def run(description):
"""Main function for running a perisomatic biophysical experiment.
Parameters
----------
description : Config
All information needed to run the experiment.
"""
# configure NEURON
utils = Utils(description)
h = utils.h
# configure model
manifest = description.manifest
morphology_path = description.manifest.get_path("MORPHOLOGY")
utils.generate_morphology(morphology_path.encode("ascii", "ignore"))
utils.load_cell_parameters()
# configure stimulus and recording
stimulus_path = description.manifest.get_path("stimulus_path")
run_params = description.data["runs"][0]
sweeps = run_params["sweeps"]
junction_potential = description.data["fitting"][0]["junction_potential"]
mV = 1.0e-3
stimulus_format = manifest.get_format("stimulus_path")
output_format = manifest.get_format("output")
if stimulus_format == "NWB" and output_format == "NWB":
prepare_nwb_output(manifest.get_path("stimulus_path"), manifest.get_path("output"))
# run sweeps
for sweep in sweeps:
if stimulus_format == "NWB":
utils.setup_iclamp(stimulus_path, sweep=sweep)
elif stimulus_format == "dat":
utils.setup_iclamp_dat(stimulus_path)
vec = utils.record_values()
h.finitialize()
h.run()
# write to an NWB File
output_data = (numpy.array(vec["v"]) - junction_potential) * mV
output_times = numpy.array(vec["t"])
if output_format == "NWB":
output_path = manifest.get_path("output")
save_nwb(output_path, output_data, sweep)
elif output_format == "dat":
output_path = manifest.get_path("output", sweep)
DatUtilities.save_voltage(output_path, output_data, output_times)
def read_local_swc():
morphs=[]
cells1=[]
Utils.initialize_hoc()
swclist=glob.glob('*.swc')
for swcf in swclist:
#morphology = swc.read_swc(swcf)
morphology=Utils.generate_morphology(swcf)
cell1=Utils.load_cell_parameters()
cells1.append(cell1)
print type(cells1)
print type(cell1)
morphology.root
morphs.append(morphology)
return morphs,swclist,cells1
def run(description, sweeps=None):
'''Main function for running a perisomatic biophysical experiment.
Parameters
----------
description : Config
All information needed to run the experiment.
'''
# configure NEURON
utils = Utils(description)
h = utils.h
# configure model
manifest = description.manifest
morphology_path = description.manifest.get_path('MORPHOLOGY')
utils.generate_morphology(morphology_path.encode('ascii', 'ignore'))
utils.load_cell_parameters()
# configure stimulus and recording
stimulus_path = description.manifest.get_path('stimulus_path')
run_params = description.data['runs'][0]
if sweeps == None:
sweeps = run_params['sweeps']
junction_potential = description.data['fitting'][0]['junction_potential']
mV = 1.0e-3
prepare_nwb_output(manifest.get_path('stimulus_path'),
manifest.get_path('output'))
# run sweeps
for sweep in sweeps:
utils.setup_iclamp(stimulus_path, sweep=sweep)
vec = utils.record_values()
h.finitialize()
h.run()
# write to an NWB File
output_data = (numpy.array(vec['v']) - junction_potential) * mV
output_path = manifest.get_path("output")
save_nwb(output_path, output_data, sweep)
#Based on example code at: http://alleninstitute.github.io/AllenSDK/biophysical_perisomatic_script.html
from allensdk.model.biophysical_perisomatic.utils import Utils
from allensdk.model.biophysical_perisomatic.runner import load_description
description = load_description('manifest.json')
# configure NEURON
utils = Utils(description)
h = utils.h
print("NEURON configured")
# configure model
manifest = description.manifest
morphology_path = description.manifest.get_path('MORPHOLOGY')
utils.generate_morphology(morphology_path.encode('ascii', 'ignore'))
utils.load_cell_parameters()
print("Cell loaded from: %s" % morphology_path)
# configure stimulus and recording
stimulus_path = description.manifest.get_path('stimulus_path')
run_params = description.data['runs'][0]
sweeps = [23, 57, 60]
junction_potential = description.data['fitting'][0]['junction_potential']
mV = 1.0e-3
for sweep in sweeps:
count = 0
for model_id in cell_dirs:
if os.path.isdir(model_id):
os.chdir(model_id)
else:
os.chdir('../' + model_id)
print(
'\n\n************************************************************\n\n Parsing %s (cell %i/%i)\n'
% (model_id, count, len(cell_dirs)))
description = load_description('manifest.json')
# configure NEURON
utils = Utils(description)
h = utils.h
print("NEURON configured")
# configure model
manifest = description.manifest
morphology_path = description.manifest.get_path('MORPHOLOGY')
utils.generate_morphology(morphology_path.encode('ascii', 'ignore'))
utils.load_cell_parameters()
print("Cell loaded from: %s" % morphology_path)
h.finitialize()
h.psection()
import os
from allensdk.core.nwb_data_set import NwbDataSet
import glob
from allensdk.model.biophysical_perisomatic.utils import Utils
from allensdk.model.biophys_sim.config import Config
#import d3py
import pickle
bp = BiophysicalPerisomaticApi('http://api.brain-map.org')
#import unittest
from utils import Utils
import numpy as np
import pdb
config = Config().load('config.json')
# The readin flag when set enables the wiring to be read in from pre-existing
# pickled files with rank specific file names.
utils = Utils(config,NCELL=60,readin=0)
info_swc=utils.gcs(utils.NCELL)
utils.wirecells()#wire cells on different hosts.
utils.global_icm=utils.matrix_reduce(utils.icm)
utils.global_ecm=utils.matrix_reduce(utils.ecm)
utils.global_visited=utils.matrix_reduce(utils.visited)
if utils.COMM.rank==0:
utils.dumpjson_graph()
utils.h('forall{ for(x,0){ uninsert xtra}}') #mechanism only needed for wiring cells not for simulating them.
from rigp import NetStructure
if utils.COMM.rank==0:
hubs=NetStructure(utils,utils.global_ecm,utils.global_icm,utils.visited,utils.celldict)
print 'experimental rig'
hubs.save_matrix()
# A global analysis of hub nodes, using global complete adjacency matrices.
#Inhibitory hub
clear_neuron()
count = 0
for model_id in cell_dirs:
if os.path.isdir(model_id):
os.chdir(model_id)
else:
os.chdir('../'+model_id)
print('\n\n************************************************************\n\n Parsing %s (cell %i/%i)\n'%(model_id, count, len(cell_dirs)))
description = load_description('manifest.json')
# configure NEURON
utils = Utils(description)
h = utils.h
print("NEURON configured")
# configure model
manifest = description.manifest
morphology_path = description.manifest.get_path('MORPHOLOGY')
utils.generate_morphology(morphology_path.encode('ascii', 'ignore'))
utils.load_cell_parameters()
print("Cell loaded from: %s"%morphology_path)
h.finitialize()
h.psection()
