VectorDict 1.0.0

dict with recursive operations (algebraic, set, logicial)

Vector Dict provides all the expected operations on a dict as if it was a vector.

• a * vector (where a can be a scalar or a vector)

• vector1 + vector2

• vector1 * vector2

• a / b (where at least one of a and b is a vector)

• cos(vector1,vector2) cosine similarity

• jaccard(vector1, vector2)

VectorDict is derived from defautdict thus it works the same for initialisation.

Properties being propagated to each level, it works on arbitrary depth dict

It provides some helpful helpers : path_from_array as_vector_iter as_row_iter

#!/usr/bin/env python

from vector_dict import VectorDict

a = VectorDict( int, dict( x=1, y=1 ) )

b = VectorDict( int, dict( x=1, y=0, z=0) )

a + b

# Out : defaultdict(<type ‘int’>, {‘y’: 1, ‘x’: 2, ‘z’ : 0 })

a * b

#Out : defaultdict(<class ‘vector_dict.VectorDict’>, {‘y’: 0, ‘x’: 1})

print a.cos(b)

# Out : 0.7071067811865475

# sqrt(2) / 2 = acos(45°)

a.dot(b)

# Out : 1.0

a.norm()

# 1.4142135623730951

a.pprint()

# u’y’=1 # u’x’=1

Helpers

as_vector_iter

A generator of the vector in the form : path to key in the form of a set of keys , value (leaf)

a = VectorDict( int, dict( a=1, b = VectorDict(int, dict(c=1))))

[ (k, v) for k,v in a.as_vector_iter() ]

# Out: [((‘a’,), 1), ((‘b’, ‘c’), 1)]

as_row_iter

A generator of the vector as either tuple of ( (path), obj ) or [ [ path + obj ] ] used for instance to ready a dict for a csv

a = VectorDict( int, dict( a=1, b = VectorDict(int, dict(c=1))))

[ e for e in a.as_row_iter(flatten=False) ]

# Out : [((‘a’,), 1), ((‘b’, ‘c’), 1)]

[ e for e in a.as_row_iter(flatten=True) ]

# Out : [[‘a’, 1], [‘b’, ‘c’, 1]]

from_path_array

Build an intricated dict from an array representing a flat array of keys ending by a value

path_from_array( [ “a”, “b” , 1 ])

# Out : defaultdict(<class ‘vector_dict.VectorDict’>, {‘a’: defaultdict(<class ‘vector_dict.VectorDict’>, {‘b’: 1})})

Bibliography

Cosine similarity and jaccard formula

Introduction to the use of vectors in data mining (in ruby)