weaselj

import json

class MapReduce:
    def __init__(self):
        self.data = []
        self.intermediate = {}
        self.result = []

    def emit_intermediate(self, key, value):
        self.intermediate.setdefault(key, [])

weaselj

# Coursera SNA optional Programming Assignment 3 template

# see this blog post for a nice overview of community detection algorithms
# http://www.r-bloggers.com/summary-of-community-detection-algorithms-in-igraph-0-6/

# load the igraph library
# you may have to install this module if you haven't already
import igraph as ig
# read in the graph in GML format
# it is a sampled collection of pages from a strange set of seed categories:

weaselj

# Coursera SNA optional Programming Assignment 2 template

# load the igraph library
# you may have to install this module if you haven't already
import igraph as ig
import numpy as np

# read in the graph in GML format
# it is a sampled collection of pages from a strange set of seed categories:
# Math, Sociology, and Chemistry

weaselj

function MonitorAssignment( F, names, valNames, E )
% MonitorAssignment( F, names, valNames, E ) - Pretty prints all the 
%   marginals for an assignment
%
%   F contains the struct array of factors
%   names contains the variable names
%   valNames contains the assignment names for each variable, 
%    as seen in SAMIAM
%   E is an N-by-2 cell array, each row being a variable/value pair. 
%     Variables are in the first column and values are in the second column.