Merge pull request #174 from Neurosim-lab/development

PR from development to master - VERSION 0.6.2

CHANGES.md

@@ -1,3 +1,35 @@
+# Version 0.6.2
+
+- Added importing of cell ion parameters (eg. 'ena' or 'ek')
+
+- Added backupCfgFile (eg. ['cfg.py', 'backupcfg/']) to simConfig to copy cfg file after run
+
+- Added gatherOnlySimData to simConfig to gather only simulation data and not cells or pops
+
+- Added simLabel and saveFolder to simConfig (can be used instead of filename)
+
+- Added printRunTime to simConfig to print run time (in sec) during execution
+
+- Added printPopAvgRates to simConfig to print population avg firing rates after run 
+
+- Automatic saving of netpyne and netParams version to file
+
+- Moved creation of fih functions to set cell vinit from setupRecording() to preRun()
+
+- Can now load netParams and simConfig from file without setting in sim
+
+- Added sim.readCmdLineArgs to read simConfig and netParams filepaths from command line 
+
+- Can now access NEURON's h module via sim.h
+
+- Fixed bug so can load netParams and simConfig without initializing sim
+
+- Fixed bug that prevented mechanism properties with value 0.0 from being set
+
+- Fixed bug in code to distribute cells (converted numCells from float to int)
+
+- Fixe bug in plotTraces
+
 # Version 0.6.1
 
 - Added global boolean variable netpyne.__gui__ to enable/disable graphics (issue #150)

doc/source/reference.rst

@@ -186,6 +186,10 @@ Each item of the ``cellParams`` ordered dict consists of a key and a value. The
 	* **mechs**: Dictionary of density/distributed mechanisms.
 		The key contains the name of the mechanism (e.g. ``hh`` or ``pas``)
 		The value contains a dictionary with the properties of the mechanism (e.g. ``{'g': 0.003, 'e': -70}``).
+
+	* **ions**: Dictionary of ions.
+		The key contains the name of the ion (e.g. ``na`` or ``na``)
+		The value contains a dictionary with the properties of the ion (e.g. ``{'e': -70}``).
 
 	* **pointps**: Dictionary of point processes (excluding synaptic mechanisms). 
 		The key contains an arbitrary label (e.g. 'Izhi')
@@ -631,9 +635,16 @@ Related to the simulation and netpyne framework:
 
 * **duration** - Duration of the simulation, in ms (default: 1000)
 * **dt** - Internal integration timestep to use (default: 0.025)
+* **hParams** - Dictionary with parameters of h module (default: {'celsius': 6.3, 'clamp_resist': 0.001})
+* **cache_efficient** - Use CVode cache_efficient option to optimize load when running on many cores (default: False) 
 * **seeds** - Dictionary with random seeds for connectivity, input stimulation, and cell locations (default: {'conn': 1, 'stim': 1, 'loc': 1})
 * **createNEURONObj** - Create HOC objects when instantiating network (default: True)
 * **createPyStruct** - Create Python structure (simulator-independent) when instantiating network (default: True)
+* **printRunTime** - Print run time at interval (in sec) specified here (eg. 0.1) (default: False) 
+* **printPopAvgRates** - Print population avg firing rates after run (default: False)
+* **includeParamsLabel** - Include label of param rule that created that cell, conn or stim (default: True)
+* **timing** - Show and record timing of each process (default: True)
+* **saveTiming** - Save timing data to pickle file (default: False)
 * **verbose** - Show detailed messages (default: False)
 
 Related to recording:
@@ -646,6 +657,8 @@ Related to recording:
 Related to file saving:
 
 * **saveDataInclude** = Data structures to save to file (default: ['netParams', 'netCells', 'netPops', 'simConfig', 'simData'])
+* **simLabel** = Name of simulation (used as filename if none provided) (default: '')
+* **saveFolder** = Path where to save output data (default: '')
 * **filename** - Name of file to save model output (default: 'model_output')
 * **timestampFilename**  - Add timestamp to filename to avoid overwriting (default: False)
 * **savePickle** - Save data to pickle file (default: False)
@@ -654,6 +667,7 @@ Related to file saving:
 * **saveTxt** - Save data to txt file (default: False)
 * **saveDpk** - Save data to .dpk pickled file (default: False)
 * **saveHDF5** - Save data to save to HDF5 file (default: False)
+* **backupCfgFile** - Copy cfg file to folder, eg. ['cfg.py', 'backupcfg/'] (default: [])
 
 
 .. _sim_config_analysis:
@@ -672,7 +686,6 @@ Related to plotting and analysis:
 
 	Availble analysis functions include ``plotRaster``, ``plotSpikeHist``, ``plotTraces``, ``plotConn`` and ``plot2Dnet``. A full description of each function and its arguments is available here: :ref:`analysis_functions`.
 
-
 .. _package_functions:
 
 Package functions

examples/HHTut/HHTut.py

@@ -82,7 +82,6 @@
 simConfig.saveFileStep = 1000 # step size in ms to save data to disk
 simConfig.savePickle = False # Whether or not to write spikes etc. to a .mat file
 
-
 # Analysis and plotting 
 simConfig.analysis['plotRaster'] = True  # Plot raster
 simConfig.analysis['plotTraces'] = {'include': [2]}  # Plot raster

examples/RL_arm/params.py

@@ -312,7 +312,7 @@
 simConfig.saveFileStep = 1000 # step size in ms to save data to disk
 simConfig.savePickle = False # Whether or not to write spikes etc. to a .mat file
 simConfig.saveJson = False # Whether or not to write spikes etc. to a .mat file
-simConfig.saveMat = False # Whether or not to write spikes etc. to a .mat file
+simConfig.saveMat = True # Whether or not to write spikes etc. to a .mat file
 simConfig.saveTxt = False # save spikes and conn to txt file
 simConfig.saveDpk = False # save to a .dpk pickled file
 

netpyne/__init__.py

@@ -1,3 +1,3 @@
 
-__version__ = '0.6.1'
+__version__ = '0.6.2'
 __gui__ = True  # global option to enable/disable graphics

netpyne/analysis.py

@@ -534,7 +534,7 @@ def plotTraces (include = None, timeRange = None, overlay = False, oneFigPer = '
     # Plot one fig per trace for given cell list
     def plotFigPerTrace(subGids):
         for itrace, trace in enumerate(tracesList):
-            figs.append(figure()) # Open a new figure
+            figs['_trace_'+str(trace)] = figure() # Open a new figure
             fontsiz = 12
             for igid, gid in enumerate(subGids):
                 if 'cell_'+str(gid) in sim.allSimData[trace]:
@@ -698,7 +698,7 @@ def plotConn (include = ['all'], feature = 'strength', orderBy = 'gid', figSize
 
     print('Plotting connectivity matrix...')
 
-    cells, cellGids, netStimPops = getCellsInclude(include)    
+    cells, cellGids, netStimPops = getCellsInclude(include) 
 
     # Create plot
     fig = figure(figsize=figSize)

netpyne/cell.py

@@ -184,7 +184,7 @@ def createNEURONObj (self, prop):
                         for iseg,seg in enumerate(sec['hSec']):  # set mech params for each segment
                             if type(mechParamValue) in [list]: 
                                 mechParamValueFinal = mechParamValue[iseg]
-                            if mechParamValueFinal:  # avoid setting None values
+                            if mechParamValueFinal is not None:  # avoid setting None values
                                 seg.__getattribute__(mechName).__setattr__(mechParamName,mechParamValueFinal)
 
             # add ions
@@ -367,16 +367,16 @@ def addSynMech (self, synLabel, secLabel, loc):
                     for synParamName,synParamValue in synMechParams.iteritems():  # add params of the synaptic mechanism
                         if synParamName not in ['label', 'mod', 'selfNetCon', 'loc']:
                             setattr(synMech['hSyn'], synParamName, synParamValue)
-                        elif synParamName == 'selfNetCon':  # create self netcon required for some synapses (eg. homeostatic)
+                        elif synParamName == 'selfNetcon':  # create self netcon required for some synapses (eg. homeostatic)
                             secLabelNetCon = synParamValue.get('sec', 'soma')
                             locNetCon = synParamValue.get('loc', 0.5)
                             secNetCon = self.secs.get(secLabelNetCon, None)
-                            synMech['hNetCon'] = h.NetCon(secNetCon['hSec'](locNetCon)._ref_v, synMech['hSyn'], sec=secNetCon['hSec'])
+                            synMech['hNetcon'] = h.NetCon(secNetCon['hSec'](locNetCon)._ref_v, synMech['hSyn'], sec=secNetCon['hSec'])
                             for paramName,paramValue in synParamValue.iteritems():
                                 if paramName == 'weight':
-                                    synMech['hNetCon'].weight[0] = paramValue
+                                    synMech['hNetcon'].weight[0] = paramValue
                                 elif paramName not in ['sec', 'loc']:
-                                    setattr(synMech['hNetCon'], paramName, paramValue)
+                                    setattr(synMech['hNetcon'], paramName, paramValue)
             return synMech
 
 

netpyne/network.py

@@ -483,7 +483,7 @@ def _connStrToFunc (self, preCellsTags, postCellsTags, connParam):
     ###############################################################################
     def fullConn (self, preCellsTags, postCellsTags, connParam):
         ''' Generates connections between all pre and post-syn cells '''
-        if sim.cfg.verbose: print 'Generating set of all-to-all connections...'
+        if sim.cfg.verbose: print 'Generating set of all-to-all connections (rule: %s) ...' % (connParam['label'])
 
         # get list of params that have a lambda function
         paramsStrFunc = [param for param in [p+'Func' for p in self.connStringFuncParams] if param in connParam] 
@@ -509,7 +509,7 @@ def fullConn (self, preCellsTags, postCellsTags, connParam):
     ###############################################################################
     def probConn (self, preCellsTags, postCellsTags, connParam):
         ''' Generates connections between all pre and post-syn cells based on probability values'''
-        if sim.cfg.verbose: print 'Generating set of probabilistic connections...'
+        if sim.cfg.verbose: print 'Generating set of probabilistic connections (rule: %s) ...' % (connParam['label'])
 
         seed(sim.id32('%d'%(sim.cfg.seeds['conn']+preCellsTags.keys()[-1]+postCellsTags.keys()[-1])))  
         allRands = {(preGid,postGid): random() for preGid in preCellsTags for postGid in postCellsTags}  # Create an array of random numbers for checking each connection
@@ -539,7 +539,7 @@ def probConn (self, preCellsTags, postCellsTags, connParam):
     ###############################################################################
     def convConn (self, preCellsTags, postCellsTags, connParam):
         ''' Generates connections between all pre and post-syn cells based on probability values'''
-        if sim.cfg.verbose: print 'Generating set of convergent connections...'
+        if sim.cfg.verbose: print 'Generating set of convergent connections (rule: %s) ...' % (connParam['label'])
 
         # get list of params that have a lambda function
         paramsStrFunc = [param for param in [p+'Func' for p in self.connStringFuncParams] if param in connParam] 
@@ -568,7 +568,7 @@ def convConn (self, preCellsTags, postCellsTags, connParam):
     ###############################################################################
     def divConn (self, preCellsTags, postCellsTags, connParam):
         ''' Generates connections between all pre and post-syn cells based on probability values'''
-        if sim.cfg.verbose: print 'Generating set of divergent connections...'
+        if sim.cfg.verbose: print 'Generating set of divergent connections (rule: %s) ...' % (connParam['label'])
 
         # get list of params that have a lambda function
         paramsStrFunc = [param for param in [p+'Func' for p in self.connStringFuncParams] if param in connParam] 
@@ -596,7 +596,7 @@ def divConn (self, preCellsTags, postCellsTags, connParam):
     ###############################################################################
     def fromListConn (self, preCellsTags, postCellsTags, connParam):
         ''' Generates connections between all pre and post-syn cells based list of relative cell ids'''
-        if sim.cfg.verbose: print 'Generating set of connections from list...'
+        if sim.cfg.verbose: print 'Generating set of connections from list (rule: %s) ...' % (connParam['label'])
 
         # list of params that can have a lambda function
         paramsStrFunc = [param for param in [p+'Func' for p in self.connStringFuncParams] if param in connParam] 

netpyne/pop.py

@@ -66,7 +66,7 @@ def createCellsFixedNum (self):
                 maxv = self.tags[coord+'normRange'][1] 
                 randLocs[:,icoord] = randLocs[:,icoord] * (maxv-minv) + minv
 
-        for i in xrange(int(sim.rank), sim.net.params.scale * self.tags['numCells'], sim.nhosts):
+        for i in xrange(int(sim.rank), int(sim.net.params.scale * self.tags['numCells']), sim.nhosts):
             gid = sim.net.lastGid+i
             self.cellGids.append(gid)  # add gid list of cells belonging to this population - not needed?
             cellTags = {k: v for (k, v) in self.tags.iteritems() if k in sim.net.params.popTagsCopiedToCells}  # copy all pop tags to cell tags, except those that are pop-specific

netpyne/sim.py

@@ -15,4 +15,5 @@
 from cell import Cell, PointNeuron
 from pop import Pop 
 import utils
+from neuron import h