def create_feature_space_IG(n):
	a={}
	weight = {}
	ig, gr, si = textgain.compute('IG')
	sortedIG = sorted(ig,key=ig.__getitem__,reverse=True)
	k = sortedIG[:n]
	for j in range(0,len(k)):
		if k[j] not in a:
			a[k[j]] = len(a)
			weight[k[j]] = ig[k[j]]
	return [a,weight]
def create_feature_space_IG(n):
    a = {}
    weight = {}
    ig, gr, si = textgain.compute('IG')
    sortedIG = sorted(ig, key=ig.__getitem__, reverse=True)
    k = sortedIG[:n]
    for j in range(0, len(k)):
        if k[j] not in a:
            a[k[j]] = len(a)
            weight[k[j]] = ig[k[j]]
    return [a, weight]
def create_feature_space_IG(bi):
    a = {}
    ig, gr, si = textgain.compute('IG')
    sortedIG = sorted(ig, key=ig.__getitem__, reverse=True)
    ki = sortedIG[:8000]
    k = bi[:16000]

    k.extend(ki)
    print len(k)

    for j in range(0, len(k)):
        if k[j] not in a:
            a[k[j]] = len(a)
    return a
def create_feature_space_IG(bi):
	a={}
	ig, gr, si = textgain.compute('IG')
	sortedIG = sorted(ig,key=ig.__getitem__,reverse=True)
	ki = sortedIG[:8000]
	k = bi[:16000]

	k.extend(ki)
	print len(k)

	for j in range(0,len(k)):
		if k[j] not in a:
			a[k[j]] = len(a)
	return a