dheerajrajagopal

#! /usr/bin/env python

import math

def wilson( total, correct):
	z = 1.96 # can be changed to a suitable value you want. 
	p = float(correct) / total
	center =  (p + 1 / 2.0 / total * z * z) / (1 + 1.0 / total * z * z)
	d = z * math.sqrt((p * (1 - p) + 1 / 4.0 / total * z * z) / total) / (1 + 1.0 / total * z * z) 	
	t = (center, d)

dheerajrajagopal

import numpy as np
from scipy.sparse import csc_matrix
import random

def column(matrix, i):
    return [row[i] for row in matrix]

def pageRank(G, s = 0.85, maxerr = .001):
    """
    Computes the pagerank for each of the n states.

dheerajrajagopal

import numpy as np
from scipy.sparse import csc_matrix

def pageRank(G, s = .85, maxerr = .001):
    """
    Computes the pagerank for each of the n states.

    Used in webpage ranking and text summarization using unweighted
    or weighted transitions respectively.