def test_std_usage(self):
zikm = eda.ZeroIGKdeMdl(self.x)
np.testing.assert_allclose(zikm.x, self.x)
assert zikm.x is not self.x
np.testing.assert_allclose(zikm.x_nonzero, self.x[50:250])
np.testing.assert_allclose(zikm.mdl, zikm.zi_mdl + zikm.kde_mdl)
np.testing.assert_allclose(
zikm.zi_mdl,
np.log(3) + eda.MultinomialMdl(self.x != 0).mdl)
assert zikm._bw_method == "scott"
assert zikm.bandwidth is not None
# test > 0 value kde same
zikm2 = eda.ZeroIGKdeMdl(self.x[50:250])
np.testing.assert_allclose(zikm2.kde_mdl, zikm.kde_mdl)
np.testing.assert_allclose(zikm2.bandwidth, zikm.bandwidth)
def test_encode(self):
# retrospect
np.testing.assert_allclose(
eda.MultinomialMdl([0]).mdl,
eda.MultinomialMdl([0]).mdl)
np.testing.assert_allclose(
eda.MultinomialMdl(np.arange(10)).mdl,
eda.MultinomialMdl(np.arange(10)).mdl)
np.testing.assert_allclose(
eda.MultinomialMdl([0, 1, 2, 10, -10]).mdl,
eda.MultinomialMdl([0, 1, 2, 10, -10]).mdl)
np.testing.assert_allclose(
eda.MultinomialMdl([0]).encode([0, 1, 5, 100, 200, -20],
use_adjescent_when_absent=True), 0)
np.testing.assert_allclose(
eda.MultinomialMdl([0]).encode([0, 1, 5, 100, 200, -20],
use_adjescent_when_absent=False),
np.log(200 * 2) * 5)
np.testing.assert_allclose(
eda.MultinomialMdl([]).encode([0, 1, 5, 100, 200, -20],
use_adjescent_when_absent=False),
np.log(200 * 2) * 6)
np.testing.assert_allclose(
eda.MultinomialMdl([0]).encode([0, 1, 5, 100, 200, -20]),
np.log(200 * 2) * 5)
assert eda.MultinomialMdl([0]).encode([]) == 0
np.testing.assert_allclose(
eda.MultinomialMdl([0, 0, 3, 3,
3]).encode([-20, 0, 2, 5, 100, 200],
use_adjescent_when_absent=True),
-np.log(0.4) * 2 - np.log(0.6) * 4)
np.testing.assert_allclose(
eda.MultinomialMdl([0, 0, 3, 3,
3]).encode([-20, 1, 1.5, 2, 100, 200],
use_adjescent_when_absent=True),
-np.log(0.4) * 2 - np.log(0.6) * 4)
def test_getter(self):
mmdl = eda.MultinomialMdl([])
assert mmdl.x.tolist() == []
mmdl2 = eda.MultinomialMdl([0, 0, 1, 1, 1])
assert mmdl2.x.tolist() == [0, 0, 1, 1, 1]
def test_multi_levels(self):
x = [1] * 10 + [2] * 25
_, uxcnt = np.unique(x, return_counts=True)
mmdl = eda.MultinomialMdl(x)
np.testing.assert_allclose(mmdl.mdl,
(-np.log(uxcnt / len(x)) * uxcnt).sum())
def test_single_level(self):
mmdl = eda.MultinomialMdl([1] * 10)
np.testing.assert_allclose(mmdl.mdl, np.log(10))
def test_empty_x(self):
mmdl = eda.MultinomialMdl([])
assert mmdl.mdl == 0