Demo for obtaining leaf index

import os
import xgboost as xgb

# load data in do training
CURRENT_DIR = os.path.dirname(__file__)
dtrain = xgb.DMatrix(os.path.join(CURRENT_DIR, '../data/agaricus.txt.train'))
dtest = xgb.DMatrix(os.path.join(CURRENT_DIR, '../data/agaricus.txt.test'))
param = {'max_depth': 2, 'eta': 1, 'objective': 'binary:logistic'}
watchlist = [(dtest, 'eval'), (dtrain, 'train')]
num_round = 3
bst = xgb.train(param, dtrain, num_round, watchlist)

print('start testing predict the leaf indices')
# predict using first 2 tree
leafindex = bst.predict(
    dtest, iteration_range=(0, 2), pred_leaf=True, strict_shape=True
)
print(leafindex.shape)
print(leafindex)
# predict all trees
leafindex = bst.predict(dtest, pred_leaf=True)
print(leafindex.shape)