Metadata-Version: 2.1
Name: build2vec
Version: 0.0.5
Summary: Python package for building data embeddings
Home-page: UNKNOWN
Author: Mahmoud Abdelrahman
Author-email: <arch.mahmoud.ouf111@gmail.com>
License: UNKNOWN
Description: 
        # build2Vec
        
        Graph Neural Networks based building representation in the vector space
        
        ## Installation
        
        ```
        $ pip install build2vec
        ```
        
        ## Examples
        
        ```Python
        import networkx as nx
        from build2vec import Build2Vec
        emb_dimensions = 10
        # Create a graph using networkx -- you can generate the graph from dataframe of edges
        
        graph = nx.from_pandas_edgelist(df_links_graph)
        
        build2vec = Build2Vec(graph, dimensions=emb_dimensions, walk_length=50, num_walks=50, workers=1)
        
        model = build2vec.fit(window=50, min_count=1, batch_words=10)
        ```
        
        ## Todos:
        
        1. Add automatic grid generation method.
        2. Add automatic graph construction method.
        3. Add visualization moddule.
        4. Add ML clustering, classification, and prediction moduels.
        5. Define other builing-related random walks methods.
        
        ## Citation:
        
        ```bib
        @inproceedings{abdelrahmanbuild2vec,
            title = {{Build2Vec: Building Representation in Vector Space}},
            year = {2020},
            booktitle = {SimAUD 2020},
            author = {Abdelrahman, Mahmoud M and Chong, Adrian and Miller, Clayton},
            number = {May},
            pages = {101--104},
            publisher = {Society for Modeling {\&} Simulation International (SCS)},
            url = {http://simaud.org/2020/proceedings/102.pdf},
            address = {Online},
            arxivId = {2007.00740},
            keywords = {Feature learning, Graph embeddings, Representation learning, STAR, node2vec}
        }
        ```
        
Keywords: graph,network,building,spatial,spatiotemporal,bim,gis
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: Unix
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: Microsoft :: Windows
Description-Content-Type: text/markdown
