def page_rank(
graph: Matrix,
page_rank: Vector,
damping_factor=0.85,
threshold=1.e-5,
max_iters=None):
if max_iters is None:
c.algorithm(
algorithm = "page_rank",
graph = graph,
page_rank = page_rank,
damping_factor = damping_factor,
threshold = threshold,
)
else:
c.algorithm(
algorithm = "page_rank",
graph = graph,
page_rank = page_rank,
damping_factor = damping_factor,
threshold = threshold,
max_iters = max_iters
)
return page_rank
def bfs_level_masked_v2(graph, wavefront, levels):
c.algorithm(
algorithm = "bfs_level_masked_v2",
graph = graph,
wavefront = wavefront,
levels = levels
)
return levels
def mst(graph: Matrix, parents: Vector):
return c.algorithm(
algorithm = "mst",
graph = graph,
parents = parents
)
def vertex_out_degree(graph: Matrix, vid: int):
return c.algorithm(
algorithm = "vertex_out_degree",
graph = graph
)(
vid = vid
)
def triangle_count_newGBTL(l_matrix: Matrix, u_matrix: Matrix):
return c.algorithm(
algorithm = "triangle_count_newGBTL",
l_matrix = l_matrix,
u_matix = u_matrix
)
def sssp(graph: Matrix, path: Vector):
return c.algorithm(
algorithm = "sssp",
graph = graph,
path = path
)
def vertex_eccentricity(graph: Matrix, vid: int):
return c.algorithm(
algorithm = "vertex_eccentricity",
graph = graph
)(
vid = vid
)
def bfs(graph: Matrix, wavefront: Vector, parent_list=None):
if not isinstance(wavefront, Vector):
print("creating wavefront")
w = [0] * graph.shape[1]
w[wavefront] = 1
wavefront = Vector(w)
if parent_list is None:
print("creating parent_list")
parent_list = Vector([0] * graph.shape[1])
c.algorithm(
algorithm = "bfs",
graph = graph,
wavefront = wavefront,
parent_list = parent_list
)
def closeness_centrality(graph: Matrix, vid: int):
return c.algorithm(
algorithm = "closeness_centrality",
graph = graph
)(
vid = vid
)
def bfs_batch(graph: Matrix, wavefronts: Matrix, parent_list=None):
# TODO
#if not isinstance(wavefront, Matrix):
# w = [0] * graph.shape[1]
# w[wavefront] = 1
# wavefront = Vector(w)
if parent_list is None:
parent_list = Matrix(shape=graph.shape, dtype=graph.dtype)
c.algorithm(
algorithm = "bfs_batch",
graph = graph,
wavefronts = wavefronts,
parent_list = parent_list
)
return parent_list
def mis(graph: Matrix, independent_set: Vector, seed: int = 0):
return c.algorithm(
algorithm = "mis",
graph = graph,
independent_set = independent_set
)(
seed = seed
)
def maxflow(capacity: Matrix, source: int, sink: int):
return c.algorithm(
algorithm = "maxflow",
capacity = capacity
)(
source = source,
sink = sink
)
def graph_distance_matrix(graph: Matrix, result: Matrix = None):
if result is None:
result = Matrix(shape=graph.shape, dtype=graph.dtype)
return c.algorithm(
algorithm = "graph_distance",
graph = graph,
result = result,
)
def graph_distance(graph: Matrix, sid: int, result: Vector=None):
if result is None:
result = Vector(shape=graph.shape[0], dtype=graph.dtype)
return c.algorithm(
algorithm = "graph_distance",
graph = graph,
result = result,
)(
sid = sid
)
def graph_radius(graph: Matrix):
return c.algorithm(
algorithm = "graph_radius",
graph = graph
)
def graph_diameter(graph: Matrix):
return c.algorithm(
algorithm = "graph_diameter",
graph = graph
)
def get_vertex_IDs(independent_set: Matrix):
return c.algorithm(
algorithm = "get_vertex_IDs",
independent_set = independent_set
)
def triangle_count(graph: Matrix):
return c.algorithm(
algorithm = "triangle_count",
graph = graph
)
def triangle_count_masked(graph: Matrix):
return c.algorithm(
algorithm = "triangle_count_masked",
graph = graph
)