def test_no_iso(self):
"""CKA is sensitive to column scaling"""
X, Y = _get_multi()
X0 = X[:, :2]
X0p = X0 @ np.array([[1, 1], [10, 1]])
c1 = cka(X0, Y)
c2 = cka(X0p, Y)
self.assertGreater(abs(c1 - c2), .001)
def test_rotation(self):
"""CKA is insensitive to rotations"""
X, Y = _get_multi()
X0 = X[:, :2]
X0p = X0 @ np.array([[1, -1], [1, 1]]) / np.sqrt(2)
c1 = cka(X0, Y)
c2 = cka(X0p, Y)
self.assertAlmostEqual(c1, c2)
def test_wide(self):
"""Smoke test."""
X, Y = _get_wide()
c1 = cka(X, Y)
def test_value(self):
"""Regression test: for this particular input, check that the value
is the same as it always was."""
X, Y = _get_multi()
c1 = cka(X, Y)
self.assertAlmostEqual(c1, 0.96577, places=4)
def test_isoscaling(self):
"""CKA is insensitive to scaling by a scalar"""
X, Y = _get_multi()
c1 = cka(X, Y)
c2 = cka(2.0 * X, -1 * Y)
self.assertAlmostEqual(c1, c2)
def test_corr(self):
"""The CKA of two vectors is the square of the correlation coefficient"""
X, Y = _get_one()
c1 = cka(X, Y)
c2 = np.corrcoef(X.squeeze(), Y.squeeze())[0, 1]**2
self.assertAlmostEqual(c1, c2)
def test_same(self):
"""The CKA of a matrix and itself is one"""
X, _ = _get_one()
self.assertAlmostEqual(cka(X, X), 1)
def test_wrong_dim(self):
"""It should throw an error if we have a different number of stimuli"""
X = np.ones((8, 1))
Y = np.ones((10, 1))
cka(X, Y)