def test_computePageRank(self):
epsilon = 0.00001
nodeCount = 3
graph = lib.newGraph(nodeCount+10, 1, 0.5, epsilon, 2, 0)
lib.addEdgeByIds(graph, 1, 2, 1)
lib.addEdgeByIds(graph, 1, 3, 1)
lib.addEdgeByIds(graph, 2, 3, 1)
lib.addEdgeByIds(graph, 3, 1, 1)
lib.computeIteration(graph)
# initial pageRank
n = lib.findNodeById(graph, 1)
self.assertTrue(abs(n.pageRank_a - 1.0/graph.weightedSize) < epsilon)
n = lib.findNodeById(graph, 2)
self.assertTrue(abs(n.pageRank_a - 1.0/graph.weightedSize) < epsilon)
n = lib.findNodeById(graph, 3)
self.assertTrue(abs(n.pageRank_a - 1.0/graph.weightedSize) < epsilon)
while graph.converged == 0:
lib.computeIteration(graph)
# one more so both a and b have the converged page rank
lib.computeIteration(graph)
a = lib.findNodeById(graph, 1)
b = lib.findNodeById(graph, 2)
c = lib.findNodeById(graph, 3)
# the examples are not normalized so we must divide by nodeCount
# http://pr.efactory.de/e-pagerank-algorithm.shtml
self.assertTrue(abs(a.pageRank_a - 1.07692308 / nodeCount) < epsilon*10)
self.assertTrue(abs(a.pageRank_b - 1.07692308 / nodeCount) < epsilon*10)
self.assertTrue(abs(b.pageRank_a - 0.76923077 / nodeCount) < epsilon*10)
self.assertTrue(abs(b.pageRank_b - 0.76923077 / nodeCount) < epsilon*10)
self.assertTrue(abs(c.pageRank_a - 1.15384615 / nodeCount) < epsilon*10)
self.assertTrue(abs(c.pageRank_b - 1.15384615 / nodeCount) < epsilon*10)
lib.cleanup(graph)
def computeIteration(self):
lib.computeIteration(self.graph)
