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V 0.5.0

Data Structures

  • Implement a hash map library
    • Create POC, avoid collisions at all costs
    • Throw exceptions for key lookup that don't exist
  • Improvement and fix for the adjacency list data structure
    • Detect unused slots in the graph
    • Don't allocate more nodes that aren't needed for both unweighted, weighted and directed/un-directed graphs
    • Use array of pointers for node_list structure, use arrow deference for head pointer
  • Matrix library
    • Add method for getting columns of matrix to_cols
    • Allow option for batching a matrix and selecting a certain amount or rows

Data Extraction

  • Add hash map as attribute for data frame
    • Replicate similar methods for getting cols and rows
  • Create a prototype of GML (graph markup language)
    • Create a regular expression for parsing this type of file format
    • Create an interpreter that can serialize files
    • Will not do weighted graphs in this version

Deep Learning

  • Refactored computation graph to forward and backward all node types
  • Added refactored computation graph representation to network module

Graph Library

  • Make all random walk methods use the walk structure
    • Easier to use on the python front end
  • Create general graph structure that makes use of data structures
    • Include the adjacency list and matrices as inherited attributes
    • Add attribute for keeping track of labeled nodes
  • Label propagation with multiple classes
    • Should work with more than two labels
    • Discovered that graph markup serialization doesn't work here