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))