def vpdist_toset_ps(st, lot, q):
n = len(st)
if n == 0:
return np.ones(len(lot))
d = np.ones(len(lot), np.float64)
q2 = 2.0 / q
for i, e in enumerate(lot):
m = len(e)
if m:
d[i] = et.vpdist(st, e, q2) / (n + m)
return d
def vpdist_ps(lot, q):
q2 = 2.0 / q
nl = len(lot)
dm = np.zeros((nl, nl))
for i in range(nl - 1):
for j in range(i, nl):
n = len(lot[i])
m = len(lot[j])
if not n or not m:
d = 1
else:
d = et.vpdist(lot[i], lot[j], q2) / (n + m)
dm[i, j] = d
dm[j, i] = d
return dm
def vpdist_pe(lot, q):
exp = {'nprob': float(len([x for x in lot if not x])) / len(lot)}
q2 = 2.0 / q
nl = len(lot)
dm = np.zeros((nl, nl))
for i in range(nl - 1):
for j in range(i, nl):
n = len(lot[i])
m = len(lot[j])
if not n or not m:
d = 1
else:
d = et.vpdist(lot[i], lot[j], q2) / (n + m)
dm[i, j] = d
dm[j, i] = d
return dm
def vdC(st1, st2, q):
'''
Should return the same thing as vpP, but much faster. Calls et.vpdist(st1, st2, 2.0/q)
'''
return et.vpdist(st1, st2, 2.0 / q)
