def setup_model():
"""Setup a dummy model with a pulsegen and a spikegen detecting the
leading edges of the pulses. We record the pulse output as Uniform
data and leading edge time as Event data."""
simtime = 100.0
dt = 1e-3
model = moose.Neutral('/model')
pulse = moose.PulseGen('/model/pulse')
pulse.level[0] = 1.0
pulse.delay[0] = 10
pulse.width[0] = 20
t_lead = moose.SpikeGen('/model/t_lead')
t_lead.threshold = 0.5
moose.connect(pulse, 'output', t_lead, 'Vm')
nsdf = moose.NSDFWriter('/model/writer')
nsdf.filename = 'nsdf_demo.h5'
nsdf.mode = 2 #overwrite existing file
nsdf.flushLimit = 100
moose.connect(nsdf, 'requestOut', pulse, 'getOutputValue')
print 'event input', nsdf.eventInput, nsdf.eventInput.num
print nsdf
nsdf.eventInput.num = 1
ei = nsdf.eventInput[0]
print ei.path
moose.connect(t_lead, 'spikeOut', nsdf.eventInput[0], 'input')
tab = moose.Table('spiketab')
tab.threshold = t_lead.threshold
clock = moose.element('/clock')
for ii in range(32):
moose.setClock(ii, dt)
moose.connect(pulse, 'output', tab, 'spike')
print datetime.now().isoformat()
moose.reinit()
moose.start(simtime)
print datetime.now().isoformat()
np.savetxt('nsdf.txt', tab.vector)
###################################
# Set the environment attributes
###################################
nsdf.stringAttr['title'] = 'NSDF writing demo for moose'
nsdf.stringAttr[
'description'] = '''An example of writing data to NSDF file from MOOSE simulation. In
this simulation we generate square pules from a PulseGen object and
use a SpikeGen to detect the threshold crossing events of rising
edges. We store the pulsegen output as Uniform data and the threshold
crossing times as Event data. '''
nsdf.stringAttr['creator'] = getpass.getuser()
nsdf.stringVecAttr['software'] = ['python2.7', 'moose3']
nsdf.stringVecAttr['method'] = ['']
nsdf.stringAttr['rights'] = ''
nsdf.stringAttr['license'] = 'CC-BY-NC'
# Specify units. MOOSE is unit agnostic, so we explicitly set the
# unit attibutes on individual datasets
nsdf.stringAttr['/data/uniform/PulseGen/outputValue/tunit'] = 's'
nsdf.stringAttr['/data/uniform/PulseGen/outputValue/unit'] = 'A'
eventDataPath = '/data/event/SpikeGen/spikeOut/{}_{}_{}/unit'.format(
t_lead.vec.value, t_lead.getDataIndex(), t_lead.getFieldIndex())
nsdf.stringAttr[eventDataPath] = 's'
def write_nsdf():
"""
Setup a dummy model with a PulseGen vec and dump the outputValue in
NSDF file
"""
simtime = 100.0
dt = 1e-3
elements = 5
model = moose.Neutral('/model')
pulsegen = moose.PulseGen('/model/pulse', elements)
spikegen = moose.SpikeGen('/model/t_lead', elements)
nsdf = moose.NSDFWriter('/model/writer')
nsdf.filename = 'nsdf_vec_demo.h5'
nsdf.mode = 2 #overwrite existing file
# nsdf.eventInput.num = elements
nsdf.flushLimit = 100
for ii in range(elements):
pulse = pulsegen.vec[ii]
t_lead = spikegen.vec[ii]
# Just to make the values different for different elements in
# the vec ...
pulse.level[0] = 1.0 * (ii + 1)
pulse.delay[0] = 5 * (ii + 1)
pulse.width[0] = 20
t_lead.threshold = 0.5
moose.connect(pulse, 'output', t_lead, 'Vm')
moose.connect(nsdf, 'requestOut', pulse, 'getOutputValue')
# ei = nsdf.eventInput[ii]
# moose.connect(t_lead, 'spikeOut', ei, 'input')
# tab = moose.Table('spiketab_{}'.format(ii))
# tab.threshold = t_lead.threshold
# moose.connect(pulse, 'output', tab, 'spike')
clock = moose.element('/clock')
for ii in range(32):
moose.setClock(ii, dt)
print(('Starting simulation at:', datetime.now().isoformat()))
moose.reinit()
moose.start(simtime)
print(('Finished simulation at:', datetime.now().isoformat()))
###################################
# Set the environment attributes
###################################
nsdf.stringAttr['title'] = 'NSDF writing demo for moose'
nsdf.stringAttr[
'description'] = '''An example of writing data to NSDF file from MOOSE simulation. In
this simulation we generate square pules from a PulseGen object and
use a SpikeGen to detect the threshold crossing events of rising
edges. We store the pulsegen output as Uniform data and the threshold
crossing times as Event data. '''
nsdf.stringAttr['creator'] = getpass.getuser()
nsdf.stringVecAttr['software'] = ['python2.7', 'moose3']
nsdf.stringVecAttr['method'] = ['']
nsdf.stringAttr['rights'] = ''
nsdf.stringAttr['license'] = 'CC-BY-NC'
####################################################
## !! Work in progress: concurrent write via h5py does not work !!
####################################################
## Now write some custom stuff via h5py
print('Closing nsdf handle')
nsdf.close() #explicitly close the file so we do not interfere with h5py
print('Closed nsdf handle')
with h5.File(nsdf.filename, 'a') as fd:
static = fd.create_group('/data/static')
static_pg = static.create_group(pulsegen.className)
pulse_info = static_pg.create_dataset('pulse_0', (elements, ),
dtype=np.dtype([
('delay', 'float64'),
('level', 'float64'),
('width', 'float64')
]))
map_ = fd.create_group('/map/static')
map_pg = map_.create_group(pulsegen.className)
map_pulse = map_pg.create_dataset('pulse_0', (elements, ),
dtype=h5.special_dtype(vlen=str))
for ii in range(elements):
pulse_info['delay', ii] = pulsegen.vec[ii].delay[0]
pulse_info['width', ii] = pulsegen.vec[ii].width[0]
pulse_info['level', ii] = pulsegen.vec[ii].level[0]
map_pulse[ii] = pulsegen.vec[ii].path
#TODO: connect this as a dimension scale on pulse_info
return nsdf.filename
References:
Ray, Chintaluri, Bhalla and Wojcik. NSDF: Neuroscience Simulation Data
Format, Neuroinformatics, 2015.
http://nsdf.readthedocs.org/en/latest/
"""
import numpy as np
from datetime import datetime
import getpass
import moose
try:
nsdf = moose.NSDFWriter('/test')
except AttributeError as e:
print("[INFO ] This build is not built with NSDFWriter.")
print('\tPlease see https://github.com/BhallaLab/moose-core')
quit()
def setup_model():
"""
Setup a dummy model with a PulseGen and a SpikeGen. The SpikeGen
detects the leading edges of the pulses created by the PulseGen
and sends out the event times. We record the PulseGen outputValue
as Uniform data and leading edge time as Event data in the NSDF
file.
"""
# Maintainer:
# Created: Sat Dec 19 22:27:27 2015 (-0500)
# Version:
# Last-Updated: Thu Aug 11 11:09:33 2016 (-0400)
# By: Subhasis Ray
# Update #: 135
# URL:
# Keywords:
# Compatibility:
#
import numpy as np
from datetime import datetime
import getpass
import moose
try:
a = moose.NSDFWriter( '/a' )
except Exception as e:
print( '[WARN] This build does not have NSDF support.' )
print( ' -- To build moose with NSDF support please see: \
https://github.com/BhallaLab/moose-core/blob/master/INSTALL.md' )
quit()
try:
import h5py as h5
except ImportError as e:
print( 'No module h5py. Please install it using pip' )
quit()
from matplotlib import pyplot as plt
