def set_current_ampl(self,current_ampl):
"""Sets the amplitude of the injected current."""
err = ""
print "Current amplitude is ",current_ampl
from ucl.physiol.neuroconstruct.utils import NumberGenerator
sim_config_info = self.manager.project.simConfigInfo
sim_config = sim_config_info.getSimConfig(self.sim_config_name)
print("Sim Config name is %s" % self.sim_config_name)
inputs = sim_config.getInputs()
print("%s has %d inputs" % (self.sim_config_name,len(inputs)))
if len(inputs) < 1:
err = "This sim config has no inputs"
else:
one_set = False
for inp in range(len(inputs)):
input_ = inputs.get(inp)
stim = self.manager.project.elecInputInfo.getStim(input_)
if hasattr(stim,'setAmp'):
stim.setAmp(NumberGenerator(current_ampl))
stim.setDur(NumberGenerator(200.0)) # Change pulse length to 400 ms.
self.manager.project.elecInputInfo.updateStim(stim)
print("Stim amplitude set to %f" % current_ampl)
one_set = True
else:
err = "This stim has no attribute 'setAmp'"
if one_set:
err = ""
print err
return err
def runColumnSimulation(simConfig="TempSimConfig",
simDuration=100,
simDt=0.025,
neuroConstructSeed=1234,
simulatorSeed=1234,
simulators=["NEURON"],
simRefPrefix="Net_",
suggestedRemoteRunTime=120,
defaultSynapticDelay=0.05,
mpiConf=MpiSettings.LOCAL_SERIAL,
scaleCortex=0.1,
scaleThalamus=0,
gabaScaling=1,
l4ssAmpaScaling=1,
l5PyrGapScaling=1,
inNrtTcrNmdaScaling=1,
pyrSsNmdaScaling=1,
deepBiasCurrent=-1,
maxElecLenFRB=0.01,
maxElecLenRS=0.01,
maxElecLenIN=0.01,
maxElecLenSS=0.01,
somaNseg=-1,
varTimestepNeuron=False,
verbose=True,
runInBackground=False):
print "Running new column simulation..."
############################################
# Full column populations
numFRB = 50 # full model: 50
numRS = 1000 # full model: 1000
numSupBask = 90 # full model: 90
numSupAxAx = 90 # full model: 90
numSupLTS = 90 # full model: 90
numL4SpinStell = 240 # full model: 240
numL5TuftIB = 800 # full model: 800
numL5TuftRS = 200 # full model: 200
numDeepBask = 100 # full model: 100
numDeepAxAx = 100 # full model: 100
numDeepLTS = 100 # full model: 100
numL6NonTuftRS = 500 # full model: 500
numTCR = 100 # full model: 100
numnRT = 100 # full model: 100
#######################################
### Load neuroConstruct project
import datetime
start = datetime.datetime.now()
print "Loading project %s from at %s " % (projFile.getCanonicalPath(),
start.strftime("%Y-%m-%d %H:%M"))
pm = ProjectManager()
project = pm.loadProject(projFile)
### Set duration & timestep & simulation configuration
project.simulationParameters.setDt(simDt)
simConfig = project.simConfigInfo.getSimConfig(simConfig)
simConfig.setSimDuration(simDuration)
### Set simulation reference
index = 0
simRef = "%s%i" % (simRefPrefix, index)
while File("%s/simulations/%s_N" %
(project.getProjectMainDirectory().getCanonicalPath(),
simRef)).exists():
simRef = "%s%i" % (simRefPrefix, index)
index = index + 1
project.simulationParameters.setReference(simRef)
### Change num in each cell group
numFRB = int(scaleCortex * numFRB)
numRS = int(scaleCortex * numRS)
numSupBask = int(scaleCortex * numSupBask)
numSupAxAx = int(scaleCortex * numSupAxAx)
numSupLTS = int(scaleCortex * numSupLTS)
numL4SpinStell = int(scaleCortex * numL4SpinStell)
numL5TuftIB = int(scaleCortex * numL5TuftIB)
numL5TuftRS = int(scaleCortex * numL5TuftRS)
numDeepBask = int(scaleCortex * numDeepBask)
numDeepAxAx = int(scaleCortex * numDeepAxAx)
numDeepLTS = int(scaleCortex * numDeepLTS)
numL6NonTuftRS = int(scaleCortex * numL6NonTuftRS)
numTCR = int(scaleThalamus * numTCR)
numnRT = int(scaleThalamus * numnRT)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_L23PyrFRB").setMaxNumberCells(
numFRB) # Note only works if RandomCellPackingAdapter
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_L23PyrRS").setMaxNumberCells(numRS)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_SupBask").setMaxNumberCells(numSupBask)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_SupAxAx").setMaxNumberCells(numSupAxAx)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_SupLTS").setMaxNumberCells(numSupLTS)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_L4SpinStell").setMaxNumberCells(numL4SpinStell)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_L5TuftIB").setMaxNumberCells(numL5TuftIB)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_L5TuftRS").setMaxNumberCells(numL5TuftRS)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_DeepBask").setMaxNumberCells(numDeepBask)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_DeepAxAx").setMaxNumberCells(numDeepAxAx)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_DeepLTS").setMaxNumberCells(numDeepLTS)
project.cellGroupsInfo.getCellPackingAdapter(
"CG3D_L6NonTuftRS").setMaxNumberCells(numL6NonTuftRS)
project.cellGroupsInfo.getCellPackingAdapter("CG3D_TCR").setMaxNumberCells(
numTCR)
project.cellGroupsInfo.getCellPackingAdapter("CG3D_nRT").setMaxNumberCells(
numnRT)
### Change weights in synapses/gap junctions
for netConnName in simConfig.getNetConns():
if gabaScaling != 1:
SimulationsInfo.addExtraSimProperty("gabaWeightScaling",
str(gabaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("GABAA") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, gabaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(gabaScaling))
if l4ssAmpaScaling != 1:
SimulationsInfo.addExtraSimProperty("l4ssAmpaScaling",
str(l4ssAmpaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("Syn_AMPA_L4SS_L4SS") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, l4ssAmpaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(l4ssAmpaScaling))
if l5PyrGapScaling != 1:
SimulationsInfo.addExtraSimProperty("l5PyrGapScaling",
str(l5PyrGapScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
tgtCG = project.morphNetworkConnectionsInfo.getTargetCellGroup(
netConnName)
if synName.count("Syn_Elect_DeepPyr_DeepPyr"
) > 0 and tgtCG.count("CG3D_L5") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, l5PyrGapScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(l5PyrGapScaling))
if inNrtTcrNmdaScaling != 1:
SimulationsInfo.addExtraSimProperty("inNrtTcrNmdaScaling",
str(inNrtTcrNmdaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("NMDA") > 0 and (
synName.endswith("_IN") > 0
or synName.endswith("_DeepIN") > 0
or synName.endswith("_SupIN") > 0
or synName.endswith("_SupFS") > 0
or synName.endswith("_DeepFS") > 0
or synName.endswith("_SupLTS") > 0
or synName.endswith("_DeepLTS") > 0
or synName.endswith("_nRT") > 0
or synName.endswith("_TCR") > 0):
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, inNrtTcrNmdaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(inNrtTcrNmdaScaling))
if pyrSsNmdaScaling != 1:
SimulationsInfo.addExtraSimProperty("pyrSsNmdaScaling",
str(pyrSsNmdaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("NMDA") > 0 and (
synName.endswith("_SupPyr") > 0
or synName.endswith("_DeepPyr") > 0
or synName.endswith("_L4SS") > 0
or synName.endswith("_L5Pyr") > 0
or synName.endswith("_L5RS") > 0
or synName.endswith("_L5IB") > 0
or synName.endswith("_L6NT") > 0
or synName.endswith("_Pyr") > 0):
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, pyrSsNmdaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(pyrSsNmdaScaling))
### Change bias currents
for inputName in simConfig.getInputs():
stim = project.elecInputInfo.getStim(inputName)
if deepBiasCurrent >= 0:
if stim.getElectricalInput().TYPE == "IClamp" and (
stim.getCellGroup() == "CG3D_L5TuftIB"
or stim.getCellGroup() == "CG3D_L5TuftRS"
or stim.getCellGroup() == "CG3D_L6NonTuftRS"):
print "Changing offset current in %s to %f" % (
stim.getCellGroup(), deepBiasCurrent)
stim.setAmp(NumberGenerator(deepBiasCurrent))
project.elecInputInfo.updateStim(stim)
### Change spatial discretisation of some cells. This will impact accuracy & simulation speed
if maxElecLenFRB > 0:
frbCell = project.cellManager.getCell("L23PyrFRB_varInit")
info = CellTopologyHelper.recompartmentaliseCell(
frbCell, maxElecLenFRB, project)
print "Recompartmentalised FRB cell: " + info
if somaNseg > 0:
frbCell.getSegmentWithId(
0).getSection().setNumberInternalDivisions(somaNseg)
if maxElecLenRS > 0:
rsCell = project.cellManager.getCell("L23PyrRS")
info = CellTopologyHelper.recompartmentaliseCell(
rsCell, maxElecLenRS, project)
print "Recompartmentalised RS cell: " + info
if somaNseg > 0:
rsCell.getSegmentWithId(0).getSection().setNumberInternalDivisions(
somaNseg)
if maxElecLenIN > 0:
inCells = [
"SupBasket", "SupAxAx", "SupLTSInter", "DeepBasket", "DeepAxAx",
"DeepLTSInter"
]
for inCellName in inCells:
inCell = project.cellManager.getCell(inCellName)
info = CellTopologyHelper.recompartmentaliseCell(
inCell, maxElecLenIN, project)
print "Recompartmentalised " + inCellName + " cell: " + info
if somaNseg > 0:
inCell.getSegmentWithId(
0).getSection().setNumberInternalDivisions(somaNseg)
### Change parallel configuration
mpiSettings = MpiSettings()
simConfig.setMpiConf(mpiSettings.getMpiConfiguration(mpiConf))
print "Parallel configuration: " + str(simConfig.getMpiConf())
if suggestedRemoteRunTime > 0:
project.neuronFileManager.setSuggestedRemoteRunTime(
suggestedRemoteRunTime)
project.genesisFileManager.setSuggestedRemoteRunTime(
suggestedRemoteRunTime)
### Change synaptic delay associated with each net conn
for netConnName in simConfig.getNetConns():
if netConnName.count("gap") == 0:
print "Changing synaptic delay in %s to %f" % (
netConnName, defaultSynapticDelay)
delayGen = NumberGenerator(defaultSynapticDelay)
for synProps in project.morphNetworkConnectionsInfo.getSynapseList(
netConnName):
synProps.setDelayGenerator(delayGen)
# defaultSynapticDelay will be recorded in simulation.props and listed in SimulationBrowser GUI
SimulationsInfo.addExtraSimProperty("defaultSynapticDelay",
str(defaultSynapticDelay))
### Generate network structure in neuroConstruct
pm.doGenerate(simConfig.getName(), neuroConstructSeed)
while pm.isGenerating():
print "Waiting for the project to be generated with Simulation Configuration: " + str(
simConfig)
sleep(2)
print "Generated %i cells in %i cell groups" % (
project.generatedCellPositions.getNumberInAllCellGroups(),
project.generatedCellPositions.getNumberNonEmptyCellGroups())
print "Generated %i instances in %i network connections" % (
project.generatedNetworkConnections.getNumAllSynConns(),
project.generatedNetworkConnections.getNumNonEmptyNetConns())
print "Generated %i instances in %i elect inputs" % (
project.generatedElecInputs.getNumberSingleInputs(),
project.generatedElecInputs.getNonEmptyInputRefs().size())
if simulators.count("NEURON") > 0:
simRefN = simRef + "_N"
project.simulationParameters.setReference(simRefN)
nc.generateAndRunNeuron(project,
pm,
simConfig,
simRefN,
simulatorSeed,
verbose=verbose,
runInBackground=runInBackground,
varTimestep=varTimestepNeuron)
sleep(2) # wait a while before running GENESIS...
if simulators.count("GENESIS") > 0:
simRefG = simRef + "_G"
project.simulationParameters.setReference(simRefG)
nc.generateAndRunGenesis(project,
pm,
simConfig,
simRefG,
simulatorSeed,
verbose=verbose,
runInBackground=runInBackground)
sleep(2) # wait a while before running MOOSE...
if simulators.count("MOOSE") > 0:
simRefM = simRef + "_M"
project.simulationParameters.setReference(simRefM)
nc.generateAndRunMoose(project,
pm,
simConfig,
simRefM,
simulatorSeed,
verbose=verbose,
runInBackground=runInBackground)
sleep(2) # wait a while before running GENESIS...
print "Finished running all sims, shutting down..."
stop = datetime.datetime.now()
print
print "Started: %s, finished: %s" % (start.strftime("%Y-%m-%d %H:%M"),
stop.strftime("%Y-%m-%d %H:%M"))
print
# generate
pm.doGenerate(sim_config_name, 1234)
while pm.isGenerating():
time.sleep(0.02)
print('network generated for stim type ' + stim_type)
for rate in stim_rate_range:
sim_ref = 'io' + stim_type + timestamp + '_' + str(int(round(rate)))
sim_refs.append(sim_ref)
sim_path = '../simulations/' + sim_ref
project.simulationParameters.setReference(sim_ref)
# set stim rate
rate_in_kHz = rate/1000.
stim = project.elecInputInfo.getStim('relay_stim')
stim.setRate(NumberGenerator(rate_in_kHz))
project.elecInputInfo.updateStim(stim)
# generate and compile neuron files
print "Generating NEURON scripts..."
project.neuronFileManager.setSuggestedRemoteRunTime(10)
simulator_seed = random.getrandbits(32)
project.neuronFileManager.generateTheNeuronFiles(sim_config, None, NeuronFileManager.RUN_HOC,simulator_seed)
compile_process = ProcessManager(project.neuronFileManager.getMainHocFile())
compile_success = compile_process.compileFileWithNeuron(0,0)
# simulate
if compile_success:
print "Submitting simulation reference " + sim_ref
pm.doRunNeuron(sim_config)
time.sleep(2) # Wait for sim to be kicked off
if not sim_config.getMpiConf().isRemotelyExecuted():
# if running locally, never have more than one sim running
### Change weights in synapses/gap junctions
for netConnName in simConfig.getNetConns():
if gabaScaling != 1:
SimulationsInfo.addExtraSimProperty("gabaWeightScaling", str(gabaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(netConnName).get(index).getSynapseType()
if synName.count("GABAA")>0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f"%(synName, netConnName, gabaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(netConnName).get(index).setWeightsGenerator(NumberGenerator(gabaScaling))
if l4ssAmpaScaling !=1:
SimulationsInfo.addExtraSimProperty("l4ssAmpaScaling", str(l4ssAmpaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(netConnName).get(index).getSynapseType()
if synName.count("Syn_AMPA_L4SS_L4SS")>0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f"%(synName, netConnName, l4ssAmpaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(netConnName).get(index).setWeightsGenerator(NumberGenerator(l4ssAmpaScaling))
### Change bias currents
if not syn in cellMechNames:
print "Synapse mechanism %s not found in project!"%syn
exit()
synProp = SynapticProperties(syn)
synProp.setThreshold(0)
synProp.setFixedDelay(default_syn_delay)
synList.add(synProp)
searchPattern = SearchPattern.getRandomSearchPattern()
maxMinLength = MaxMinLength()
connectivityConditions = ConnectivityConditions()
connectivityConditions.setGenerationDirection(ConnectivityConditions.TARGET_TO_SOURCE)
connectivityConditions.setNumConnsInitiatingCellGroup(NumberGenerator(numPre))
if "axon" in postGroup:
connectivityConditions.getPrePostAllowedLoc().setAxonsAllowedPost(1)
if "dend" in preGroup:
connectivityConditions.getPrePostAllowedLoc().setDendritesAllowedPre(1)
connectivityConditions.setAllowAutapses(0)
if("Elect" in syns[0]):
connectivityConditions.setNoRecurrent(1)
netConnInfo.addNetConn(netConnName,
source,
target,
SimulationsInfo.addExtraSimProperty("gabaWeightScaling",
str(gabaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("GABAA") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, gabaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(gabaScaling))
if l4ssAmpaScaling != 1:
SimulationsInfo.addExtraSimProperty("l4ssAmpaScaling",
str(l4ssAmpaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("Syn_AMPA_L4SS_L4SS") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, l4ssAmpaScaling)
while pm.isGenerating():
time.sleep(0.02)
print('network generated')
for amplitude in stim_amplitude_range:
sim_ref = utils.ir_sim_ref(timestamp, gj_conn_type, amplitude,
trial)
sim_refs.append(sim_ref)
sim_path = '../simulations/' + sim_ref
project.simulationParameters.setReference(sim_ref)
# set stim rate
amplitude_in_nA = amplitude / 1000.
for cell_type in ['Vervaeke', 'reduced']:
stim = project.elecInputInfo.getStim('cclamp_network_' +
cell_type)
stim.setAmp(NumberGenerator(amplitude_in_nA))
project.elecInputInfo.updateStim(stim)
# generate and compile neuron files
print "Generating NEURON scripts..."
project.neuronFileManager.setSuggestedRemoteRunTime(10)
simulator_seed = random.getrandbits(32)
project.neuronFileManager.generateTheNeuronFiles(
sim_config, None, NeuronFileManager.RUN_HOC, simulator_seed)
compile_process = ProcessManager(
project.neuronFileManager.getMainHocFile())
compile_success = compile_process.compileFileWithNeuron(0, 0)
# simulate
if compile_success:
print "Submitting simulation reference " + sim_ref
pm.doRunNeuron(sim_config)
time.sleep(2) # Wait for sim to be kicked off
def testAll(argv=None):
if argv is None:
argv = sys.argv
print "Loading project from "+ projFile.getCanonicalPath()
simManager = nc.SimulationManager(projFile,
numConcurrentSims = numConcurrentSims,
verbose = verbose)
### Change num in each cell group
simManager.project.cellGroupsInfo.getCellPackingAdapter("ExcCells").setMaxNumberCells(numExcCells)
simManager.project.cellGroupsInfo.getCellPackingAdapter("INCells").setMaxNumberCells(numINCells)
### Change weights in synapses/gap junctions
simConfig = simManager.project.simConfigInfo.getSimConfig(simConfigName)
for netConnName in simConfig.getNetConns():
print "Changing synaptic delay in %s to %f"%(netConnName, defaultSynapticDelay)
delayGen = NumberGenerator(defaultSynapticDelay)
for synProps in simManager.project.morphNetworkConnectionsInfo.getSynapseList(netConnName):
synProps.setDelayGenerator(delayGen)
# defaultSynapticDelay will be recorded in simulation.props and listed in SimulationBrowser GUI
SimulationsInfo.addExtraSimProperty("defaultSynapticDelay", str(defaultSynapticDelay))
allSims = simManager.runMultipleSims(simConfigs = [simConfigName],
simDt = simDt,
simDuration = simDuration,
simulators = simulators,
runInBackground = runInBackground,
varTimestepNeuron = varTimestepNeuron,
mpiConfigs = mpiConfigs,
suggestedRemoteRunTime = suggestedRemoteRunTime,
simRefGlobalPrefix = simAllPrefix,
runSims = runSims,
neuroConstructSeed = neuroConstructSeed,
simulatorSeed = simulatorSeed)
while (len(simManager.allRunningSims)>0):
print "Waiting for the following sims to finish: "+str(simManager.allRunningSims)
time.sleep(5) # wait a while...
simManager.updateSimsRunning()
for sim in allSims:
simDir = File(projFile.getParentFile(), "/simulations/"+sim)
try:
simData = SimulationData(simDir)
simData.initialise()
simTime = simData.getSimulationProperties().getProperty("RealSimulationTime")
print "Simulation: %s took %s seconds"%(sim, simTime)
except:
print "Error analysing simulation data from: %s"%simDir.getCanonicalPath()
if mpiConfigs == [MpiSettings.LOCAL_SERIAL] or mpiConfigs == [MpiSettings.MATLEM_1PROC]:
simManager.reloadSims(plotVoltageOnly = True,
plotSims = plotSims,
analyseSims = analyseSims)
# Load an existing neuroConstruct project
projFile = File("TestPython/TestPython.neuro.xml")
print "Loading project from file: " + projFile.getAbsolutePath(
) + ", exists: " + str(projFile.exists())
pm = ProjectManager()
myProject = pm.loadProject(projFile)
print "Loaded project: " + myProject.getProjectName()
# Get first electrical stimulation & reset it
stim = myProject.elecInputInfo.getStim(0)
print "First stimulation setting: " + str(stim)
newAmp = random() * 0.2
stim.setAmp(NumberGenerator(newAmp))
myProject.elecInputInfo.updateStim(stim)
print "Stimulation now: " + str(myProject.elecInputInfo.getStim(0))
# Save project & exit
myProject.markProjectAsEdited()
myProject.saveProject()
System.exit(0)
SimulationsInfo.addExtraSimProperty("gabaWeightScaling",
str(gabaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("GABAA") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, gabaScaling)
project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).setWeightsGenerator(
NumberGenerator(gabaScaling))
if l4ssAmpaScaling != 1:
SimulationsInfo.addExtraSimProperty("l4ssAmpaScaling",
str(l4ssAmpaScaling))
synList = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName)
for index in range(0, len(synList)):
synName = project.morphNetworkConnectionsInfo.getSynapseList(
netConnName).get(index).getSynapseType()
if synName.count("Syn_AMPA_L4SS_L4SS") > 0:
print "Changing synaptic weight for syn %s in net conn %s by factor %f" % (
synName, netConnName, l4ssAmpaScaling)
synProp = SynapticProperties(syn)
synProp.setThreshold(0)
synProp.setFixedDelay(default_syn_delay)
synList.add(synProp)
searchPattern = SearchPattern.getRandomSearchPattern()
#searchPattern = SearchPattern.getClosestSearchPattern() # will be better, but slower!
maxMinLength = MaxMinLength()
connectivityConditions = ConnectivityConditions()
connectivityConditions.setGenerationDirection(
ConnectivityConditions.SOURCE_TO_TARGET)
connectivityConditions.setNumConnsInitiatingCellGroup(
NumberGenerator(numPre))
print "Set NumConnsInitiatingCellGroup to %i" % numPre
if "axon" in postGroup:
connectivityConditions.getPrePostAllowedLoc().setAxonsAllowedPost(
1)
connectivityConditions.getPrePostAllowedLoc(
).setDendritesAllowedPost(0)
connectivityConditions.getPrePostAllowedLoc().setSomaAllowedPost(0)
print "Set connectivityConditions: " + str(connectivityConditions)
connectivityConditions.setAllowAutapses(0)
if ("Elect" in syns[0]):