def test_plot_distance_crp(data, distances):
"""Test plotting a distance CRP curve."""
edges = [0.5, 1.5, 2.5, 3.5]
stat = fr.distance_crp(data, 'item_index', distances, edges)
g = fr.plot_distance_crp(stat, min_samples=2)
plt.close()
assert isinstance(g, sns.FacetGrid)
def test_distance_crp_unique(self):
crp = fr.distance_crp(self.data,
'item_index',
self.distances,
self.edges,
count_unique=True)
actual = np.array([0, 1, 1])
possible = np.array([1, 1, 1])
prob = np.array([0, 1, 1])
np.testing.assert_array_equal(crp['actual'], actual)
np.testing.assert_array_equal(crp['possible'], possible)
np.testing.assert_array_equal(crp['prob'], prob)
def test_distance_crp_unique(data, distances2):
"""Test distance CRP analysis with unique counts only."""
edges = [0.5, 1.5, 2.5, 3.5]
crp = fr.distance_crp(data,
'item_index',
distances2,
edges,
count_unique=True)
actual = np.array([0, 1, 1])
possible = np.array([1, 1, 1])
prob = np.array([0, 1, 1])
np.testing.assert_array_equal(crp['actual'], actual)
np.testing.assert_array_equal(crp['possible'], possible)
np.testing.assert_array_equal(crp['prob'], prob)