- In order to form a reindexed egoistic database structure, necessarily algorithms are implemented, through this database strusture (as a dictionary that can save and load through pickle) provide a mobile database to the user.
- Algorithms are changed to generate database only render the data obtained from the wiring database (randirect_database_generation, create_graph..).
- Pandas headline colons('InNode')('TermNode') is adjusted to the actual database colon names to get data properly.
- Actual_Databases (HIPPIE-confidence-075.csv) is added.
Note: Body code going to execute to reindex database as goistic structure present in the search graphlet file (In #Trial1).
- From this version graphlets can be introduced to the library as Object.
- Defined graphlets can be search inside the bigger Graphs; Subgraphs that are is defined in terms of the size graphlets of interest added to found_list, if they are isomorphically identical like 4-cliques, 3-stars etc...
- Subgraphs that are isomorph with the outlines of graphlets (like cliques, stars etc..) can be plotted and save as figure as it's identity.
- The algorithm gives common nodes, edges and fused nodes, edges is coded.
- Also Spectral comparison, Vertex/Edge Overlap comparison and Get Edit Distance comparison algorithms are coded to the the Spectral_VeO_GeD_comparison.py
- Defined networkx databases can be manipulatd through directd randomization algorithm coded in generate_randirected_db.py, also can be plotted
- Different networkx defined databases corresponds (G1,G2..) can be project to fusion matrices that is generated from fused ndoe_lists
- Comparison algorithm is coded to compare_binary_interacted_networks.py script, projected Graphs can be compared in terms of it's edge_binarial identity.
- Compared graphs can be evaluated in the score functions that render with x**2
- The databases contains random nades are assigned to Networkx.
- Defined Networkx databases can be plotted through implied algorithm through matplotlib