def confusion(stims, dm):
'''
stims is a tuple of stimulus conditions.
dm is a distance matrix of responses (with the same number of rows as stims)
Returns a confusion matrix between stimulus conditions
'''
di = infdiag(dm)
stimind = np.array(stims)
nstims = stimind.max() + 1
conf = np.zeros((nstims, nstims))
for i in range(di.shape[0]):
inds = np.nonzero(di[i, :] == di[i, :].min())[0]
st = stimind[inds]
sst = stimind[i]
n = 1.0 / inds.shape[0]
for s in st:
conf[sst, s] += n
conf[s, sst] += n
return conf
def treeXformAv(evts, q, dmeth):
dm = infdiag(distance(evts, None, q, dmeth))
wts = np.ones(dm.shape[0])
while len(evts) > 2:
evts, dm, wts = pair_and_av(list(evts), dm, wts, q, dmeth)
return avst(evts[0], evts[1], q, wts[0], wts[1], dmeth)