def cSpaceSet(d, cmode='istac', clevel=3):
#FIXME: assumes particular structure for D. Should be a transform.
uc1 = ucse(d['s1'], 10000, LENGTH)
uc2 = ucse(d['s2'], 10000, LENGTH)
rc1 = ece(d['s1'], d['evts1'], LENGTH, LEAD)
rc2 = ece(d['s2'], d['evts2'], LENGTH, LEAD)
istacs = {}
istacs['uc'] = comp(uc2, uc1, clevel)
istacs['rc'] = comp(rc2, rc1, clevel)
istacs['c1'] = comp(rc1, uc1, clevel)
istacs['c2'] = comp(rc2, uc2, clevel)
istacs['j'] = comp(eqrc((rc1, rc2)), np.column_stack([uc1, uc2]), clevel)
return istacs
def comp2s(stim1, evts1, stim2, evts2, length=LENGTH, lead=LEAD, compress='no', clevel=0, testprop=TESTPROP,
bootstrap=BOOTSTRAP, report=None):
'''
Like compare, but considers the case where there are two stimuli in
addition to two response sets
'''
rc1 = ece(stim1, evts1, length, lead)
rc2 = ece(stim2, evts2, length, lead)
if compress in DRMODES:
uc = np.column_stack([ucse(stim1, 10000, length),
ucse(stim2, 10000, length)])
ce = eqrc((rc1, rc2))
cspace = DRMODES[compress](ce, uc, clevel)
if report:
report('Using %i components' % cspace.shape[0])
rc1 = np.dot(cspace, rc1)
rc2 = np.dot(cspace, rc2)
return lltest(rc1, rc2, testprop, bootstrap)
def stacnbackFig(m1, stac=.8):
stim = gwn.getstim('bl')
uc = ucse(stim)
rc = evalSystem(m1, True, cid=0)
iss = istac.istacspace(rc, uc, stac)['vecs']
plt.figure(3)
plt.clf()
_prow(rc, None, 0)
rc1 = np.dot(iss.transpose(), rc)
_prow(rc1, None, 1)
rc2 = np.dot(iss, rc1)
_prow(rc2, None, 2)
f = plt.figure(3)
f.subplots_adjust(left=.04, right=.99, bottom=.05, top=.99, wspace=.05, hspace=.05)
f.canvas.draw()
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
def bigFig(m1, m2, compress='istac', clevel=.85):
stim = gwn.getstim('bl')
uc = ucse(stim)
rcse = evalSystem(m1, True, cid=0)
rcse2 = evalSystem(m2, True, cid=1)
rc = eqrc((rcse, rcse2))
iss = DRMODES[compress](rc, uc, clevel)
report('Using %i components' % iss.shape[0])
plt.figure(3)
plt.clf()
ll = lltest(rcse, rcse2)
_prow(rcse, rcse2, 0, 3, True, ll)
rc1 = np.dot(iss, rcse)
rc2 = np.dot(iss, rcse2)
ll = lltest(rc1, rc2)
_prow(rc1, rc2, 1, 3, True, ll)
rcb1 = np.dot(iss.transpose(), rc1)
rcb2 = np.dot(iss.transpose(), rc2)
#ll = lltest(rcb1, rcb2)
_prow(rcb1, rcb2, 2, 3, True, ll)
f = plt.figure(3)
f.subplots_adjust(left=.04, right=.99, bottom=.05, top=.99, wspace=.05, hspace=.05)
f.canvas.draw()
