# cenkbircanoglu/similarityPy Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information. images requirements settings similarityPy tests .gitignore .travis.yml LICENSE MANIFEST.in Makefile README.md make.bat setup.cfg setup.py tox.ini

# Similarity Py  ## Installation

Install the package

`    \$ pip install similarityPy`

## Dependencies

``````enum
``````

###Distance Algorithms

#### Numerical Data

#####  Norm

#####  Manhattan Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Euclidean Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Squared Euclidean Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Normalized Squared Euclidean Distance

#####  Chessboard Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Bray Curtis Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Canberra Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Cosine Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #####  Correlation Distance

Data: [{a, b, c}, {x, y, z}]
Formula: #### Boolean Data

#####  Jaccard Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to , where nij is the number of corresponding pairs of elements in u and v respectively equal to i and j.

#####  Matching Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to (n10+n01)/Length[u], where nij is the number of corresponding pairs of elements in u and v respectively equal to i and j.

#####  Dice Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to , where nij is the number of corresponding pairs of elements in u and v respectively equal to i and j.

#####  Rogers Tanimoto Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to , where nij is the number of corresponding pairs of elements in u and v respectively equal to i and j.

#####  Russell Rao Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to (n10+n01+n00)/Length[u], where nij is the number of corresponding pairs of elements in u and v respectively equal to i and j.

#####  Sokal Sneath Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to , where nij is the number of corresponding pairs of elements in and respectively equal to i and j.

#####  Yule Dissimilarity

Data: [{True,False,True}, {True,True,False}]
Explanation:[u,v] is equivalent to , where nij is the number of corresponding pairs of elements in and respectively equal to i and j.

#### String Data

#####  Hamming Distance

Data: [{a, b, c}, {x, y, z}]
Explanation:[u,v] gives the number of elements whose values disagree in u and v.

#####  Edit Distance

Data: [{a, b, c}, {x, y, z}]
Explanation:[u,v] gives the number of one-element deletions, insertions, and substitutions required to transform u to v.

#####  Damerau Levenshtein Distance

Data: [{a, b, c}, {x, y, z}]
Explanation:[u,v] gives the number of one-element deletions, insertions, substitutions, and transpositions required to transform u to v.

#####  Needleman Wunsch Similarity (Not Implemented Yet)

Data: [{a, b, c}, {x, y, z}]
Explanation:[u,v] finds an optimal global alignment between the elements of u and v, and returns the number of one-element matches.

#####  Smith Waterman Similarity (Not Implemented Yet)

Data: [{a, b, c}, {x, y, z}]
Explanation:[u,v] finds an optimal local alignment between the elements of u and v, and returns the number of one-element matches.

##Testing

Run all tests:

`    \$ python -m unittest discover -s tests -p '*_test.py'`

Start test with nose and code coverage:

`    \$ nosetests --with-cov  --cov-report html  --cov  similarityPy tests/`
You can’t perform that action at this time.