def test_single_row_random_forest():
import shap
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn.ensemble import RandomForestClassifier
import sklearn
X_train,X_test,Y_train,_ = train_test_split(*shap.datasets.adult(), test_size=0.2, random_state=0)
clf = RandomForestClassifier(random_state=202, n_estimators=10, max_depth=10)
clf.fit(X_train, Y_train)
predicted = clf.predict_proba(X_test)
ex = shap.TreeExplainer(clf)
shap_values = ex.shap_values(X_test.iloc[0,:])
assert np.abs(shap_values[0].sum() + ex.expected_value[0] - predicted[0,0]) < 1e-4, \
"SHAP values don't sum to model output!"
