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()
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)
