def __init__(self, pars):
self.compress = pars['compress']
self.clevel = pars['clevel']
self.doc = gwn.getstim('doc', pars['slen'])
self.snn = self.doc.find(timeseries_t, True)
self.ac = acell.acell()
self.cm = acell.compare()
self.nd = pars['nd']
Model.__init__(self, pars)
def runSystems(stimuli=STIMS_BAND_OL, systems=(M200_FO,), stimlength=800, length=60, lead=40,
label="A", date="", comments="", edet=(1.0, .01)):
'''
stimuli is a list of "band" parameter tuples. Systems is a list of
(off, mean, cov) test system parameter tuples. "l" is a stimulus length.
Constructs each stimulus in the stimulus list, and passes it to each
system.
'''
if not date:
date = time.strftime("%m%d%y")
s = gd.Doc()
s['label'] = 'iSTACe' + date + label
s['comments'] = comments
s['samplerate'] = 1000.0
s['stimlength'] = stimlength
s['enslength'] = length
s['enslead'] = lead
s['eventgenerator'] = 'peakdet'
for i, b in enumerate(stimuli):
sn = "s%i" % i
s[sn + '._'] = gwn.getstim('bl', stimlength, b)
s[sn + '.band'] = b
un = "u%i" % i
s[un + '._'] = ucse(s[sn + '._'], 10000, length)
for i, p in enumerate(systems):
mn = "m%i" % i
off, mu, sig = p
d = {'mu': mu, 'off': off, 'sigma': sig, 'cid': i, 'ejit': edet[0], 'ethresh': edet[1]}
s.set(mn, d)
for j in range(len(stimuli)):
en = "e%i_%i" % (i, j)
sn = "s%i" % j
d['outpath'] = en
d['stimpath'] = "->" + sn
s = s.fuse(acell(s, d)[0])
s[en + '.stim'] = {'_link': sn}
s[en + '.sys'] = {'_link': mn}
rn = "r%i_%i" % (i, j)
s[rn + '._'] = ece(s[sn + '._'], s[en + '._'], length, lead)
s[rn + '.stim'] = {'_link': sn}
s[rn + '.sys'] = {'_link': mn}
return s
ll = self.callWith(comp2s, paths, pars)
c12 = (ll[0, 0, 0] - ll[0, 1, 0]) / (ll[0, 0, 1] + ll[0, 1, 1])
c21 = (ll[1, 1, 0] - ll[1, 0, 0]) / (ll[1, 0, 1] + ll[1, 1, 1])
out[pars['outpath']] = min(c12, c21)
out[pars['outpath'] + '.raw'] = ll
compare2 = Compare2s()
if __name__ == "__main__":
import gwn
s = gwn.getstim().fuse(gwn.getstim(band=(1, 400)))
s['m1.outpath'] = 'evts1'
s['m1.stimpath'] = 'stim5_150'
d, r = acell(s, 'm1')
for st in r:
print(st)
s['m2.outpath'] = 'evts2'
s['m2.stimpath'] = 'stim1_400'
d2, r = acell(s, 'm2')
for st in r:
print(st)
d = d.fuse(d2)
d['stim1'] = s['stim5_150']
d['stim2'] = s['stim1_400']
cmo = {'evts1': 'evts1', 'evts2': 'evts2', 'stim1': 'stim1', 'stim2': 'stim2'}
print d['evts1']
d3, r = compare2(d, cmo)
print(d3['fitness'], d3.d.fitness.raw)
