sample_tree(t, m)
else:
if t.c in m:
ch = m[t.c].rvs()
if len(ch) == 2:
lc = tree.Tree(ch[0][0])
rc = tree.Tree(ch[1][0])
sample_tree(lc, m)
sample_tree(rc, m)
t.ch = [lc, rc]
elif len(ch) == 1:
lc = tree.Tree(ch[0])
t.ch = [lc]
R = model.CondModel('R')
for line in sys.stdin:
if line.strip != '':
R.read(line)
m = {}
for c in R:
vals = [None, None]
vals[0] = list(R[c].keys())
vals[1] = np.asarray(list(R[c].values()))
m[c] = rv_discrete_label(values=vals)
for i in range(n):
t = tree.Tree()
sample_tree(t, m)
return (words.index(t) + 1)
heads[t] = max(t.ch, key=lambda x: head_model[t.c][x])
if args.debug:
heads[t].c = 'HEAD:' + heads[t].c + '->' + str(ix)
children = t.ch[:]
head = children.pop(children.index(heads[t]))
headix = get_deps(head, ix, words)
for ch in children:
get_deps(ch, headix, words)
if args.debug:
ch.c += '->' + str(headix)
return (headix)
with open(args.model[0], 'r') as m:
head_model = model.CondModel('R')
for line in m:
head_model.read(line)
t = tree.Tree()
for line in sys.stdin:
heads = {}
deps = {}
t.read(line)
preterminals = preterms(t)
get_deps(t, 0, preterminals)
preterminals.insert(0, tree.Tree('X', [tree.Tree('ROOT', [])]))
if args.debug:
print(t)
for i in range(1, len(preterminals)):
#### create branch- and depth-specific pcfg
import sys, os
sys.path.append(os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg', 'scripts'))
import model
MAX_ITER = 20
#### 0) read model from stdin
mCr = model.Model('Cr')
mCC = model.CondModel('CC')
mCu = model.CondModel('Cu')
mX = model.CondModel('X')
mPc = model.CondModel('Pc')
mPw = model.CondModel('Pw')
mP = model.Model('P')
mW = model.Model('W')
for s in sys.stdin:
mCr.read(s)
mCC.read(s)
mCu.read(s)
mX.read(s)
mPc.read(s)
mPw.read(s)
mP.read(s)
mW.read(s)
## # add terminal rules (comment out if terminal and nonterminal categories intersect)
## for c in mX:
## mCC[c]['-','-'] = 1.0
import model
input = [
"G : who = .1", "G : whom = .9", "P who : who = 1", "P who : whom = 0",
"P whom : who = .2", "P whom : whom = .8", "C who : who = 1",
"C who : whom = 0", "C whom : who = .5", "C whom : whom = .5"
]
G = model.Model('G')
#PgivG
P = model.CondModel('P')
#CgivP
C = model.CondModel('C')
for line in input:
G.read(line)
P.read(line)
C.read(line)
print line
PgivNone = model.Model("PgivNone")
for g in P:
for p in P[g]:
PgivNone[p] += P[g][p] / len(P[p])
GCP = model.Model("GCP")
PC = model.Model("PC")
for g in G:
for p in C:
for c in C[p]:
GCP[g, p, c] = G[g] * P[g][p] * C[p][c]
os.path.join(os.path.dirname(__file__), '..', '..', 'resource-gcg',
'scripts'))
import model
import argparse
argparser = argparse.ArgumentParser(description='''
Counts and divides model-formatted files.
''')
argparser.add_argument('-n',
'--no-normalization',
dest='nonorm',
action='store_true',
help='Do not normalize')
args = argparser.parse_args()
counts = model.CondModel()
for line in sys.stdin:
predictor, _, response = line.strip('\n').rpartition(' : ')
response, count = response.split(' = ') if ' = ' in response else (
response, '1')
counts[predictor][response] += float(count)
if not args.nonorm:
for predictor in sorted(counts):
denominator = sum(
[counts[predictor][val] for val in counts[predictor]])
for response in sorted(counts[predictor]):
print(predictor + ' : ' + response + ' = ' +
str(counts[predictor][response] / denominator))
else:
for predictor in sorted(counts):
import model
input = ["R : ohio = .5", "R : phil = .5", "W : /nek/ = .6", "W : /naek/ = .4",
"O ohio /nek/ : [nek] = 1", "O phil /nek/ : [nek] = .667", "O phil /nek/ : [naek] = .333",
"O ohio /naek/ : [naek] = 1", "O phil /naek/ : [naek] = 1"]
R = model.Model("R")
W = model.CondModel('W')
O = model.CondModel("O")
OgivR = model.CondModel('OR')
for line in input:
R.read(line)
W.read(line)
O.read(line)
OgivNone = model.Model("Onone")
Idata = "I [naek] [nek] [naek]"
IdataSplit = Idata.split()
#w values aren't given for each time step, so condition out
for r, w in O:
for o in O[r,w]:
OgivR[r][o] += O[r,w][o] / 2
OgivNone[o] += O[r,w][o] / 4
#for o in OgivNone:
#print(o, OgivNone[o])