def test_feature_importances_feature_names():
feature_importances = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
feature_names = ['thing_a', 'thing_b', 'thing_c', 'thing_d', 'thing_e']
with open('static/table_ft_names.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(feature_importances,
feature_names=feature_names))
def test_feature_importances_w_subestimators():
rf = Mock()
tree_1 = Mock()
tree_1.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
tree_2 = Mock()
tree_2.feature_importances_ = np.array([0.10, 0.10, 0.8, 0.06, 0.01])
tree_3 = Mock()
tree_3.feature_importances_ = np.array([0.09, 0.01, 0.9, 0.12, 0.02])
tree_4 = Mock()
tree_4.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.01])
rf.estimators_ = [tree_1, tree_2, tree_3, tree_4]
rf.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('tests/static/table_w_subestimator.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(rf))
def test_feature_importances_w_subestimators():
rf = Mock()
tree_1 = Mock()
tree_1.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
tree_2 = Mock()
tree_2.feature_importances_ = np.array([0.10, 0.10, 0.8, 0.06, 0.01])
tree_3 = Mock()
tree_3.feature_importances_ = np.array([0.09, 0.01, 0.9, 0.12, 0.02])
tree_4 = Mock()
tree_4.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.01])
rf.estimators_ = [tree_1, tree_2, tree_3, tree_4]
rf.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('static/table_w_subestimator.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(rf))
def test_feature_importances(self):
with self.assertRaisesRegexp(ValueError, "needed to tabulate"):
table.feature_importances(None)
def test_feature_importances():
model = Mock()
model.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('tests/static/table.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(model))
def test_feature_importances_top3():
ft_imp = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('tests/static/table_top3.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(ft_imp, top_n=3))
def test_feature_importances_from_array():
feature_importances = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('tests/static/table.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(feature_importances))
def test_feature_importances_top3():
ft_imp = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('static/table_top3.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(ft_imp, top_n=3))
def test_feature_importances_from_array():
feature_importances = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('static/table.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(feature_importances))
def test_feature_importances():
model = Mock()
model.feature_importances_ = np.array([0.12, 0.10, 0.8, 0.06, 0.03])
with open('static/table.txt', 'r') as f:
expected = f.read()
assert expected == str(table.feature_importances(model))