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Add back support for scipy.sparse.coo_matrix (#6162)

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Philip Hyunsu Cho 2020-09-25 00:49:49 -07:00 committed by GitHub
parent 72ef553550
commit bd2b1eabd0
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2 changed files with 20 additions and 0 deletions
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11
python-package/xgboost/data.py
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@ -82,6 +82,15 @@ def _from_scipy_csc(data, missing, feature_names, feature_types):
return handle, feature_names, feature_types return handle, feature_names, feature_types
def _is_scipy_coo(data):
try:
import scipy
except ImportError:
scipy = None
return False
return isinstance(data, scipy.sparse.coo_matrix)
def _is_numpy_array(data): def _is_numpy_array(data):
return isinstance(data, (np.ndarray, np.matrix)) return isinstance(data, (np.ndarray, np.matrix))
@ -504,6 +513,8 @@ def dispatch_data_backend(data, missing, threads,
return _from_scipy_csr(data, missing, feature_names, feature_types) return _from_scipy_csr(data, missing, feature_names, feature_types)
if _is_scipy_csc(data): if _is_scipy_csc(data):
return _from_scipy_csc(data, missing, feature_names, feature_types) return _from_scipy_csc(data, missing, feature_names, feature_types)
if _is_scipy_coo(data):
return _from_scipy_csr(data.tocsr(), missing, feature_names, feature_types)
if _is_numpy_array(data): if _is_numpy_array(data):
return _from_numpy_array(data, missing, threads, feature_names, return _from_numpy_array(data, missing, threads, feature_names,
feature_types) feature_types)

9
tests/python/test_dmatrix.py
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@ -76,6 +76,15 @@ class TestDMatrix(unittest.TestCase):
assert dtrain.num_row() == 3 assert dtrain.num_row() == 3
assert dtrain.num_col() == 3 assert dtrain.num_col() == 3
def test_coo(self):
row = np.array([0, 2, 2, 0, 1, 2])
col = np.array([0, 0, 1, 2, 2, 2])
data = np.array([1, 2, 3, 4, 5, 6])
X = scipy.sparse.coo_matrix((data, (row, col)), shape=(3, 3))
dtrain = xgb.DMatrix(X)
assert dtrain.num_row() == 3
assert dtrain.num_col() == 3
def test_np_view(self): def test_np_view(self):
# Sliced Float32 array # Sliced Float32 array
y = np.array([12, 34, 56], np.float32)[::2] y = np.array([12, 34, 56], np.float32)[::2]