def test_invalid_metric(self):
"""Test whether computing RSA with an invalid metric raises error."""
with pytest.raises(ValueError, match='Invalid RSA metric'):
next(rsa_gen(dsm_gen([dsm()]), dsm(), metric='foo'))
# These metrics only work with multiple model DSMs
with pytest.raises(ValueError, match='Need more than one model DSM'):
next(rsa_gen(dsm_gen([dsm()]), dsm(), metric='partial'))
with pytest.raises(ValueError, match='Need more than one model DSM'):
next(rsa_gen(dsm_gen([dsm()]), dsm(), metric='partial-spearman'))
def test_regression(self):
"""Test computing RSA with regression."""
model_dsm1 = np.array([-1, 0, 1])
model_dsm2 = np.array([1, -2, 1])
data_dsm = dsm_gen([3 * model_dsm1 + 5 * model_dsm2])
rsa_val = next(rsa_gen(data_dsm, [model_dsm1, model_dsm2],
metric='regression'))
assert_allclose(rsa_val, [3, 5])
def test_partial_spearman(self):
"""Test computing RSA with partial spearman correlation."""
# Example verified with MATLAB's partialcorr function
model_dsm1 = np.array([1, 2, 3, 4])
model_dsm2 = np.array([0, 0, 1, 1])
data_dsm = dsm_gen([[2, 4, 20, 15]])
rsa_val = next(rsa_gen(data_dsm, [model_dsm1, model_dsm2],
metric='partial-spearman'))
assert_allclose(rsa_val, [0, 2 / 3], atol=1E-15)
def test_partial(self):
"""Test computing RSA with partial correlation."""
# Example taken from https://en.wikipedia.org/wiki/Partial_correlation
model_dsm1 = np.array([1, 2, 3, 4])
model_dsm2 = np.array([0, 0, 1, 1])
data_dsm = dsm_gen([[2, 4, 15, 20]])
rsa_val = next(rsa_gen(data_dsm, [model_dsm1, model_dsm2],
metric='partial'))
assert_allclose(rsa_val, [0.919145, 0.912871])
def test_kendall_tau_a(self):
"""Test computing RSA with Kendall's Tau Alpha"""
data_dsm = dsm_gen([[1, 2, 3]])
model_dsm = np.array([1, 3, 3]) # This metric deals well with ties
rsa_val = next(rsa_gen(data_dsm, model_dsm, metric='kendall-tau-a'))
assert rsa_val == 2 / 3
def test_pearson(self):
"""Test computing RSA with Pearson correlation"""
data_dsm = dsm_gen([[1, 2, 3]])
model_dsm = np.array([2, 3, 3.5])
assert next(rsa_gen(data_dsm, model_dsm, metric='pearson')) < 1.0
def test_spearman(self):
"""Test computing RSA with Spearman correlation"""
data_dsm = dsm_gen([[1, 2, 3]])
model_dsm = np.array([2, 3, 3.5])
assert next(rsa_gen(data_dsm, model_dsm, metric='spearman')) == 1.0
def test_return_type(self):
"""Test return type of rsa_gen"""
assert isinstance(rsa_gen(dsm_gen([dsm()]), dsm()), GeneratorType)
assert next(rsa_gen(dsm_gen([dsm()]), dsm())).shape == tuple()
assert next(rsa_gen(dsm_gen([dsm()]), [dsm()])).shape == (1,)
