def test_correlation(self): fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__") values = [random.random() for i in range(0, 100)] values = [[x, x + random.random() / 2] for x in values] tbl = TableFormula(["x", "y"], values) cov = tbl.covariance() assert len(cov.values) == 2 assert len(cov.header) == 3 assert cov[1, 1] == cov[0, 2] cor = tbl.correlation() assert len(cor.values) == 2 assert len(cor.header) == 3 assert cov[1, 1] == cov[0, 2] assert abs(cor[0, 1] - cor[1, 2]) < 1e-5 assert abs(1 - cor[1, 2]) < 1e-5
def test_correlation(self): fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__") values = [random.random() for i in range(0, 100)] values = [[x, x + random.random() / 2] for x in values] tbl = TableFormula(["x", "y"], values) cov = tbl.covariance() assert len(cov.values) == 2 assert len(cov.header) == 3 assert cov[1, 1] == cov[0, 2] cor = tbl.correlation() assert len(cor.values) == 2 assert len(cor.header) == 3 assert cov[1, 1] == cov[0, 2] assert abs(cor[0, 1] - cor[1, 2]) < 1e-5 assert abs(1 - cor[1, 2]) < 1e-5
def test_correlation(self): fLOG(__file__, self._testMethodName, OutputPrint=__name__ == "__main__") values = [random.random() for i in range(0, 100)] values = [[x, x + random.random() / 2] for x in values] tbl = TableFormula(["x", "y"], values) cov = tbl.covariance() assert len(cov.values) == 2 assert len(cov.header) == 3 assert cov[1, 1] == cov[0, 2] cor = tbl.correlation() assert len(cor.values) == 2 assert len(cor.header) == 3 assert cov[1, 1] == cov[0, 2] assert abs(cor[0, 1] - cor[1, 2]) < 1e-5 assert abs(1 - cor[1, 2]) < 1e-5 assert tbl.shape is not None tbl[0, 0] = 0. tbl[0, 1] = 0. row = tbl[0] assert row is not None assert tbl[0, 0] == 0 row = tbl[:1] assert row is not None row = tbl[[0]] assert row is not None tbl2 = None assert tbl != tbl2 tbl2 = tbl assert tbl == tbl2 res = tbl.avg_std(lambda r: r['x']) self.assertIsInstance(res, tuple) cor = tbl.correlation_col('x', 'y') self.assertIsInstance(cor, float) cor = tbl.correlation_row(0, 1) self.assertIsInstance(cor, float) cor = tbl.covariance_row(0, 1) self.assertIsInstance(cor, float) cor = tbl.correlation() self.assertEqual(cor.shape, (2, 3)) cor = tbl.correlation(useBootstrap=True) self.assertEqual(cor.shape, (2, 3))