Metadata-Version: 2.1
Name: interspace
Version: 0.0.10
Summary: Interspace gives us different type distances between two vectors.
Home-page: https://github.com/rehanguha/interspace
Author: Rehan Guha
Author-email: rehanguha29@gmail.com
License: mit
Description: 
        # Interspace
        Gives us different distance between two vectors which are given in as an input.
        
        ## Installation
        
        ```bash
        pip install interspace
        ```
        
        ## Different Distance Functions
        
        - [Minkowski distance(p-Norm Distance)](https://en.wikipedia.org/wiki/Minkowski_distance)
        >minkowski(vector_1, vector_2, p=1)
        - [Euclidean distance (2-norm distance)](https://en.wikipedia.org/wiki/Euclidean_distance)
        >euclidean(vector_1, vector_2)
        -  [Manhattan distance/Taxicab norm](https://en.wikipedia.org/wiki/Taxicab_geometry)
        >manhattan(vector_1, vector_2)
        - [Cosine Similarity](https://en.wikipedia.org/wiki/Cosine_similarity)
        >cosine_similarity(vector_1, vector_2)
        - [Haversine formula](https://en.wikipedia.org/wiki/Haversine_formula)
        >haversine(coord1, coord2, R = 6372800)
        - [Hamming distance](https://en.wikipedia.org/wiki/Hamming_distance)
        >hamming(int, int); hamming(str, str) # where, length of both the strings should be same
        - [Mahalanobis distance](https://en.wikipedia.org/wiki/Mahalanobis_distance)
        >mahalanobis(vector_1, vector_2, inverse_of_the_covariance_matrix)
        
        
        ## Usage
        
        ```python
        import interspace
        
        # Calculate Euclidean Distace
        interspace.euclidean([1,2,3],[4,5,6])
        ##Output: 5.196152422706632
        
        # Compute the great-circle distance between two points on a sphere 
        # given their longitudes and latitudes.
        interspace.haversine((42.5170365,  15.2778599),(51.5073219,  -0.1276474))
        ##Output: 1532329.6237517272
        ```
Keywords: distance,ml,machine learning,maths,vectors,space
Platform: UNKNOWN
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: Scientific/Engineering
Classifier: Intended Audience :: Developers
Requires-Python: >=2.7
Description-Content-Type: text/markdown
