def _test_pairplot_with_gmm_outputs(**kws):
X = np.random.rand(15, 3)
gmm = GaussianMixture(n_components=3, **kws).fit(X)
labels = ["A"] * 5 + ["B"] * 5 + ["C"] * 5
cluster_palette = {0: "red", 1: "blue", 2: "green"}
label_palette = {"A": "red", "B": "blue", "C": "green"}
fig = pairplot_with_gmm(X, gmm)
fig = pairplot_with_gmm(
X,
gmm,
labels=labels,
cluster_palette=cluster_palette,
label_palette=label_palette,
)
def _test_pairplot_with_gmm_inputs(caller: unittest.TestCase, **kws):
X = np.random.rand(15, 3)
gmm = GaussianMixture(n_components=3, **kws).fit(X)
labels = ["A"] * 5 + ["B"] * 5 + ["C"] * 5
# test data
with caller.assertRaises(ValueError):
pairplot_with_gmm(X="test", gmm=gmm)
with caller.assertRaises(ValueError):
pairplot_with_gmm(X=X, gmm=gmm, labels=["A"])
with caller.assertRaises(NameError):
pairplot_with_gmm(X, gmm=None)
def test_pairplot_with_gmm_inputs():
X = np.random.rand(15, 3)
gmm = GaussianMixture(n_components=3, covariance_type="full").fit(X)
labels = ["A"] * 5 + ["B"] * 5 + ["C"] * 5
# test data
with pytest.raises(ValueError):
pairplot_with_gmm(X="test", gmm=gmm)
with pytest.raises(ValueError):
pairplot_with_gmm(X=X, gmm=gmm, labels=["A"])
with pytest.raises(NameError):
pairplot_with_gmm(X, gmm=None)