def viewExperimentResult(self, payload: dict):
""" Loads the output file of a simulated experiment trial.
:param payload: {name: str, trial: str, onlyModelSpecification: bool}
:return: geppetto model
"""
name = payload.get("name", None)
trial = payload.get("trial", None)
only_model_spec = payload.get("onlyModelSpecification", False)
file = experiments.get_trial_output_path(name, trial)
if file is None or not os.path.exists(file):
return utils.getJSONError(
f"Couldn't find output file of condition. Please take a look at the simulation log.",
"")
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.initialize()
if only_model_spec:
# Load only model specification
sim.loadNetParams(file)
sim.loadSimCfg(file)
self.netParams = sim.net.params
self.simConfig = sim.cfg
netpyne_ui_utils.remove(self.simConfig.todict())
netpyne_ui_utils.remove(self.netParams.todict())
return
else:
# Load the complete simulation
sim.loadAll(file)
self._create3D_shapes(file)
self.geppetto_model = self.model_interpreter.getGeppettoModel(sim)
return json.loads(
GeppettoModelSerializer.serialize(self.geppetto_model))
def plot_batch_ind_conn(batchLabel,
batchdatadir=batchdatadir,
includePre=['all'],
includePost=['all'],
feature='strength',
orderBy='gid',
figSize=(10, 10),
groupBy='pop',
groupByIntervalPre=None,
groupByIntervalPost=None,
graphType='matrix',
synOrConn='syn',
synMech=None,
connsFile=None,
tagsFile=None,
clim=None,
fontSize=12,
saveData=None,
showFig=False,
save=True,
outputdir='batch_figs'):
"""Plots individual connectivity plots for each parameter combination."""
from netpyne import specs
if type(batchLabel) == str:
params, data = batch_utils.load_batch(batchLabel,
batchdatadir=batchdatadir)
elif type(batchLabel) == tuple:
batchLabel, params, data = batchLabel
else:
raise Exception()
simLabels = data.keys()
for simLabel in simLabels:
print('Plotting sim: ' + simLabel)
datum = data[simLabel]
cfg = specs.SimConfig(datum['simConfig'])
cfg.createNEURONObj = False
sim.initialize() # create network object and set cfg and net params
sim.loadAll('', data=datum, instantiate=False)
sim.setSimCfg(cfg)
try:
print('Cells created: ' + str(len(sim.net.allCells)))
except:
print('Alternate sim loading...')
sim.net.createPops()
sim.net.createCells()
sim.setupRecording()
sim.gatherData()
sim.allSimData = datum['simData']
features = [
'weight', 'delay', 'numConns', 'probability', 'strength',
'convergence', 'divergence'
]
for feature in features:
if save:
saveFig = batchdatadir + '/' + batchLabel + '/' + 'connFig_' + feature + simLabel + '.png'
else:
saveFig = None
sim.analysis.plotConn(includePre=includePre,
includePost=includePost,
feature=feature,
orderBy=orderBy,
figSize=figSize,
groupBy=groupBy,
groupByIntervalPre=groupByIntervalPre,
groupByIntervalPost=groupByIntervalPost,
graphType=graphType,
synOrConn=synOrConn,
synMech=synMech,
connsFile=connsFile,
tagsFile=tagsFile,
clim=clim,
fontSize=fontSize,
saveData=saveData,
saveFig=saveFig,
showFig=showFig)
def plot_batch_ind_stats(batchLabel,
batchdatadir=batchdatadir,
include=['allCells', 'eachPop'],
statDataIn={},
timeRange=None,
graphType='boxplot',
stats=['rate', 'isicv'],
bins=50,
popColors=[],
histlogy=False,
histlogx=False,
histmin=0.0,
density=False,
includeRate0=False,
legendLabels=None,
normfit=False,
histShading=True,
xlim=None,
dpi=100,
figSize=(6, 8),
fontSize=12,
saveData=None,
showFig=True,
save=True,
outputdir='batch_figs'):
"""Plots individual connectivity plots for each parameter combination."""
from netpyne import specs
if type(batchLabel) == str:
params, data = batch_utils.load_batch(batchLabel,
batchdatadir=batchdatadir)
elif type(batchLabel) == tuple:
batchLabel, params, data = batchLabel
else:
raise Exception()
simLabels = data.keys()
for simLabel in simLabels:
print('Plotting sim: ' + simLabel)
datum = data[simLabel]
cfg = specs.SimConfig(datum['simConfig'])
cfg.createNEURONObj = False
sim.initialize() # create network object and set cfg and net params
sim.loadAll('', data=datum, instantiate=False)
sim.setSimCfg(cfg)
try:
print('Cells created: ' + str(len(sim.net.allCells)))
except:
print('Alternate sim loading...')
sim.net.createPops()
sim.net.createCells()
sim.setupRecording()
sim.gatherData()
sim.allSimData = datum['simData']
if save:
saveFig = batchdatadir + '/' + batchLabel + '/' + 'statFig_' + simLabel
else:
saveFig = None
sim.analysis.plotSpikeStats(include=include,
statDataIn=statDataIn,
timeRange=timeRange,
graphType=graphType,
stats=stats,
bins=bins,
popColors=popColors,
histlogy=histlogy,
histlogx=histlogx,
histmin=histmin,
density=density,
includeRate0=includeRate0,
legendLabels=legendLabels,
normfit=normfit,
histShading=histShading,
xlim=xlim,
dpi=dpi,
figSize=figSize,
fontSize=fontSize,
saveData=saveData,
saveFig=saveFig,
showFig=showFig)
def plot_batch_ind_raster(batchLabel,
batchdatadir=batchdatadir,
include=['allCells'],
timeRange=None,
maxSpikes=1e8,
orderBy='gid',
orderInverse=False,
labels='legend',
popRates=False,
spikeHist=None,
spikeHistBin=5,
syncLines=False,
figSize=(10, 8),
saveData=None,
showFig=False,
save=True,
outputdir='batch_figs'):
"""Plots individual raster plots for each parameter combination."""
from netpyne import specs
if type(batchLabel) == str:
params, data = batch_utils.load_batch(batchLabel,
batchdatadir=batchdatadir)
elif type(batchLabel) == tuple:
batchLabel, params, data = batchLabel
else:
raise Exception()
simLabels = data.keys()
for simLabel in simLabels:
print('Plotting sim: ' + simLabel)
datum = data[simLabel]
cfg = specs.SimConfig(datum['simConfig'])
cfg.createNEURONObj = False
sim.initialize() # create network object and set cfg and net params
sim.loadAll('', data=datum, instantiate=False)
sim.setSimCfg(cfg)
try:
print('Cells created: ' + str(len(sim.net.allCells)))
except:
print('Alternate sim loading...')
sim.net.createPops()
sim.net.createCells()
sim.setupRecording()
sim.gatherData()
sim.allSimData = datum['simData']
if save:
saveFig = batchdatadir + '/' + batchLabel + '/' + 'rasterFig' + simLabel + '.png'
else:
saveFig = None
sim.analysis.plotRaster(include=include,
timeRange=timeRange,
maxSpikes=maxSpikes,
orderBy=orderBy,
orderInverse=orderInverse,
labels=labels,
popRates=popRates,
spikeHist=spikeHist,
spikeHistBin=spikeHistBin,
syncLines=syncLines,
figSize=figSize,
saveData=saveData,
saveFig=saveFig,
showFig=showFig)
def loadModel(self, args):
""" Imports a model stored as file in json format.
:param args:
:return:
"""
def remove(dictionary):
# remove reserved keys such as __dict__, __Method__, etc
# they appear when we do sim.loadAll(json_file)
if isinstance(dictionary, dict):
for key, value in list(dictionary.items()):
if key.startswith('__'):
dictionary.pop(key)
else:
remove(value)
if not any([
args[option] for option in
['loadNetParams', 'loadSimCfg', 'loadSimData', 'loadNet']
]):
return utils.getJSONError(
"Error while loading data",
'You have to select at least one option')
try:
owd = os.getcwd()
compileModMechFiles(args['compileMod'], args['modFolder'])
except:
return utils.getJSONError("Error while importing/compiling mods",
sys.exc_info())
finally:
os.chdir(owd)
try:
with redirect_stdout(sys.__stdout__):
sim.initialize()
wake_up_geppetto = False
if all([
args[option] for option in
['loadNetParams', 'loadSimCfg', 'loadSimData', 'loadNet']
]):
wake_up_geppetto = True
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.initialize()
sim.loadAll(args['jsonModelFolder'])
self.netParams = sim.net.params
self.simConfig = sim.cfg
remove(self.netParams.todict())
remove(self.simConfig.todict())
else:
if args['loadNet']:
wake_up_geppetto = True
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.initialize()
sim.loadNet(args['jsonModelFolder'])
if args['loadSimData']: # TODO (https://github.com/Neurosim-lab/netpyne/issues/360)
wake_up_geppetto = True
if not self.doIhaveInstOrSimData()['haveInstance']:
sim.create(specs.NetParams(), specs.SimConfig())
sim.net.defineCellShapes()
sim.gatherData(gatherLFP=False)
sim.loadSimData(args['jsonModelFolder'])
if args['loadSimCfg']:
sim.loadSimCfg(args['jsonModelFolder'])
self.simConfig = sim.cfg
remove(self.simConfig.todict())
if args['loadNetParams']:
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.loadNetParams(args['jsonModelFolder'])
self.netParams = sim.net.params
remove(self.netParams.todict())
if wake_up_geppetto:
if len(sim.net.cells) > 0:
section = list(sim.net.cells[0].secs.keys())[0]
if 'pt3d' not in list(
sim.net.cells[0].secs[section].geom.keys()):
sim.net.defineCellShapes()
sim.gatherData()
sim.loadSimData(args['jsonModelFolder'])
sim.gatherData()
self.geppetto_model = self.model_interpreter.getGeppettoModel(
sim)
return json.loads(
GeppettoModelSerializer.serialize(self.geppetto_model))
else:
return utils.getJSONReply()
except:
return utils.getJSONError("Error while loading the NetPyNE model",
sys.exc_info())
def loadModel(self, args):
""" Imports a model stored as file in json format.
:param args:
:return:
"""
if not any([
args[option] for option in
['loadNetParams', 'loadSimCfg', 'loadSimData', 'loadNet']
]):
return utils.getJSONError(
"Error while loading data",
'You have to select at least one option')
try:
owd = os.getcwd()
compileModMechFiles(args['compileMod'], args['modFolder'])
except Exception:
message = "Error while importing/compiling mods"
logging.exception(message)
return utils.getJSONError(message, sys.exc_info())
finally:
os.chdir(owd)
try:
with redirect_stdout(sys.__stdout__):
sim.initialize()
wake_up_geppetto = False
if all([
args[option] for option in
['loadNetParams', 'loadSimCfg', 'loadSimData', 'loadNet']
]):
wake_up_geppetto = True
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.initialize()
sim.loadAll(args['jsonModelFolder'])
self.netParams = sim.net.params
self.simConfig = sim.cfg
netpyne_ui_utils.remove(self.netParams.todict())
netpyne_ui_utils.remove(self.simConfig.todict())
else:
if args['loadNet']:
wake_up_geppetto = True
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.initialize()
sim.loadNet(args['jsonModelFolder'])
# TODO (https://github.com/Neurosim-lab/netpyne/issues/360)
if args['loadSimData']:
wake_up_geppetto = True
if not self.doIhaveInstOrSimData()['haveInstance']:
sim.create(specs.NetParams(), specs.SimConfig())
sim.net.defineCellShapes()
sim.gatherData(gatherLFP=False)
sim.loadSimData(args['jsonModelFolder'])
if args['loadSimCfg']:
sim.loadSimCfg(args['jsonModelFolder'])
self.simConfig = sim.cfg
netpyne_ui_utils.remove(self.simConfig.todict())
if args['loadNetParams']:
if self.doIhaveInstOrSimData()['haveInstance']:
sim.clearAll()
sim.loadNetParams(args['jsonModelFolder'])
self.netParams = sim.net.params
netpyne_ui_utils.remove(self.netParams.todict())
if wake_up_geppetto:
self._create3D_shapes(args['jsonModelFolder'])
# TODO: Fix me - gatherData will remove allSimData!
sim.gatherData()
self.geppetto_model = self.model_interpreter.getGeppettoModel(
sim)
return json.loads(
GeppettoModelSerializer.serialize(self.geppetto_model))
else:
return utils.getJSONReply()
except Exception:
message = "Error while loading the NetPyNE model"
logging.exception(message)
return utils.getJSONError(message, sys.exc_info())