Merge pull request #26 from Bears-R-Us/code-module-overhaul

updated code modules, tests, and documentation

arachne/README.md

@@ -47,6 +47,6 @@ python3 bfs.py node port -d /path/to/arkouda-njit/arachne/data -t 10
 ## Testing
 The Arachne tests are executed from the arkouda-njit/arachne directory as follows:
 ```
-python3 -m pytest test/bfs_test.py test/reading_test.py test/class_test.py
+python3 -m pytest test/algorithm_test.py test/class_test.py test/prop_graph_test.py test/reading_test.py
 ```
 **Note**: Errors when executing using pytest from arachne directory. 

arachne/arachne_simple_tests.py

@@ -22,7 +22,7 @@ def create_parser():
     src = ak.array([34, 23, 34, 23, 23, 89])
     dst = ak.array([23, 34, 89, 89, 89, 89])
     wgt = ak.array([98, 12, 13, .4, 23, 12])
-    graph = ar.DiGraph()
+    graph = ar.PropGraph()
     graph.add_edges_from(src, dst, wgt)
 
     # Add node labels to the property graph.
@@ -102,8 +102,8 @@ def create_parser():
     print("Edges with property since from 2011 =\n", edge_property_filter.__repr__())
     print()
 
-    H = ar.subgraph_view(graph, filter_labels=node_label_filter, filter_relationships=edge_relationship_filter, filter_node_properties=node_property_filter, filter_edge_properties=edge_property_filter)
+    subgraph = ar.subgraph_view(graph, ar.Graph(), filter_labels=node_label_filter, filter_relationships=edge_relationship_filter, filter_node_properties=node_property_filter, filter_edge_properties=edge_property_filter)
     print(graph.edges())
-    print(H.edges())
+    print(subgraph.edges())
 
     ak.shutdown()

arachne/client/README.md

@@ -7,12 +7,14 @@ Due to the emergence of massive real-world graphs such as social networks, compu
 - Graph Double-Index Data Structuren Class(es) and Methods
     - `Graph` class for undirected (un)weighted graphs. 
     - `DiGraph` class for directed weighted graphs. 
+    - `PropGraph` class for property graphs that can hold node labels, edge relationships, and properties for both nodes and edges.
     - `__len__(self) -> int` returns the number of vertices of a Graph (DiGraph) G. Use `len(G)`.
     - `size(self) -> int` returns the number of edges of a Graph (DiGraph) G. Use `G.size()`.
     - `add_edges_from(self, akarray_src: pdarray, akarray_dst: pdarray, akarray_weight: Union[None, pdarray] = None) -> None` adds to a Graph (DiGraph) object edges from arkouda arrays. The arrays `akarray_src` and `akarray_dst` must be specificed. An optional extra array called `akarray_weight` could be used to make a weighted Graph (DiGraph).
+    - **More found in arachne.py**
 - Graph Building Methods
     - `read_edgelist(path: str, weighted: bool = False, directed: bool = False, comments: str = "#", filetype: str = "txt") -> Union[Graph, DiGraph]` returns a Graph or DiGraph object with read graph data. Removes self-loops and multiedges. Has option to enable reading in a matrix market file that is typically used to store graphs. 
     - `read_known_edgelist(ne: int, nv: int, path: str, weighted: bool = False, directed: bool = False, comments: str = "#", filetype: str = "txt") -> Union[Graph, DiGraph]` returns a Graph or DiGraph object with read graph data. Does not remove self-loops or multiedges. Intended for use when the number of vertices or edges are known for faster graph building times. 
 - Algorithms
     - `bfs_layers(graph: Graph, source: int) -> pdarray` returns a depth array with how far each vertex is from the source vertex. Currently, we only support single source BFS.
-    - **More to Come!**
+    - **More found in arachne.py**