def test_PCA(self): """ Regression test. """ trajectory_handler = TrajectoryHandlerStub(testPCAMetric.not_iterposed_coordsets,66) clustering = Clustering([Cluster(None,range(6)),Cluster(None,range(6,12))], "a clustering") pcaMetric = PCAMetric(trajectory_handler) self.assertAlmostEquals(pcaMetric.evaluate(clustering), 1.427748687873, 12)
def test_PCA(self): """ Regression test. """ trajectory_handler = TrajectoryHandlerStub( testPCAMetric.not_iterposed_coordsets, 66) clustering = Clustering( [Cluster(None, range(6)), Cluster(None, range(6, 12))], "a clustering") pcaMetric = PCAMetric(trajectory_handler) self.assertAlmostEquals(pcaMetric.evaluate(clustering), 1.427748687873, 12)
def analysis_function_pca(self, clustering, trajectory_handler): calculator = PCAMetric(trajectory_handler) return calculator.evaluate(clustering)
def analysis_function_pca(self, clustering, data_handler): """ """ calculator = PCAMetric(data_handler) return calculator.evaluate(clustering)
def analysis_function_pca(self,clustering, data_handler): """ """ calculator = PCAMetric(data_handler) return calculator.evaluate(clustering)