (%s) or the port number (%s) or both is invalid." % (src, port))
+
+def get_delay(src, port):
+    conn_dict = nest.nest.GetConnection([src], 'static_synapse', port)
+    if isinstance(conn_dict, dict):
+        return conn_dict['delay']
+    else:
+        raise Exception("Either the source id (%s) or the port number (%s) or both is invalid." % (src, port))
-
-# ==============================================================================
@@ -399 +413 @@
-        nest.setup(max_delay=0.5)
-        nest.Population.nPop = 0
-