def run_recs_fifos(pardir, outdir, ttime, recnames, fifonames, fifo_trange):
stimpar = jspar.load(os.path.join(pardir, 'stimpar.json'))
cellpar = jspar.load(os.path.join(pardir, 'cellpar.json'))
spkthr = jspar.load(os.path.join(pardir, 'spkthr.json'))
if not os.path.exists(outdir):
os.makedirs(outdir)
simfunc = run.cellpar_wrapper(run.simulation, cellpar, spkthr)
spkt, stimvec, recs, fifos = simfunc(ttime,
'OU',
stimpar,
None,
retstim=True,
recnames=recnames,
fifonames=fifonames,
fifo_trange=fifo_trange)
with open(os.path.join(outdir, 'fifos.p'), 'w') as f:
pickle.dump(fifos, f)
with open(os.path.join(outdir, 'recs.p'), 'w') as f:
pickle.dump(recs, f)
runpar = dict(hpar=run.hpar,
ttime=ttime,
stimpar=stimpar,
cellpar=cellpar,
spkthr=spkthr,
fifo_trange=fifo_trange)
rpfile = os.path.join(outdir, 'runpar.json')
jspar.save(rpfile, runpar)
def run_fifos(ttime, pardir, outdir):
stimpar = jspar.load(os.path.join(pardir, 'stimpar.json'))
cellpar = jspar.load(os.path.join(pardir, 'cellpar.json'))
spkthr = jspar.load(os.path.join(pardir, 'spkthr.json'))
if not os.path.exists(outdir):
os.makedirs(outdir)
simfunc = run.cellpar_wrapper(run.simulation, cellpar, spkthr)
fifonames = ('time', 'v_ais', 'icap_ais', 'nav_m')
fifo_trange = (-40, 0)
spkt, fifos = simfunc(ttime,
'OU',
stimpar,
None,
fifonames=fifonames,
fifo_trange=fifo_trange)
pff.save_fifos(fifos, outdir)
runpar = dict(hpar=run.hpar,
ttime=ttime,
stimpar=stimpar,
cellpar=cellpar,
spkthr=spkthr,
fifo_trange=fifo_trange)
rpfile = os.path.join(outdir, 'runpar.json')
jspar.save(rpfile, runpar)
def plot_align_thresh(indir,
yname,
trajcolor,
thrcolor,
label='',
tname='time'):
with open(os.path.join(indir, 'fifos.p')) as f:
fifos = pickle.load(f)
runpar = jspar.load(os.path.join(indir, 'runpar.json'))
fifo_trange = runpar['fifo_trange']
dt = runpar['hpar']['dt']
trng = (-20, -0.05)
taname = 'time_align'
fifos[taname] = np.tile(np.arange(fifo_trange[0], fifo_trange[1], dt),
(len(fifos[yname]), 1))
plot_traj(fifos,
taname,
yname,
trng,
fifo_trange,
dt,
label=label,
color=trajcolor,
alpha=0.7)
plot_thresh(fifos,
taname,
yname,
iname='icap_ais',
ithresh=0.001,
color=thrcolor,
label=label + ' thresh',
alpha=0.7)
def plot_contour(indir, newfig=True, **kwargs):
if newfig:
plt.figure()
mnvec = np.array(())
sdvec = np.array(())
# for wd in sorted(os.listdir(indir)):
for wd in ['']:
wpath = os.path.join(indir, wd)
ctpar = jspar.load(os.path.join(wpath, 'ctpar.json'))
xname = ctpar['xname']
fxvec = np.load(os.path.join(wpath, 'fxvec.npy'))
xvec = np.load(os.path.join(wpath, 'xvec.npy'))
if xname == 'std':
mnvec = np.concatenate((mnvec, fxvec))
sdvec = np.concatenate((sdvec, xvec))
elif xname == 'mean':
mnvec = np.concatenate((mnvec, xvec))
sdvec = np.concatenate((sdvec, fxvec))
else:
raise ValueError('xname not belong to std or mean')
# Remove nan in the arrays
nanind = np.logical_or(np.isnan(mnvec), np.isnan(sdvec))
mnvec = mnvec[~nanind]
sdvec = sdvec[~nanind]
# Sort arrays
mnvec, sdvec = zip(*sorted(zip(mnvec, sdvec)))
plt.plot(mnvec, sdvec, **kwargs)
if newfig:
# plt.ylim((0, 0.25))
plt.legend()
plt.savefig(os.path.join(indir, 'contour.pdf'))
def plot_traj_thresh(indir, xname, yname):
with open(os.path.join(indir, 'fifos.p')) as f:
fifos = pickle.load(f)
runpar = jspar.load(os.path.join(indir, 'runpar.json'))
fifo_trange = runpar['fifo_trange']
dt = runpar['hpar']['dt']
trng = (-40, -0.05)
plot_traj(fifos, xname, yname, trng, fifo_trange, dt)
plot_thresh(fifos, xname, yname, iname='icap_ais', ithresh=0.001)
def plot_operpoint(gkbar, spdir, frtli, colorli, cv=1, rad=0.005):
gkdir = labeldir.gkbar_dir(gkbar)
for i, frt in enumerate(frtli):
targsdir = labeldir.targs_dir(frt, cv)
indir = os.path.join(spdir, targsdir, gkdir)
stimpar = jspar.load(os.path.join(indir, 'stimpar.json'))
yrad = 2 * rad
color = colorli[i]
ell = patches.Ellipse((stimpar['mean'], stimpar['std']), rad, yrad, color=color, alpha=0.5)
ax = plt.gca()
ax.add_artist(ell)
def plot_gains(gkbarli, indir, figpath, normalized=False, statlab=False):
plt.figure(figsize=(8, 4))
for gkbar in gkbarli:
gkdir = labeldir.gkbar_dir(gkbar)
subdir = os.path.join(indir, gkdir)
transfdir = os.path.join(subdir, 'transfer')
transf = np.load(os.path.join(transfdir, 'transf.npy'))
fvec = np.load(os.path.join(transfdir, 'fvec.npy'))
gain = np.absolute(transf)
phase = np.angle(transf)
phase = np.negative(
phase
) ## this is used before changing phase to negative in transfer.py
lab = labeldir.gkbar_lab(gkbar)
if statlab:
statfile = os.path.join(subdir, 'spkstat.json')
if not os.path.isfile(statfile):
spkstat.get_spkstat_from_file(subdir)
stat = jspar.load(statfile)
stat_lab = '(frt:%.1f cv:%.2f lv:%.2f)' % (stat['frt'], stat['cv'],
stat['lv'])
lab = lab + ' ' + stat_lab
if normalized:
gain = gain / gain[1]
plt.subplot(121)
plt.semilogx(fvec, gain, label=lab)
plt.subplot(122)
plt.semilogx(fvec, phase, label=lab)
plt.subplot(121)
plt.xlabel('Frequency (Hz)')
if normalized:
plt.ylabel('Gain')
else:
plt.ylabel('Gain (Hz/nA)')
# plt.ylim(5e5, 2e6)
plt.legend(loc=1, prop={'size': 8}, fancybox=True, framealpha=0.5)
plt.subplot(122)
plt.xlabel('Frequency (Hz)')
plt.ylabel('Phase')
# plt.legend(prop={'size':8}, loc=4)
plt.legend(loc=1, prop={'size': 8}, fancybox=True, framealpha=0.5)
plt.tight_layout()
if figpath:
plt.savefig(figpath)
def plot_gains(tauli, indir, gkbar, frttarg, cvtarg, figpath, normalized=False, statlab=False):
plt.figure(figsize=(8, 4))
gkdir = labeldir.gkbar_dir(gkbar)
firgain = 0
for i, tau in enumerate(tauli):
optsubdir = labeldir.opt_subdir(tau, frttarg, cvtarg)
subdir = os.path.join(indir, optsubdir, gkdir)
transfdir = os.path.join(subdir, 'transfer')
transf = np.load(os.path.join(transfdir, 'transf.npy'))
fvec = np.load(os.path.join(transfdir, 'fvec.npy'))
gain = np.absolute(transf)
phase = np.angle(transf)
if normalized:
gain = gain / gain[1]
lab = labeldir.tau_lab(tau)
if statlab:
statfile = os.path.join(subdir, 'stat.json')
if not os.path.isfile(statfile):
spkstat.get_stat_from_file(subdir)
stat = jspar.load(statfile)
stat_lab = '(frt:%.1f cv:%.2f lv:%.2f)' % (stat['frt'], stat['cv'], stat['lv'])
lab = lab + ' ' + stat_lab
plt.subplot(121)
plt.semilogx(fvec, gain, label=lab)
plt.subplot(122)
plt.semilogx(fvec, phase, label=lab)
plt.subplot(121)
plt.xlabel('$f$ (Hz)')
if normalized:
plt.ylabel('Gain')
else:
plt.ylabel('Gain (Hz/nA)')
# plt.ylim(5e5, 2e6)
plt.legend(loc=1, prop={'size': 8}, fancybox=True, framealpha=0.5)
plt.subplot(122)
plt.xlabel('$f$ (Hz)')
plt.ylabel('Phase')
# plt.legend(prop={'size':8}, loc=4)
plt.legend(loc=1, prop={'size': 8}, fancybox=True, framealpha=0.5)
plt.tight_layout()
if figpath:
plt.savefig(figpath)
def plot_m_v(indir, label, trajcolor):
with open(os.path.join(indir, 'fifos.p')) as f:
fifos = pickle.load(f)
runpar = jspar.load(os.path.join(indir, 'runpar.json'))
fifo_trange = runpar['fifo_trange']
dt = runpar['hpar']['dt']
# trng = (-1, -0.05)
trng = (-20, -0.05)
rng = map(lambda x: get_ffind(x, fifo_trange[0], dt), trng)
pp.plot_multi_traj(fifos['v_ais'],
fifos['nav_m'],
fir=0,
num=20,
rng=rng,
label=label,
color=trajcolor,
alpha=0.5)
def run_simulation(ttime, outdir, pardir):
spkthrfile = os.path.join(pardir, 'spkthr.json')
cpfile = os.path.join(pardir, 'cellpar.json')
spfile = os.path.join(pardir, 'stimpar.json')
if not (os.path.exists(pardir) and os.path.isfile(cpfile)
and os.path.isfile(spfile) and os.path.isfile(spkthrfile)):
raise Exception(
'Please run run_optstimpar() before run_simulation()! pardir {}'.
format(pardir))
if not os.path.exists(outdir):
raise OSError('No such directory: {}'.format(outdir))
spkthr = jspar.load(spkthrfile)
stimtyp = 'OU'
args = [cpfile, spkthr, ttime, stimtyp, spfile, outdir]
submit_to_cluster('sim', '../../run/run_simulation.py', args)
def plot_i_v_thresh(indir, figpath, ithresh=0.001):
plt.figure()
with open(os.path.join(indir, 'fifos.p')) as f:
fifos = pickle.load(f)
runpar = jspar.load(os.path.join(indir, 'runpar.json'))
fifo_trange = runpar['fifo_trange']
dt = runpar['hpar']['dt']
# trng = (-1, -0.05)
trng = (-20, -0.05)
rng = map(lambda x: get_ffind(x, fifo_trange[0], dt), trng)
pp.plot_multi_traj(fifos['v_ais'],
fifos['icap_ais'],
fir=15,
num=20,
rng=rng,
color='#1f77b4',
alpha=0.7)
plt.axhline(ithresh, color='k', linestyle='dashed')
plt.xlabel('AIS membrane voltage (mV)')
plt.ylabel('AIS current density(mA/cm$^2$)')
plt.tight_layout()
plt.savefig(figpath)
parser.add_argument('cpfile', help='json file of cell parameter')
parser.add_argument('spkthr', type=float, help='json file of cell parameter')
parser.add_argument('ttime', type=float, help='total simulation time')
parser.add_argument('stimtyp', help='stimulation type')
parser.add_argument('spfile', help='json file of stimulation parameter')
parser.add_argument('outdir', help='output directory')
parser.add_argument('--moddir', help='path for model definition')
args = parser.parse_args()
if args.moddir:
moddir = args.moddir
else:
moddir = '.'
run = imp.load_source('run', os.path.join(moddir, 'run.py'))
stimpar = jspar.load(args.spfile)
cellpar = jspar.load(args.cpfile)
outdir = args.outdir
if not os.path.exists(outdir):
raise OSError('No such directory: {}'.format(outdir))
spktimes, stimvec = run.simulation(cellpar,
args.spkthr,
args.ttime,
args.stimtyp,
stimpar,
retstim=True)
runpar = dict(hpar=run.hpar,
ttime=args.ttime,
parser.add_argument('spkthr',
type=float,
help='voltage thresh for spike detection')
parser.add_argument('outdir', help='output directory')
parser.add_argument('--moddir', help='path for model definition')
parser.add_argument(
'--noise',
type=float,
help='0: no noise, non-0: standard deviation of OU process')
parser.add_argument('--tau', type=float, help='tau for OU process')
args = parser.parse_args()
if args.moddir:
moddir = args.moddir
else:
moddir = '.'
run = imp.load_source('run', os.path.join(moddir, 'run.py'))
curtvec = np.load(args.ctvfile)
cellpar = jspar.load(args.cpfile)
outdir = args.outdir
if not os.path.exists(outdir):
raise Exception('No such directory: %s' % outdir)
simfunc = run.cellpar_wrapper(run.simulation, cellpar, args.spkthr)
frtvec = ficurve.get_frtvec(simfunc, curtvec, noise=args.noise, tau=args.tau)
np.save(os.path.join(outdir, 'frtvec.npy'), frtvec)
jspar.save(os.path.join(outdir, 'fipar.json'), vars(args))
import numpy as np
scriptdir = os.path.dirname(os.path.realpath(__file__))
sys.path.append(os.path.join(scriptdir, '..'))
from nrngain import jspar, spktrigavrg
parser = argparse.ArgumentParser()
parser.add_argument('indir',
help='input directory contains spktimes, stimvec, runpar')
parser.add_argument('--maxtau',
help='time range of stimulus before and after spike (ms)')
args = parser.parse_args()
indir = args.indir
if not os.path.exists(indir):
raise OSError('No such directory: {}'.format(indir))
spktimes = np.load(os.path.join(indir, 'spktimes.npy'))
stimvec = np.load(os.path.join(indir, 'stimvec.npy'))
runpar = jspar.load(os.path.join(indir, 'runpar.json'))
if args.maxtau:
maxtau = args.maxtau
else:
maxtau = 500.
dt = runpar['hpar']['dt']
stim_mean = runpar['stimpar']['mean']
sta = spktrigavrg.get_sta(stimvec, spktimes, maxtau, dt, stim_mean)
np.save(os.path.join(indir, 'sta.npy'), sta)
