Changeset 708

Timestamp:

02/12/10 16:02:09 (2 years ago)

Author:

apdavison

Message:

Various fixes from running doctests

Location:

trunk

Files:

• doc/dynamicsynapses.txt (modified) (1 diff)
• doc/fileformats.txt (modified) (1 diff)
• doc/highlevelapi.txt (modified) (4 diffs)
• doc/lowlevelapi.txt (modified) (2 diffs)
• doc/testdocs.py (modified) (1 diff)
• examples/VAbenchmarks.py (modified) (3 diffs)
• examples/tools/VAbenchmark_graphs.py (modified) (2 diffs)
• setup.py (modified) (1 diff)
• src/brian/electrodes.py (modified) (2 diffs)
• src/nest/simulator.py (modified) (3 diffs)
• src/neuroml.py (modified) (9 diffs)
• src/pcsim/electrodes.py (modified) (2 diffs)

trunk/doc/dynamicsynapses.txt

@@ -73 +73 @@
     >>> prj.getSynapseDynamics('tau_rec')[:5]
     [50.0, 50.0, 50.0, 50.0, 50.0]
+    >>> from pyNN.random import RandomDistribution
     >>> distr = RandomDistribution('normal', [0.02, 0.05])
     >>> prj2.randomizeSynapseDynamics('w_max', distr)
     >>> prj2.getSynapseDynamics('w_max')[:5]
-    aofuha
+    [-0.056605932509016577, 0.063197908706714212, 0.034940801886916589, 0.010755581262934901, 0.011700727992415299]
 
 There are a number of examples of networks using synaptic plasticity in the ``examples`` directory of the source distribution.

trunk/doc/fileformats.txt

@@ -23 +23 @@
     >>> p.printSpikes(spike_file)
     >>> spike_file.close()
-    >>> vm_file = HDF5ArrayFile("my_Vm_data.h5")
+    >>> vm_file = HDF5ArrayFile("my_Vm_data.h5", "w")
     >>> p.print_v(vm_file)
     >>> vm_file.close()

trunk/doc/highlevelapi.txt

@@ -75 +75 @@
     Traceback (most recent call last):
       File "<stdin>", line 1, in ?
-      File "/usr/lib/python/site-packages/pyNN/nest1.py", line 457, in __getitem__
-        id = self.cell[addr]
-    IndexError: index (999) out of range (0<=index<=10) in dimension 0
+      File "/usr/lib/python/site-packages/pyNN/common.py", line 794, in __getitem__
+        id = self.all_cells[addr]
+    IndexError: index (999) out of range (0<=index<10) in dimension 0
 
 as will giving the wrong number of dimensions in the address.
@@ -107 +107 @@
     Traceback (most recent call last):
       File "<stdin>", line 1, in <module>
-      File "/home/andrew/dev/pyNN/neuron/__init__.py", line 759, in index
+      File "/usr/lib/python/site-packages/pyNN/neuron/__init__.py", line 759, in index
         return self.fullgidlist[n]
     IndexError: index out of bounds
@@ -228 +228 @@
         File "<stdin>", line 1, in <module>
           sine_wave.inject_into(p2)
-        File "/home/andrew/dev/pyNN/neuron/electrodes.py", line 67, in inject_into
+        File "/usr/lib/python/site-packages/pyNN/neuron/electrodes.py", line 67, in inject_into
           raise TypeError("Can't inject current into a spike source.")
     TypeError: Can't inject current into a spike source.
@@ -359 +359 @@
       File "<stdin>", line 1, in <module>
         invalid_prj = Projection(p2, p3, OneToOneConnector())
-      File "/home/andrew/dev/pyNN/neuron/__init__.py", line 220, in __init__
+      File "/usr/lib/python/site-packages/pyNN/neuron/__init__.py", line 220, in __init__
         method.connect(self)
-      File "/home/andrew/dev/pyNN/connectors.py", line 281, in connect
+      File "/usr/lib/python/site-packages/pyNN/connectors.py", line 281, in connect
         raise common.InvalidDimensionsError("OneToOneConnector does not support
                    presynaptic and postsynaptic Populations of different sizes.")

trunk/doc/lowlevelapi.txt

@@ -61 +61 @@
 stored in the ``default_values`` of the standard cell class, e.g.::
 
-    >>> IF_curr_alpha.default_parameters #doctest" +NORMALIZE_WHITESPACE
+    >>> IF_curr_alpha.default_parameters #doctest: +NORMALIZE_WHITESPACE
     {'tau_refrac': 0.0, 'tau_m': 20.0, 'i_offset': 0.0, 'cm': 1.0, 'v_init': -65.0,
      'v_thresh': -50.0, 'tau_syn_E': 0.5, 'v_rest': -65.0, 'tau_syn_I': 0.5,
@@ -75 +75 @@
     Traceback (most recent call last):
       File "<stdin>", line 1, in ?
-      File "/usr/lib/python/site-packages/pyNN/nest1.py", line 228, in create
+      File "/usr/lib/python/site-packages/pyNN/common.py", line 655, in create
+        all_cells, mask_local, first_id, last_id = simulator.create_cells(cellclass, cellparams, n)
+      File "/home/andrew/dev/pyNN/neuron/simulator.py", line 287, in create_cells
         celltype = cellclass(cellparams)
-      File "/usr/lib/python/site-packages/pyNN/nest1.py", line 68, in __init__
-        common.IF_curr_alpha.__init__(self,parameters) # checks supplied parameters and adds default
-      File "/usr/lib/python/site-packages/pyNN/common.py", line 113, in __init__
-        self.parameters = self.checkParameters(parameters, with_defaults=True)
-      File "/usr/lib/python/site-packages/pyNN/common.py", line 99, in checkParameters
-        raise NonExistentParameterError(k)
-    NonExistentParameterError: foo
+      File "/usr/lib/python/site-packages/pyNN/neuron/cells.py", line 442, in __init__
+        cells.IF_curr_alpha.__init__(self, parameters) # checks supplied parameters and adds default
+      File "/usr/lib/python/site-packages/pyNN/common.py", line 460, in __init__
+        self.parameters = self.__class__.checkParameters(parameters, with_defaults=True)
+      File "/usr/lib/python/site-packages/pyNN/common.py", line 504, in checkParameters
+        raise NonExistentParameterError(k, cls)
+    NonExistentParameterError: foo (valid parameters for IF_curr_alpha are: cm, i_offset, tau_m, tau_refrac, tau_syn_E, tau_syn_I, v_init, v_reset, v_rest, v_thresh)
     >>> create(IF_curr_alpha, cellparams={'tau_m': 'bar'})
     Traceback (most recent call last):

trunk/doc/testdocs.py

@@ -10 +10 @@
 
 optionflags = doctest.IGNORE_EXCEPTION_DETAIL+doctest.NORMALIZE_WHITESPACE
-#optionflags = doctest.NORMALIZE_WHITESPACE
+optionflags = doctest.NORMALIZE_WHITESPACE
 
 class MyOutputChecker(doctest.OutputChecker):

trunk/examples/VAbenchmarks.py

@@ -144 +144 @@
     connections['ext2i'] = Projection(ext_stim, inh_cells, ext_conn, target='excitatory')
 
-for prj in connections.keys():
-    connections[prj].saveConnections('Results/VAbenchmark_%s_%s_%s_np%d.conn' % (benchmark, prj, simulator_name, np))
-
 # === Setup recording ==========================================================
 print "%s Setting up recording..." % node_id
@@ -154 +151 @@
 exc_cells.record_v(vrecord_list)
 
-buildCPUTime = timer.elapsedTime()
+buildCPUTime = timer.diff()
+
+# === Save connections to file =================================================
+
+for prj in connections.keys():
+    connections[prj].saveConnections('Results/VAbenchmark_%s_%s_%s_np%d.conn' % (benchmark, prj, simulator_name, np))
+saveCPUTime = timer.diff()
 
 # === Run simulation ===========================================================
 print "%d Running simulation..." % node_id
-timer.reset()
 
 run(tstop)
 
-simCPUTime = timer.elapsedTime()
-
-E_rate = exc_cells.meanSpikeCount()*1000./tstop
-I_rate = inh_cells.meanSpikeCount()*1000./tstop
+simCPUTime = timer.diff()
+
+E_count = exc_cells.meanSpikeCount()
+I_count = inh_cells.meanSpikeCount()
 
 # === Print results to file ====================================================
 
 print "%d Writing data to file..." % node_id
-timer.reset()
 
 if not(os.path.isdir('Results')):
@@ -178 +179 @@
 inh_cells.printSpikes("Results/VAbenchmark_%s_inh_%s_np%d.ras" % (benchmark, simulator_name, np))
 exc_cells.print_v("Results/VAbenchmark_%s_exc_%s_np%d.v" % (benchmark, simulator_name, np))
-writeCPUTime = timer.elapsedTime()
-
-tmp_string = "%d e→e  %d e→i  %d i→e  %d i→i" % (connections['e2e'].size(),
-                                                 connections['e2i'].size(),
-                                                 connections['i2e'].size(),
-                                                 connections['i2i'].size())
-
-def nprint(s):
-    """Small function to display information only on node 0."""
-    if (node_id == 0):
-        print s
-
-nprint("\n--- Vogels-Abbott Network Simulation ---")
-nprint("Nodes                  : %d" % np)
-nprint("Simulation type        : %s" % benchmark)
-nprint("Number of Neurons      : %d" % n)
-nprint("Number of Synapses     : %s" % tmp_string)
-nprint("Excitatory conductance : %g nS" % Gexc)
-nprint("Inhibitory conductance : %g nS" % Ginh)
-nprint("Excitatory rate        : %g Hz" % E_rate)
-nprint("Inhibitory rate        : %g Hz" % I_rate)
-nprint("Build time             : %g s" % buildCPUTime) 
-nprint("Simulation time        : %g s" % simCPUTime)
-nprint("Writing time           : %g s" % writeCPUTime)
+writeCPUTime = timer.diff()
+
+connections = "%d e→e  %d e→i  %d i→e  %d i→i" % (connections['e2e'].size(),
+                                                  connections['e2i'].size(),
+                                                  connections['i2e'].size(),
+                                                  connections['i2i'].size())
+
+if node_id == 0:
+    print "\n--- Vogels-Abbott Network Simulation ---"
+    print "Nodes                  : %d" % np
+    print "Simulation type        : %s" % benchmark
+    print "Number of Neurons      : %d" % n
+    print "Number of Synapses     : %s" % connections
+    print "Excitatory conductance : %g nS" % Gexc
+    print "Inhibitory conductance : %g nS" % Ginh
+    print "Excitatory rate        : %g Hz" % (E_count*1000.0/tstop,)
+    print "Inhibitory rate        : %g Hz" % (I_count*1000.0/tstop,)
+    print "Build time             : %g s" % buildCPUTime
+    print "Save connections time  : %g s" % saveCPUTime
+    print "Simulation time        : %g s" % simCPUTime
+    print "Writing time           : %g s" % writeCPUTime
 
 

trunk/examples/tools/VAbenchmark_graphs.py

@@ -4 +4 @@
 
 import pylab, sys
+import numpy
 from NeuroTools import signals, plotting
 from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
@@ -69 +70 @@
         
         # Plot membrane potential trace
-        allvdata = pylab.load("Results/VAbenchmark_%s_exc_%s_np%d.v" % (benchmark, simulator, num_nodes), comments='#')
+        allvdata = numpy.loadtxt("Results/VAbenchmark_%s_exc_%s_np%d.v" % (benchmark, simulator, num_nodes), comments='#')
         cell_ids = allvdata[:,1].astype(int)
         allvdata = allvdata[:,0]

trunk/setup.py

@@ -41 +41 @@
 setup(
     name = "PyNN",
-    version = "0.6pre",
+    version = "0.6.0pre",
     package_dir={'pyNN': 'src'},
     packages = ['pyNN','pyNN.nest', 'pyNN.pcsim', 'pyNN.neuron', 'pyNN.brian', 'pyNN.recording'],

trunk/src/brian/electrodes.py

@@ -6 +6 @@
     StepCurrentSource  -- a step-wise time-varying current.
 
-$Id:$
+$Id$
 """
 
@@ -33 +33 @@
     def inject_into(self, cell_list):
         """Inject this current source into some cells."""
+        for cell in cell_list:
+            if 'v' not in cell.cellclass.recordable:
+                raise TypeError("Can't inject current into a spike source.")
         self.cell_list.extend(cell_list)        
     

trunk/src/nest/simulator.py

@@ -271 +271 @@
     def __getitem__(self, i):
         """Return the `i`th connection on the local MPI node."""
-        if i < len(self):
-            return Connection(self, i)
-        else:
-            raise IndexError("%d > %d" % (i, len(self)-1))
+        if isinstance(i, int):
+            if i < len(self):
+                return Connection(self, i)
+            else:
+                raise IndexError("%d > %d" % (i, len(self)-1))
+        elif isinstance(i, slice):
+            if i.stop < len(self):
+                return [Connection(self, j) for j in range(i.start, i.stop, i.step or 1)]
+            else:
+                raise IndexError("%d > %d" % (i.stop, len(self)-1))
+            
     
     def __len__(self):
@@ -395 +402 @@
         
         if parameter_name not in ('weight', 'delay'):
-            if parameter_name in self.parent.synapse_dynamics.fast.translations:
-                parameter_name = self.parent.synapse_dynamics.fast.translations[parameter_name]["translated_name"] # this is a hack that works because there are no units conversions
+            translated_name = None
+            if self.parent.synapse_dynamics.fast and parameter_name in self.parent.synapse_dynamics.fast.translations:
+                translated_name = self.parent.synapse_dynamics.fast.translations[parameter_name]["translated_name"] # this is a hack that works because there are no units conversions
+            elif self.parent.synapse_dynamics.slow:
+                for component_name in "timing_dependence", "weight_dependence", "voltage_dependence":
+                    component = getattr(self.parent.synapse_dynamics.slow, component_name)
+                    if component and parameter_name in component.translations:
+                        translated_name = component.translations[parameter_name]["translated_name"]
+                        break
+            if translated_name:
+                parameter_name = translated_name
             else:
                 raise Exception("synapse type does not have an attribute '%s', or else this attribute is not accessible." % parameter_name)
@@ -468 +484 @@
             #translation = self.parent.synapse_dynamics.reverse_translate({name: value})
             #name, value = translation.items()[0]
-            name = self.parent.synapse_dynamics.fast.translations[name]["translated_name"] # a hack
+            translated_name = None
+            if self.parent.synapse_dynamics.fast:
+                if name in self.parent.synapse_dynamics.fast.translations:
+                    translated_name = self.parent.synapse_dynamics.fast.translations[name]["translated_name"] # a hack
+            if translated_name is None:
+                if self.parent.synapse_dynamics.slow:
+                    for component_name in "timing_dependence", "weight_dependence", "voltage_dependence":
+                        component = getattr(self.parent.synapse_dynamics.slow, component_name)
+                        if component and name in component.translations:
+                            translated_name = component.translations[name]["translated_name"]
+                            break
+            if translated_name:
+                name = translated_name
         
         i = 0

trunk/src/neuroml.py

@@ -7 +7 @@
 from pyNN import common, connectors, cells
 import math
-#import numpy, types, sys, shutil
+import numpy
 import sys
 sys.path.append('/usr/lib/python%s/site-packages/oldxml' % sys.version[:3]) # needed for Ubuntu
@@ -24 +24 @@
 neuroml_xsd="http://www.neuroml.org/NeuroMLValidator/NeuroMLFiles/Schemata/v"+neuroml_ver+"/Level3/NeuroML_Level3_v"+neuroml_ver+".xsd"
 
+strict = False
+
 # ==============================================================================
 #   Utility classes
 # ==============================================================================
 
-class ID(common.IDMixin):
+class ID(int, common.IDMixin):
     """
     Instead of storing ids as integers, we store them as ID objects,
@@ -38 +40 @@
     
     def __init__(self, n):
-        common.IDMixin.__init__(self, n)
+        common.IDMixin.__init__(self)
 
 # ==============================================================================
@@ -179 +181 @@
         return cell_node, channel_nodes, synapse_nodes
 
+
+class NotImplementedModel(object):
+    
+    def __init__(self):
+        if strict:
+            raise Exception('Cell type %s is not available in NeuroML' % self.__class__.__name__)
+    
+    def build_nodes(self):
+        cell_node = build_node(':not_implemented_cell', name=self.label)
+        doc_node = build_node('meta:notes', "PyNN %s cell type not implemented" % self.__class__.__name__)
+        return cell_node, [], []
+        
+
 # ==============================================================================
 #   Standard cells
 # ==============================================================================
 
-class IF_curr_exp(cells.IF_curr_exp):
+class IF_curr_exp(cells.IF_curr_exp, NotImplementedModel):
     """Leaky integrate and fire model with fixed threshold and
     decaying-exponential post-synaptic current. (Separate synaptic currents for
     excitatory and inhibitory synapses"""
     
+    n = 0
+    translations = common.build_translations(*[(name, name)
+                                               for name in cells.IF_curr_exp.default_parameters])
+    
     def __init__(self, parameters):
-        raise Exception('Cell type %s is not available in NeuroML' % self.__class__.__name__)
-
-class IF_curr_alpha(cells.IF_curr_alpha):
+        NotImplementedModel.__init__(self)
+        cells.IF_curr_exp.__init__(self, parameters)
+        self.label = '%s%d' % (self.__class__.__name__, self.__class__.n)
+        self.synapse_type = "doub_exp_syn"
+        self.__class__.n += 1
+
+class IF_curr_alpha(cells.IF_curr_alpha, NotImplementedModel):
     """Leaky integrate and fire model with fixed threshold and alpha-function-
     shaped post-synaptic current."""
     
+    n = 0
+    translations = common.build_translations(*[(name, name)
+                                               for name in cells.IF_curr_alpha.default_parameters])
+    
     def __init__(self, parameters):
-        raise Exception('Cell type %s is not available in NeuroML' % self.__class__.__name__)
+        NotImplementedModel.__init__(self)
+        cells.IF_curr_exp.__init__(self, parameters)
+        self.label = '%s%d' % (self.__class__.__name__, self.__class__.n)
+        self.synapse_type = "doub_exp_syn"
+        self.__class__.n += 1
 
 class IF_cond_exp(cells.IF_cond_exp, IF_base):
@@ -226 +257 @@
         self.__class__.n += 1
 
-class SpikeSourcePoisson(cells.SpikeSourcePoisson):
+class SpikeSourcePoisson(cells.SpikeSourcePoisson, NotImplementedModel):
     """Spike source, generating spikes according to a Poisson process."""
 
+    n = 0
+    translations = common.build_translations(*[(name, name)
+                                               for name in cells.SpikeSourcePoisson.default_parameters])
+    
     def __init__(self, parameters):
-        raise Exception('Cell type %s not yet implemented' % self.__class__.__name__)
+        NotImplementedModel.__init__(self)
         cells.SpikeSourcePoisson.__init__(self, parameters)
-        
-
-class SpikeSourceArray(cells.SpikeSourceArray):
+        self.label = '%s%d' % (self.__class__.__name__, self.__class__.n)
+        self.__class__.n += 1
+        
+
+class SpikeSourceArray(cells.SpikeSourceArray, NotImplementedModel):
     """Spike source generating spikes at the times given in the spike_times array."""
 
+    n = 0
+    translations = common.build_translations(*[(name, name)
+                                               for name in cells.SpikeSourcePoisson.default_parameters])
+
     def __init__(self, parameters):
-        raise Exception('Cell type %s not yet implemented' % self.__class__.__name__)
-        cells.SpikeSourceArray.__init__(self, parameters)
+        NotImplementedModel.__init__(self)
+        cells.SpikeSourceARRAY.__init__(self, parameters)
+        self.label = '%s%d' % (self.__class__.__name__, self.__class__.n)
+        self.__class__.n += 1
         
 
@@ -253 +296 @@
     simulator but not by others.
     """
-    global xmldoc, xmlfile, populations_node, projections_node, inputs_node, cells_node, channels_node, neuromlNode
+    global xmldoc, xmlfile, populations_node, projections_node, inputs_node, cells_node, channels_node, neuromlNode, strict
     xmlfile = extra_params['file']
     if isinstance(xmlfile, basestring):
         xmlfile = open(xmlfile, 'w')
+    if 'strict' in extra_params:
+        strict = extra_params['strict']
     dt = timestep
     xmldoc = xml.dom.minidom.Document()
@@ -296 +341 @@
 def num_processes():
     return 1
+common.num_processes = num_processes
+
+def rank():
+    return 0
+common.rank = rank
 
 
@@ -388 +438 @@
             channels_node.appendChild(synapse_node)
 
+        self.first_id = 0
+        self.last_id = self.size-1
+        self.all_cells = numpy.array([ID(id) for id in range(self.first_id, self.last_id+1)], dtype=ID).reshape(dims)
+        self._mask_local = numpy.ones_like(self.all_cells).astype(bool)
+        self.local_cells = self.all_cells[self._mask_local]
+
+    def _record(self, variable, record_from=None, rng=None, to_file=True):
+        """
+        Private method called by record() and record_v().
+        """
+        pass
+    
+    def meanSpikeCount(self):
+        return -1
+    
+    def printSpikes(self, file, gather=True, compatible_output=True):
+        pass
+    
+    def print_v(self, file, gather=True, compatible_output=True):
+        pass
 
 class AlltoAllConnector(connectors.AllToAllConnector):
@@ -531 +601 @@
         Projection.n += 1
 
-
-# ==============================================================================
+    def saveConnections(self, filename, gather=True, compatible_output=True):
+        pass
+    
+    def __len__(self):
+        return 0 # needs implementing properly
+
+# ==============================================================================

trunk/src/pcsim/electrodes.py

@@ -19 +19 @@
     def inject_into(self, cell_list):
         """Inject this current source into some cells."""
-        print "injecting current source into cells: %s" % str(cell_list)
         if simulator.state.num_processes == 1:
             delay = 0.0
@@ -25 +24 @@
             delay = simulator.state.min_delay # perhaps it would be better to replicate the current source on each node, to avoid this delay
         for cell in cell_list:
-            print cell, cell.local, cell.cellclass.recordable
             if cell.local and 'v' not in cell.cellclass.recordable:
                 raise TypeError("Can't inject current into a spike source.")
             c = simulator.net.connect(self.input_node, cell, pypcsim.StaticAnalogSynapse(delay=0.001*delay))
             self.connections.append(c)
-            print "connected current source to cell %s" % cell